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              <p class="caption"><span class="caption-text">Notes</span></p>
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<li class="toctree-l1"><a class="reference internal" href="notes/amp_examples.html">Automatic Mixed Precision examples</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/autograd.html">Autograd mechanics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/broadcasting.html">Broadcasting semantics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/cpu_threading_torchscript_inference.html">CPU threading and TorchScript inference</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/cuda.html">CUDA semantics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/ddp.html">Distributed Data Parallel</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/extending.html">Extending PyTorch</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/faq.html">Frequently Asked Questions</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/gradcheck.html">Gradcheck mechanics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/hip.html">HIP (ROCm) semantics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
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<li class="toctree-l1"><a class="reference internal" href="notes/multiprocessing.html">Multiprocessing best practices</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/randomness.html">Reproducibility</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/serialization.html">Serialization semantics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/windows.html">Windows FAQ</a></li>
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<p class="caption"><span class="caption-text">Language Bindings</span></p>
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<li class="toctree-l1"><a class="reference internal" href="named_tensor.html">Named Tensors</a></li>
<li class="toctree-l1"><a class="reference internal" href="name_inference.html">Named Tensors operator coverage</a></li>
<li class="toctree-l1"><a class="reference internal" href="__config__.html">torch.__config__</a></li>
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<li class="toctree-l1"><a class="reference external" href="https://pytorch.org/serve">TorchServe</a></li>
<li class="toctree-l1"><a class="reference external" href="http://pytorch.org/xla/">PyTorch on XLA Devices</a></li>
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<p class="caption"><span class="caption-text">Community</span></p>
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<li class="toctree-l1"><a class="reference internal" href="community/contribution_guide.html">PyTorch Contribution Guide</a></li>
<li class="toctree-l1"><a class="reference internal" href="community/governance.html">PyTorch Governance</a></li>
<li class="toctree-l1"><a class="reference internal" href="community/persons_of_interest.html">PyTorch Governance | Persons of Interest</a></li>
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      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.SimpleElasticAgent._exit_barrier">_exit_barrier() (torch.distributed.elastic.agent.server.SimpleElasticAgent method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.SimpleElasticAgent._initialize_workers">_initialize_workers() (torch.distributed.elastic.agent.server.SimpleElasticAgent method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.SimpleElasticAgent._monitor_workers">_monitor_workers() (torch.distributed.elastic.agent.server.SimpleElasticAgent method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.SimpleElasticAgent._rendezvous">_rendezvous() (torch.distributed.elastic.agent.server.SimpleElasticAgent method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.SimpleElasticAgent._restart_workers">_restart_workers() (torch.distributed.elastic.agent.server.SimpleElasticAgent method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.SimpleElasticAgent._shutdown">_shutdown() (torch.distributed.elastic.agent.server.SimpleElasticAgent method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.SimpleElasticAgent._start_workers">_start_workers() (torch.distributed.elastic.agent.server.SimpleElasticAgent method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.SimpleElasticAgent._stop_workers">_stop_workers() (torch.distributed.elastic.agent.server.SimpleElasticAgent method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="A">A</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.abs.html#torch.abs">abs() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.abs.html#torch.Tensor.abs">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.abs_.html#torch.Tensor.abs_">abs_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.absolute.html#torch.absolute">absolute() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.absolute.html#torch.Tensor.absolute">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.absolute_.html#torch.Tensor.absolute_">absolute_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.AbsTransform">AbsTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="generated/torch.acos.html#torch.acos">acos() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.acos.html#torch.Tensor.acos">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.acos_.html#torch.Tensor.acos_">acos_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.acosh.html#torch.acosh">acosh() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.acosh.html#torch.Tensor.acosh">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.acosh_.html#torch.Tensor.acosh_">acosh_() (torch.Tensor method)</a>
</li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.TimerClient.acquire">acquire() (torch.distributed.elastic.timer.TimerClient method)</a>
</li>
      <li><a href="generated/torch.optim.Adadelta.html#torch.optim.Adadelta">Adadelta (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.optim.Adagrad.html#torch.optim.Adagrad">Adagrad (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.optim.Adam.html#torch.optim.Adam">Adam (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.optim.Adamax.html#torch.optim.Adamax">Adamax (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.optim.AdamW.html#torch.optim.AdamW">AdamW (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.nn.functional.adaptive_avg_pool1d.html#torch.nn.functional.adaptive_avg_pool1d">adaptive_avg_pool1d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.adaptive_avg_pool2d.html#torch.nn.functional.adaptive_avg_pool2d">adaptive_avg_pool2d() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.adaptive_avg_pool2d">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.adaptive_avg_pool3d.html#torch.nn.functional.adaptive_avg_pool3d">adaptive_avg_pool3d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.adaptive_max_pool1d.html#torch.nn.functional.adaptive_max_pool1d">adaptive_max_pool1d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.adaptive_max_pool2d.html#torch.nn.functional.adaptive_max_pool2d">adaptive_max_pool2d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.adaptive_max_pool3d.html#torch.nn.functional.adaptive_max_pool3d">adaptive_max_pool3d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.AdaptiveAvgPool1d.html#torch.nn.AdaptiveAvgPool1d">AdaptiveAvgPool1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.AdaptiveAvgPool2d.html#torch.nn.AdaptiveAvgPool2d">AdaptiveAvgPool2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.AdaptiveAvgPool3d.html#torch.nn.AdaptiveAvgPool3d">AdaptiveAvgPool3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.AdaptiveLogSoftmaxWithLoss.html#torch.nn.AdaptiveLogSoftmaxWithLoss">AdaptiveLogSoftmaxWithLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.AdaptiveMaxPool1d.html#torch.nn.AdaptiveMaxPool1d">AdaptiveMaxPool1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.AdaptiveMaxPool2d.html#torch.nn.AdaptiveMaxPool2d">AdaptiveMaxPool2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.AdaptiveMaxPool3d.html#torch.nn.AdaptiveMaxPool3d">AdaptiveMaxPool3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.add.html#torch.add">add() (in module torch)</a>

      <ul>
        <li><a href="distributed.html#torch.distributed.Store.add">(in module torch.distributed.Store)</a>
</li>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_store.EtcdStore.add">(torch.distributed.elastic.rendezvous.etcd_store.EtcdStore method)</a>
</li>
        <li><a href="generated/torch.Tensor.add.html#torch.Tensor.add">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.add_.html#torch.Tensor.add_">add_() (torch.Tensor method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_audio">add_audio() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_custom_scalars">add_custom_scalars() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.add_dependency">add_dependency() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="futures.html#torch.futures.Future.add_done_callback">add_done_callback() (torch.futures.Future method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_embedding">add_embedding() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_figure">add_figure() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_graph">add_graph() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_histogram">add_histogram() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_hparams">add_hparams() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_image">add_image() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_images">add_images() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_mesh">add_mesh() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="profiler.html#torch.profiler.profile.add_metadata">add_metadata() (torch.profiler.profile method)</a>
</li>
      <li><a href="profiler.html#torch.profiler.profile.add_metadata_json">add_metadata_json() (torch.profiler.profile method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.add_module">add_module() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.add_module">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="torch.quantization.html#torch.quantization.add_observer_">add_observer_() (in module torch.quantization)</a>
</li>
      <li><a href="distributed.optim.html#torch.distributed.optim.ZeroRedundancyOptimizer.add_param_group">add_param_group() (torch.distributed.optim.ZeroRedundancyOptimizer method)</a>

      <ul>
        <li><a href="generated/torch.optim.Adadelta.html#torch.optim.Adadelta.add_param_group">(torch.optim.Adadelta method)</a>
</li>
        <li><a href="generated/torch.optim.Adagrad.html#torch.optim.Adagrad.add_param_group">(torch.optim.Adagrad method)</a>
</li>
        <li><a href="generated/torch.optim.Adam.html#torch.optim.Adam.add_param_group">(torch.optim.Adam method)</a>
</li>
        <li><a href="generated/torch.optim.Adamax.html#torch.optim.Adamax.add_param_group">(torch.optim.Adamax method)</a>
</li>
        <li><a href="generated/torch.optim.AdamW.html#torch.optim.AdamW.add_param_group">(torch.optim.AdamW method)</a>
</li>
        <li><a href="generated/torch.optim.ASGD.html#torch.optim.ASGD.add_param_group">(torch.optim.ASGD method)</a>
</li>
        <li><a href="generated/torch.optim.LBFGS.html#torch.optim.LBFGS.add_param_group">(torch.optim.LBFGS method)</a>
</li>
        <li><a href="generated/torch.optim.NAdam.html#torch.optim.NAdam.add_param_group">(torch.optim.NAdam method)</a>
</li>
        <li><a href="generated/torch.optim.Optimizer.add_param_group.html#torch.optim.Optimizer.add_param_group">(torch.optim.Optimizer method)</a>
</li>
        <li><a href="generated/torch.optim.RAdam.html#torch.optim.RAdam.add_param_group">(torch.optim.RAdam method)</a>
</li>
        <li><a href="generated/torch.optim.RMSprop.html#torch.optim.RMSprop.add_param_group">(torch.optim.RMSprop method)</a>
</li>
        <li><a href="generated/torch.optim.Rprop.html#torch.optim.Rprop.add_param_group">(torch.optim.Rprop method)</a>
</li>
        <li><a href="generated/torch.optim.SGD.html#torch.optim.SGD.add_param_group">(torch.optim.SGD method)</a>
</li>
        <li><a href="generated/torch.optim.SparseAdam.html#torch.optim.SparseAdam.add_param_group">(torch.optim.SparseAdam method)</a>
</li>
      </ul></li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_pr_curve">add_pr_curve() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.PruningContainer.html#torch.nn.utils.prune.PruningContainer.add_pruning_method">add_pruning_method() (torch.nn.utils.prune.PruningContainer method)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.add_quant_dequant">add_quant_dequant() (in module torch.quantization)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_scalar">add_scalar() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_scalars">add_scalars() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="fx.html#torch.fx.GraphModule.add_submodule">add_submodule() (torch.fx.GraphModule method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_text">add_text() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.add_video">add_video() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="generated/torch.addbmm.html#torch.addbmm">addbmm() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.addbmm.html#torch.Tensor.addbmm">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.addbmm_.html#torch.Tensor.addbmm_">addbmm_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.addcdiv.html#torch.addcdiv">addcdiv() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.addcdiv.html#torch.Tensor.addcdiv">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.addcdiv_.html#torch.Tensor.addcdiv_">addcdiv_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.addcmul.html#torch.addcmul">addcmul() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.addcmul.html#torch.Tensor.addcmul">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.addcmul_.html#torch.Tensor.addcmul_">addcmul_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.addmm.html#torch.addmm">addmm() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.sparse.addmm.html#torch.sparse.addmm">(in module torch.sparse)</a>
</li>
        <li><a href="generated/torch.Tensor.addmm.html#torch.Tensor.addmm">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.addmm_.html#torch.Tensor.addmm_">addmm_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.addmv.html#torch.addmv">addmv() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.addmv.html#torch.Tensor.addmv">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.addmv_.html#torch.Tensor.addmv_">addmv_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.addr.html#torch.addr">addr() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.addr.html#torch.Tensor.addr">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.addr_.html#torch.Tensor.addr_">addr_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.functional.affine_grid.html#torch.nn.functional.affine_grid">affine_grid() (in module torch.nn.functional)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.AffineTransform">AffineTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="named_tensor.html#torch.Tensor.align_as">align_as() (torch.Tensor method)</a>
</li>
      <li><a href="named_tensor.html#torch.Tensor.align_to">align_to() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.all.html#torch.all">all() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.all.html#torch.Tensor.all">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributed.html#torch.distributed.all_gather">all_gather() (in module torch.distributed)</a>
</li>
      <li><a href="distributed.html#torch.distributed.all_gather_multigpu">all_gather_multigpu() (in module torch.distributed)</a>
</li>
      <li><a href="distributed.html#torch.distributed.all_gather_object">all_gather_object() (in module torch.distributed)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.all_input_nodes">all_input_nodes() (torch.fx.Node property)</a>
</li>
      <li><a href="distributed.html#torch.distributed.all_reduce">all_reduce() (in module torch.distributed)</a>
</li>
      <li><a href="distributed.html#torch.distributed.all_reduce_multigpu">all_reduce_multigpu() (in module torch.distributed)</a>
</li>
      <li><a href="distributed.html#torch.distributed.all_to_all">all_to_all() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.allclose.html#torch.allclose">allclose() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.allclose.html#torch.Tensor.allclose">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="backends.html#torch.backends.cuda.matmul.allow_tf32">allow_tf32 (torch.backends.cuda.matmul attribute)</a>

      <ul>
        <li><a href="backends.html#torch.backends.cudnn.allow_tf32">(torch.backends.cudnn attribute)</a>
</li>
      </ul></li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.algorithms.ddp_comm_hooks.default_hooks.allreduce_hook">allreduce_hook() (in module torch.distributed.algorithms.ddp_comm_hooks.default_hooks)</a>
</li>
      <li><a href="generated/torch.nn.functional.alpha_dropout.html#torch.nn.functional.alpha_dropout">alpha_dropout() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.AlphaDropout.html#torch.nn.AlphaDropout">AlphaDropout (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.amax.html#torch.amax">amax() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.amax.html#torch.Tensor.amax">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.amin.html#torch.amin">amin() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.amin.html#torch.Tensor.amin">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.aminmax.html#torch.aminmax">aminmax() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.aminmax.html#torch.Tensor.aminmax">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.angle.html#torch.angle">angle() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.angle.html#torch.Tensor.angle">(torch.Tensor method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.jit.annotate.html#torch.jit.annotate">annotate() (in module torch.jit)</a>
</li>
      <li><a href="generated/torch.any.html#torch.any">any() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.any.html#torch.Tensor.any">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Node.append">append() (torch.fx.Node method)</a>

      <ul>
        <li><a href="generated/torch.nn.ModuleList.html#torch.nn.ModuleList.append">(torch.nn.ModuleList method)</a>
</li>
        <li><a href="generated/torch.nn.ParameterList.html#torch.nn.ParameterList.append">(torch.nn.ParameterList method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.apply">apply() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.apply">(torch.nn.Module method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.BasePruningMethod.html#torch.nn.utils.prune.BasePruningMethod.apply">(torch.nn.utils.prune.BasePruningMethod class method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.CustomFromMask.html#torch.nn.utils.prune.CustomFromMask.apply">(torch.nn.utils.prune.CustomFromMask class method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.Identity.html#torch.nn.utils.prune.Identity.apply">(torch.nn.utils.prune.Identity class method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.L1Unstructured.html#torch.nn.utils.prune.L1Unstructured.apply">(torch.nn.utils.prune.L1Unstructured class method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.LnStructured.html#torch.nn.utils.prune.LnStructured.apply">(torch.nn.utils.prune.LnStructured class method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.PruningContainer.html#torch.nn.utils.prune.PruningContainer.apply">(torch.nn.utils.prune.PruningContainer class method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.RandomStructured.html#torch.nn.utils.prune.RandomStructured.apply">(torch.nn.utils.prune.RandomStructured class method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.RandomUnstructured.html#torch.nn.utils.prune.RandomUnstructured.apply">(torch.nn.utils.prune.RandomUnstructured class method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.apply_.html#torch.Tensor.apply_">apply_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.BasePruningMethod.html#torch.nn.utils.prune.BasePruningMethod.apply_mask">apply_mask() (torch.nn.utils.prune.BasePruningMethod method)</a>

      <ul>
        <li><a href="generated/torch.nn.utils.prune.CustomFromMask.html#torch.nn.utils.prune.CustomFromMask.apply_mask">(torch.nn.utils.prune.CustomFromMask method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.Identity.html#torch.nn.utils.prune.Identity.apply_mask">(torch.nn.utils.prune.Identity method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.L1Unstructured.html#torch.nn.utils.prune.L1Unstructured.apply_mask">(torch.nn.utils.prune.L1Unstructured method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.LnStructured.html#torch.nn.utils.prune.LnStructured.apply_mask">(torch.nn.utils.prune.LnStructured method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.PruningContainer.html#torch.nn.utils.prune.PruningContainer.apply_mask">(torch.nn.utils.prune.PruningContainer method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.RandomStructured.html#torch.nn.utils.prune.RandomStructured.apply_mask">(torch.nn.utils.prune.RandomStructured method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.RandomUnstructured.html#torch.nn.utils.prune.RandomUnstructured.apply_mask">(torch.nn.utils.prune.RandomUnstructured method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.arange.html#torch.arange">arange() (in module torch)</a>
</li>
      <li><a href="generated/torch.arccos.html#torch.arccos">arccos() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.arccos.html#torch.Tensor.arccos">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.arccos_.html#torch.Tensor.arccos_">arccos_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.arccosh.html#torch.arccosh">arccosh() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.arccosh.html#torch.Tensor.arccosh">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.arccosh_.html#torch.Tensor.arccosh_">arccosh_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.arcsin.html#torch.arcsin">arcsin() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.arcsin.html#torch.Tensor.arcsin">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.arcsin_.html#torch.Tensor.arcsin_">arcsin_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.arcsinh.html#torch.arcsinh">arcsinh() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.arcsinh.html#torch.Tensor.arcsinh">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.arcsinh_.html#torch.Tensor.arcsinh_">arcsinh_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.arctan.html#torch.arctan">arctan() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.arctan.html#torch.Tensor.arctan">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.arctan_.html#torch.Tensor.arctan_">arctan_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.arctanh.html#torch.arctanh">arctanh() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.arctanh.html#torch.Tensor.arctanh">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.arctanh_.html#torch.Tensor.arctanh_">arctanh_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.are_deterministic_algorithms_enabled.html#torch.are_deterministic_algorithms_enabled">are_deterministic_algorithms_enabled() (in module torch)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.arg_constraints">arg_constraints (torch.distributions.bernoulli.Bernoulli attribute)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.beta.Beta.arg_constraints">(torch.distributions.beta.Beta attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.arg_constraints">(torch.distributions.binomial.Binomial attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.arg_constraints">(torch.distributions.categorical.Categorical attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.arg_constraints">(torch.distributions.cauchy.Cauchy attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.chi2.Chi2.arg_constraints">(torch.distributions.chi2.Chi2 attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.arg_constraints">(torch.distributions.continuous_bernoulli.ContinuousBernoulli attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet.arg_constraints">(torch.distributions.dirichlet.Dirichlet attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.arg_constraints">(torch.distributions.exponential.Exponential attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.fishersnedecor.FisherSnedecor.arg_constraints">(torch.distributions.fishersnedecor.FisherSnedecor attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gamma.Gamma.arg_constraints">(torch.distributions.gamma.Gamma attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.geometric.Geometric.arg_constraints">(torch.distributions.geometric.Geometric attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gumbel.Gumbel.arg_constraints">(torch.distributions.gumbel.Gumbel attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.arg_constraints">(torch.distributions.half_cauchy.HalfCauchy attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.arg_constraints">(torch.distributions.half_normal.HalfNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.independent.Independent.arg_constraints">(torch.distributions.independent.Independent attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.kumaraswamy.Kumaraswamy.arg_constraints">(torch.distributions.kumaraswamy.Kumaraswamy attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.arg_constraints">(torch.distributions.laplace.Laplace attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lkj_cholesky.LKJCholesky.arg_constraints">(torch.distributions.lkj_cholesky.LKJCholesky attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.log_normal.LogNormal.arg_constraints">(torch.distributions.log_normal.LogNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.arg_constraints">(torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.arg_constraints">(torch.distributions.mixture_same_family.MixtureSameFamily attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.arg_constraints">(torch.distributions.multinomial.Multinomial attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.arg_constraints">(torch.distributions.multivariate_normal.MultivariateNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.arg_constraints">(torch.distributions.negative_binomial.NegativeBinomial attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.arg_constraints">(torch.distributions.normal.Normal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.arg_constraints">(torch.distributions.one_hot_categorical.OneHotCategorical attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.pareto.Pareto.arg_constraints">(torch.distributions.pareto.Pareto attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.poisson.Poisson.arg_constraints">(torch.distributions.poisson.Poisson attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli.arg_constraints">(torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.RelaxedBernoulli.arg_constraints">(torch.distributions.relaxed_bernoulli.RelaxedBernoulli attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_categorical.RelaxedOneHotCategorical.arg_constraints">(torch.distributions.relaxed_categorical.RelaxedOneHotCategorical attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.studentT.StudentT.arg_constraints">(torch.distributions.studentT.StudentT attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.arg_constraints">(torch.distributions.transformed_distribution.TransformedDistribution attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.arg_constraints">(torch.distributions.uniform.Uniform attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.von_mises.VonMises.arg_constraints">(torch.distributions.von_mises.VonMises attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.weibull.Weibull.arg_constraints">(torch.distributions.weibull.Weibull attribute)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.distribution.Distribution.arg_constraints">arg_constraints() (torch.distributions.distribution.Distribution property)</a>
</li>
      <li><a href="generated/torch.argmax.html#torch.argmax">argmax() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.argmax.html#torch.Tensor.argmax">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.argmin.html#torch.argmin">argmin() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.argmin.html#torch.Tensor.argmin">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Node.args">args() (torch.fx.Node property)</a>
</li>
      <li><a href="generated/torch.argsort.html#torch.argsort">argsort() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.argsort.html#torch.Tensor.argsort">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.CallgrindStats.as_standardized">as_standardized() (torch.utils.benchmark.CallgrindStats method)</a>
</li>
      <li><a href="generated/torch.as_strided.html#torch.as_strided">as_strided() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.as_strided.html#torch.Tensor.as_strided">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.as_subclass.html#torch.Tensor.as_subclass">as_subclass() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.as_tensor.html#torch.as_tensor">as_tensor() (in module torch)</a>
</li>
      <li><a href="generated/torch.optim.ASGD.html#torch.optim.ASGD">ASGD (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.asin.html#torch.asin">asin() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.asin.html#torch.Tensor.asin">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.asin_.html#torch.Tensor.asin_">asin_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.asinh.html#torch.asinh">asinh() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.asinh.html#torch.Tensor.asinh">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.asinh_.html#torch.Tensor.asinh_">asinh_() (torch.Tensor method)</a>
</li>
      <li><a href="testing.html#torch.testing.assert_close">assert_close() (in module torch.testing)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.functions.async_execution">async_execution() (in module torch.distributed.rpc.functions)</a>
</li>
      <li><a href="generated/torch.atan.html#torch.atan">atan() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.atan.html#torch.Tensor.atan">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.atan2.html#torch.atan2">atan2() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.atan2.html#torch.Tensor.atan2">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.atan2_.html#torch.Tensor.atan2_">atan2_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.atan_.html#torch.Tensor.atan_">atan_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.atanh.html#torch.atanh">atanh() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.atanh.html#torch.Tensor.atanh">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.atanh_.html#torch.Tensor.atanh_">atanh_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.atleast_1d.html#torch.atleast_1d">atleast_1d() (in module torch)</a>
</li>
      <li><a href="generated/torch.atleast_2d.html#torch.atleast_2d">atleast_2d() (in module torch)</a>
</li>
      <li><a href="generated/torch.atleast_3d.html#torch.atleast_3d">atleast_3d() (in module torch)</a>
</li>
      <li><a href="generated/torch.jit.Attribute.html#torch.jit.Attribute">Attribute (class in torch.jit)</a>
</li>
      <li><a href="amp.html#torch.autocast">autocast (class in torch)</a>

      <ul>
        <li><a href="amp.html#torch.cuda.amp.autocast">(class in torch.cuda.amp)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.avg_pool1d.html#torch.nn.functional.avg_pool1d">avg_pool1d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.avg_pool2d.html#torch.nn.functional.avg_pool2d">avg_pool2d() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.avg_pool2d">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.avg_pool3d.html#torch.nn.functional.avg_pool3d">avg_pool3d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.AvgPool1d.html#torch.nn.AvgPool1d">AvgPool1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.AvgPool2d.html#torch.nn.AvgPool2d">AvgPool2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.AvgPool3d.html#torch.nn.AvgPool3d">AvgPool3d (class in torch.nn)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="B">B</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="distributed.html#torch.distributed.Backend">Backend (class in torch.distributed)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.BackendType">BackendType (class in torch.distributed.rpc)</a>
</li>
      <li><a href="generated/torch.autograd.backward.html#torch.autograd.backward">backward() (in module torch.autograd)</a>

      <ul>
        <li><a href="rpc.html#torch.distributed.autograd.backward">(in module torch.distributed.autograd)</a>
</li>
        <li><a href="generated/torch.autograd.Function.backward.html#torch.autograd.Function.backward">(torch.autograd.Function static method)</a>
</li>
        <li><a href="rpc.html#torch.distributed.rpc.RRef.backward">(torch.distributed.rpc.RRef method)</a>
</li>
        <li><a href="generated/torch.Tensor.backward.html#torch.Tensor.backward">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.baddbmm.html#torch.baddbmm">baddbmm() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.baddbmm.html#torch.Tensor.baddbmm">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.baddbmm_.html#torch.Tensor.baddbmm_">baddbmm_() (torch.Tensor method)</a>
</li>
      <li><a href="distributed.html#torch.distributed.barrier">barrier() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.bartlett_window.html#torch.bartlett_window">bartlett_window() (in module torch)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.BasePruningMethod.html#torch.nn.utils.prune.BasePruningMethod">BasePruningMethod (class in torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.nn.functional.batch_norm.html#torch.nn.functional.batch_norm">batch_norm() (in module torch.nn.functional)</a>
</li>
      <li><a href="distributions.html#torch.distributions.distribution.Distribution.batch_shape">batch_shape() (torch.distributions.distribution.Distribution property)</a>
</li>
      <li><a href="generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.batch_sizes">batch_sizes (torch.nn.utils.rnn.PackedSequence attribute)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.algorithms.ddp_comm_hooks.powerSGD_hook.batched_powerSGD_hook">batched_powerSGD_hook() (in module torch.distributed.algorithms.ddp_comm_hooks.powerSGD_hook)</a>
</li>
      <li><a href="generated/torch.nn.BatchNorm1d.html#torch.nn.BatchNorm1d">BatchNorm1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.BatchNorm2d.html#torch.nn.BatchNorm2d">BatchNorm2d (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.BatchNorm2d">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.BatchNorm3d.html#torch.nn.BatchNorm3d">BatchNorm3d (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.BatchNorm3d">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="data.html#torch.utils.data.BatchSampler">BatchSampler (class in torch.utils.data)</a>
</li>
      <li><a href="generated/torch.nn.BCELoss.html#torch.nn.BCELoss">BCELoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.BCEWithLogitsLoss.html#torch.nn.BCEWithLogitsLoss">BCEWithLogitsLoss (class in torch.nn)</a>
</li>
      <li><a href="backends.html#torch.backends.cudnn.benchmark">benchmark (torch.backends.cudnn attribute)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli">Bernoulli (class in torch.distributions.bernoulli)</a>
</li>
      <li><a href="generated/torch.bernoulli.html#torch.bernoulli">bernoulli() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.bernoulli.html#torch.Tensor.bernoulli">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.bernoulli_.html#torch.Tensor.bernoulli_">bernoulli_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.beta.Beta">Beta (class in torch.distributions.beta)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.algorithms.ddp_comm_hooks.default_hooks.bf16_compress_hook">bf16_compress_hook() (in module torch.distributed.algorithms.ddp_comm_hooks.default_hooks)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.algorithms.ddp_comm_hooks.default_hooks.bf16_compress_wrapper">bf16_compress_wrapper() (in module torch.distributed.algorithms.ddp_comm_hooks.default_hooks)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.bfloat16">bfloat16() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.bfloat16">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.bfloat16">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.bfloat16">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.bfloat16">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.bfloat16">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.bfloat16">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.bfloat16">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.bfloat16">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.bfloat16">(torch.IntStorage method)</a>
</li>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.bfloat16">(torch.jit.ScriptModule method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.bfloat16">(torch.LongStorage method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.bfloat16">(torch.nn.Module method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.bfloat16">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.bfloat16">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.bfloat16">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.bfloat16">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.bfloat16">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.bfloat16.html#torch.Tensor.bfloat16">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.BFloat16Storage">BFloat16Storage (class in torch)</a>
</li>
      <li><a href="generated/torch.nn.Bilinear.html#torch.nn.Bilinear">Bilinear (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.bilinear.html#torch.nn.functional.bilinear">bilinear() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.binary_cross_entropy.html#torch.nn.functional.binary_cross_entropy">binary_cross_entropy() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.binary_cross_entropy_with_logits.html#torch.nn.functional.binary_cross_entropy_with_logits">binary_cross_entropy_with_logits() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.bincount.html#torch.bincount">bincount() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.bincount.html#torch.Tensor.bincount">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.binomial.Binomial">Binomial (class in torch.distributions.binomial)</a>
</li>
      <li><a href="generated/torch.bitwise_and.html#torch.bitwise_and">bitwise_and() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.bitwise_and.html#torch.Tensor.bitwise_and">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.bitwise_and_.html#torch.Tensor.bitwise_and_">bitwise_and_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.bitwise_left_shift.html#torch.bitwise_left_shift">bitwise_left_shift() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.bitwise_left_shift.html#torch.Tensor.bitwise_left_shift">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.bitwise_left_shift_.html#torch.Tensor.bitwise_left_shift_">bitwise_left_shift_() (torch.Tensor method)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.bitwise_not.html#torch.bitwise_not">bitwise_not() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.bitwise_not.html#torch.Tensor.bitwise_not">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.bitwise_not_.html#torch.Tensor.bitwise_not_">bitwise_not_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.bitwise_or.html#torch.bitwise_or">bitwise_or() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.bitwise_or.html#torch.Tensor.bitwise_or">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.bitwise_or_.html#torch.Tensor.bitwise_or_">bitwise_or_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.bitwise_right_shift.html#torch.bitwise_right_shift">bitwise_right_shift() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.bitwise_right_shift.html#torch.Tensor.bitwise_right_shift">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.bitwise_right_shift_.html#torch.Tensor.bitwise_right_shift_">bitwise_right_shift_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.bitwise_xor.html#torch.bitwise_xor">bitwise_xor() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.bitwise_xor.html#torch.Tensor.bitwise_xor">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.bitwise_xor_.html#torch.Tensor.bitwise_xor_">bitwise_xor_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.blackman_window.html#torch.blackman_window">blackman_window() (in module torch)</a>
</li>
      <li><a href="generated/torch.block_diag.html#torch.block_diag">block_diag() (in module torch)</a>
</li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.Timer.blocked_autorange">blocked_autorange() (torch.utils.benchmark.Timer method)</a>
</li>
      <li><a href="generated/torch.bmm.html#torch.bmm">bmm() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.bmm.html#torch.Tensor.bmm">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.BFloat16Storage.bool">bool() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.bool">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.bool">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.bool">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.bool">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.bool">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.bool">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.bool">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.bool">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.bool">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.bool">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.bool">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.bool">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.bool">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.bool">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.bool">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.bool.html#torch.Tensor.bool">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.BoolStorage">BoolStorage (class in torch)</a>
</li>
      <li><a href="generated/torch.cuda.comm.broadcast.html#torch.cuda.comm.broadcast">broadcast() (in module torch.cuda.comm)</a>

      <ul>
        <li><a href="distributed.html#torch.distributed.broadcast">(in module torch.distributed)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.comm.broadcast_coalesced.html#torch.cuda.comm.broadcast_coalesced">broadcast_coalesced() (in module torch.cuda.comm)</a>
</li>
      <li><a href="distributed.html#torch.distributed.broadcast_multigpu">broadcast_multigpu() (in module torch.distributed)</a>
</li>
      <li><a href="distributed.html#torch.distributed.broadcast_object_list">broadcast_object_list() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.broadcast_shapes.html#torch.broadcast_shapes">broadcast_shapes() (in module torch)</a>
</li>
      <li><a href="generated/torch.broadcast_tensors.html#torch.broadcast_tensors">broadcast_tensors() (in module torch)</a>
</li>
      <li><a href="generated/torch.broadcast_to.html#torch.broadcast_to">broadcast_to() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.broadcast_to.html#torch.Tensor.broadcast_to">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.bucketize.html#torch.bucketize">bucketize() (in module torch)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.GradBucket.buffer">buffer() (in module torch.distributed.GradBucket)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.buffers">buffers() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.buffers">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="cpp_extension.html#torch.utils.cpp_extension.BuildExtension">BuildExtension() (in module torch.utils.cpp_extension)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.byte">byte() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.byte">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.byte">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.byte">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.byte">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.byte">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.byte">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.byte">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.byte">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.byte">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.byte">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.byte">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.byte">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.byte">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.byte">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.byte">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.byte.html#torch.Tensor.byte">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.ByteStorage">ByteStorage (class in torch)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="C">C</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.c10d_rendezvous_backend.C10dRendezvousBackend">C10dRendezvousBackend (class in torch.distributed.elastic.rendezvous.c10d_rendezvous_backend)</a>
</li>
      <li><a href="generated/torch.nn.utils.parametrize.cached.html#torch.nn.utils.parametrize.cached">cached() (in module torch.nn.utils.parametrize)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.calculate_gain">calculate_gain() (in module torch.nn.init)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.call_function">call_function() (torch.fx.Graph method)</a>

      <ul>
        <li><a href="fx.html#torch.fx.Interpreter.call_function">(torch.fx.Interpreter method)</a>
</li>
        <li><a href="fx.html#torch.fx.Transformer.call_function">(torch.fx.Transformer method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Graph.call_method">call_method() (torch.fx.Graph method)</a>

      <ul>
        <li><a href="fx.html#torch.fx.Interpreter.call_method">(torch.fx.Interpreter method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Graph.call_module">call_module() (torch.fx.Graph method)</a>

      <ul>
        <li><a href="fx.html#torch.fx.Interpreter.call_module">(torch.fx.Interpreter method)</a>
</li>
        <li><a href="fx.html#torch.fx.Tracer.call_module">(torch.fx.Tracer method)</a>
</li>
        <li><a href="fx.html#torch.fx.Transformer.call_module">(torch.fx.Transformer method)</a>
</li>
      </ul></li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.CallgrindStats">CallgrindStats (class in torch.utils.benchmark)</a>
</li>
      <li><a href="generated/torch.can_cast.html#torch.can_cast">can_cast() (in module torch)</a>
</li>
      <li><a href="generated/torch.cuda.can_device_access_peer.html#torch.cuda.can_device_access_peer">can_device_access_peer() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.CUDAGraph.html#torch.cuda.CUDAGraph.capture_begin">capture_begin() (torch.cuda.CUDAGraph method)</a>
</li>
      <li><a href="generated/torch.cuda.CUDAGraph.html#torch.cuda.CUDAGraph.capture_end">capture_end() (torch.cuda.CUDAGraph method)</a>
</li>
      <li><a href="generated/torch.cartesian_prod.html#torch.cartesian_prod">cartesian_prod() (in module torch)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraints.cat">cat (in module torch.distributions.constraints)</a>
</li>
      <li><a href="generated/torch.cat.html#torch.cat">cat() (in module torch)</a>
</li>
      <li><a href="distributions.html#torch.distributions.categorical.Categorical">Categorical (class in torch.distributions.categorical)</a>
</li>
      <li><a href="distributions.html#torch.distributions.cauchy.Cauchy">Cauchy (class in torch.distributions.cauchy)</a>
</li>
      <li><a href="generated/torch.Tensor.cauchy_.html#torch.Tensor.cauchy_">cauchy_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.cdf">cdf() (torch.distributions.cauchy.Cauchy method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.cdf">(torch.distributions.continuous_bernoulli.ContinuousBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.cdf">(torch.distributions.distribution.Distribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.cdf">(torch.distributions.exponential.Exponential method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.cdf">(torch.distributions.half_cauchy.HalfCauchy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.cdf">(torch.distributions.half_normal.HalfNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.cdf">(torch.distributions.laplace.Laplace method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.cdf">(torch.distributions.mixture_same_family.MixtureSameFamily method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.cdf">(torch.distributions.normal.Normal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.cdf">(torch.distributions.transformed_distribution.TransformedDistribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.cdf">(torch.distributions.uniform.Uniform method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cdist.html#torch.cdist">cdist() (in module torch)</a>
</li>
      <li><a href="generated/torch.ceil.html#torch.ceil">ceil() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.ceil.html#torch.Tensor.ceil">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.ceil_.html#torch.Tensor.ceil_">ceil_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.CELU.html#torch.nn.CELU">CELU (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.celu.html#torch.nn.functional.celu">celu() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.chain_matmul.html#torch.chain_matmul">chain_matmul() (in module torch)</a>
</li>
      <li><a href="data.html#torch.utils.data.ChainDataset">ChainDataset (class in torch.utils.data)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.ChainedScheduler.html#torch.optim.lr_scheduler.ChainedScheduler">ChainedScheduler (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="generated/torch.nn.ChannelShuffle.html#torch.nn.ChannelShuffle">ChannelShuffle (class in torch.nn)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.char">char() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.char">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.char">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.char">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.char">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.char">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.char">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.char">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.char">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.char">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.char">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.char">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.char">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.char">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.char">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.char">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.char.html#torch.Tensor.char">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.CharStorage">CharStorage (class in torch)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_store.EtcdStore.check">check() (torch.distributed.elastic.rendezvous.etcd_store.EtcdStore method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.constraints.Constraint.check">(torch.distributions.constraints.Constraint method)</a>
</li>
      </ul></li>
      <li><a href="cpp_extension.html#torch.utils.cpp_extension.check_compiler_abi_compatibility">check_compiler_abi_compatibility() (in module torch.utils.cpp_extension)</a>
</li>
      <li><a href="checkpoint.html#torch.utils.checkpoint.checkpoint">checkpoint() (in module torch.utils.checkpoint)</a>
</li>
      <li><a href="checkpoint.html#torch.utils.checkpoint.checkpoint_sequential">checkpoint_sequential() (in module torch.utils.checkpoint)</a>
</li>
      <li><a href="distributions.html#torch.distributions.chi2.Chi2">Chi2 (class in torch.distributions.chi2)</a>
</li>
      <li><a href="elastic/errors.html#torch.distributed.elastic.multiprocessing.errors.ChildFailedError">ChildFailedError (class in torch.distributed.elastic.multiprocessing.errors)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.children">children() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.children">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cholesky.html#torch.cholesky">cholesky() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.cholesky.html#torch.linalg.cholesky">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.cholesky.html#torch.Tensor.cholesky">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.linalg.cholesky_ex.html#torch.linalg.cholesky_ex">cholesky_ex() (in module torch.linalg)</a>
</li>
      <li><a href="generated/torch.cholesky_inverse.html#torch.cholesky_inverse">cholesky_inverse() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.cholesky_inverse.html#torch.Tensor.cholesky_inverse">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cholesky_solve.html#torch.cholesky_solve">cholesky_solve() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.cholesky_solve.html#torch.Tensor.cholesky_solve">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.chunk.html#torch.chunk">chunk() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.chunk.html#torch.Tensor.chunk">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.clamp.html#torch.clamp">clamp() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.clamp.html#torch.Tensor.clamp">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.clamp_.html#torch.Tensor.clamp_">clamp_() (torch.Tensor method)</a>
</li>
      <li><a href="backends.html#clear">clear()</a>

      <ul>
        <li><a href="generated/torch.nn.ModuleDict.html#torch.nn.ModuleDict.clear">(torch.nn.ModuleDict method)</a>
</li>
        <li><a href="generated/torch.nn.ParameterDict.html#torch.nn.ParameterDict.clear">(torch.nn.ParameterDict method)</a>
</li>
      </ul></li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.TimerServer.clear_timers">clear_timers() (torch.distributed.elastic.timer.TimerServer method)</a>
</li>
      <li><a href="generated/torch.clip.html#torch.clip">clip() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.clip.html#torch.Tensor.clip">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.clip_.html#torch.Tensor.clip_">clip_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.utils.clip_grad_norm_.html#torch.nn.utils.clip_grad_norm_">clip_grad_norm_() (in module torch.nn.utils)</a>
</li>
      <li><a href="generated/torch.nn.utils.clip_grad_value_.html#torch.nn.utils.clip_grad_value_">clip_grad_value_() (in module torch.nn.utils)</a>
</li>
      <li><a href="generated/torch.clone.html#torch.clone">clone() (in module torch)</a>

      <ul>
        <li><a href="storage.html#torch.BFloat16Storage.clone">(torch.BFloat16Storage method)</a>
</li>
        <li><a href="storage.html#torch.BoolStorage.clone">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.clone">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.clone">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.clone">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.clone">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.clone">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.clone">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.clone">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.clone">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.clone">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.clone">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.clone">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.clone">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.clone">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.clone">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.clone.html#torch.Tensor.clone">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousTimeout.close">close() (torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousTimeout property)</a>

      <ul>
        <li><a href="package.html#torch.package.PackageExporter.close">(torch.package.PackageExporter method)</a>
</li>
        <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.close">(torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.LazyBatchNorm1d.html#torch.nn.LazyBatchNorm1d.cls_to_become">cls_to_become (torch.nn.LazyBatchNorm1d attribute)</a>

      <ul>
        <li><a href="generated/torch.nn.LazyBatchNorm2d.html#torch.nn.LazyBatchNorm2d.cls_to_become">(torch.nn.LazyBatchNorm2d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyBatchNorm3d.html#torch.nn.LazyBatchNorm3d.cls_to_become">(torch.nn.LazyBatchNorm3d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyConv1d.html#torch.nn.LazyConv1d.cls_to_become">(torch.nn.LazyConv1d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyConv2d.html#torch.nn.LazyConv2d.cls_to_become">(torch.nn.LazyConv2d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyConv3d.html#torch.nn.LazyConv3d.cls_to_become">(torch.nn.LazyConv3d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyConvTranspose1d.html#torch.nn.LazyConvTranspose1d.cls_to_become">(torch.nn.LazyConvTranspose1d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyConvTranspose2d.html#torch.nn.LazyConvTranspose2d.cls_to_become">(torch.nn.LazyConvTranspose2d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyConvTranspose3d.html#torch.nn.LazyConvTranspose3d.cls_to_become">(torch.nn.LazyConvTranspose3d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyInstanceNorm1d.html#torch.nn.LazyInstanceNorm1d.cls_to_become">(torch.nn.LazyInstanceNorm1d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyInstanceNorm2d.html#torch.nn.LazyInstanceNorm2d.cls_to_become">(torch.nn.LazyInstanceNorm2d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyInstanceNorm3d.html#torch.nn.LazyInstanceNorm3d.cls_to_become">(torch.nn.LazyInstanceNorm3d attribute)</a>
</li>
        <li><a href="generated/torch.nn.LazyLinear.html#torch.nn.LazyLinear.cls_to_become">(torch.nn.LazyLinear attribute)</a>
</li>
        <li><a href="generated/torch.nn.parameter.UninitializedParameter.html#torch.nn.parameter.UninitializedParameter.cls_to_become">(torch.nn.parameter.UninitializedParameter attribute)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.coalesce.html#torch.Tensor.coalesce">coalesce() (torch.Tensor method)</a>
</li>
      <li><a href="fx.html#torch.fx.GraphModule.code">code() (torch.fx.GraphModule property)</a>

      <ul>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.code">(torch.jit.ScriptModule property)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.code_with_constants">code_with_constants() (torch.jit.ScriptModule property)</a>
</li>
      <li><a href="futures.html#torch.futures.collect_all">collect_all() (in module torch.futures)</a>
</li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.Timer.collect_callgrind">collect_callgrind() (torch.utils.benchmark.Timer method)</a>
</li>
      <li><a href="generated/torch.column_stack.html#torch.column_stack">column_stack() (in module torch)</a>
</li>
      <li><a href="generated/torch.combinations.html#torch.combinations">combinations() (in module torch)</a>
</li>
      <li><a href="distributed.html#torch.distributed.Store.compare_set">compare_set() (in module torch.distributed.Store)</a>
</li>
      <li><a href="generated/torch.compiled_with_cxx11_abi.html#torch.compiled_with_cxx11_abi">compiled_with_cxx11_abi() (in module torch)</a>
</li>
      <li><a href="generated/torch.complex.html#torch.complex">complex() (in module torch)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.complex_double">complex_double() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.complex_double">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.complex_double">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.complex_double">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.complex_double">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.complex_double">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.complex_double">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.complex_double">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.complex_double">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.complex_double">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.complex_double">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.complex_double">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.complex_double">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.complex_double">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.complex_double">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.complex_double">(torch.ShortStorage method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.BFloat16Storage.complex_float">complex_float() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.complex_float">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.complex_float">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.complex_float">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.complex_float">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.complex_float">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.complex_float">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.complex_float">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.complex_float">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.complex_float">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.complex_float">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.complex_float">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.complex_float">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.complex_float">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.complex_float">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.complex_float">(torch.ShortStorage method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.ComplexDoubleStorage">ComplexDoubleStorage (class in torch)</a>
</li>
      <li><a href="storage.html#torch.ComplexFloatStorage">ComplexFloatStorage (class in torch)</a>
</li>
      <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.component_distribution">component_distribution() (torch.distributions.mixture_same_family.MixtureSameFamily property)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.ComposeTransform">ComposeTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.BasePruningMethod.html#torch.nn.utils.prune.BasePruningMethod.compute_mask">compute_mask() (torch.nn.utils.prune.BasePruningMethod method)</a>

      <ul>
        <li><a href="generated/torch.nn.utils.prune.LnStructured.html#torch.nn.utils.prune.LnStructured.compute_mask">(torch.nn.utils.prune.LnStructured method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.PruningContainer.html#torch.nn.utils.prune.PruningContainer.compute_mask">(torch.nn.utils.prune.PruningContainer method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.RandomStructured.html#torch.nn.utils.prune.RandomStructured.compute_mask">(torch.nn.utils.prune.RandomStructured method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.concat.html#torch.concat">concat() (in module torch)</a>
</li>
      <li><a href="data.html#torch.utils.data.ConcatDataset">ConcatDataset (class in torch.utils.data)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="distributions.html#torch.distributions.beta.Beta.concentration0">concentration0() (torch.distributions.beta.Beta property)</a>
</li>
      <li><a href="distributions.html#torch.distributions.beta.Beta.concentration1">concentration1() (torch.distributions.beta.Beta property)</a>
</li>
      <li><a href="generated/torch.linalg.cond.html#torch.linalg.cond">cond() (in module torch.linalg)</a>
</li>
      <li><a href="elastic/metrics.html#torch.distributed.elastic.metrics.configure">configure() (in module torch.distributed.elastic.metrics)</a>

      <ul>
        <li><a href="elastic/timer.html#torch.distributed.elastic.timer.configure">(in module torch.distributed.elastic.timer)</a>
</li>
      </ul></li>
      <li><a href="rpc.html#torch.distributed.rpc.RRef.confirmed_by_owner">confirmed_by_owner() (torch.distributed.rpc.RRef method)</a>
</li>
      <li><a href="generated/torch.conj.html#torch.conj">conj() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.conj.html#torch.Tensor.conj">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.conj_physical.html#torch.conj_physical">conj_physical() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.conj_physical.html#torch.Tensor.conj_physical">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.conj_physical_.html#torch.Tensor.conj_physical_">conj_physical_() (torch.Tensor method)</a>
</li>
      <li><a href="elastic/metrics.html#torch.distributed.elastic.metrics.api.ConsoleMetricHandler">ConsoleMetricHandler (class in torch.distributed.elastic.metrics.api)</a>
</li>
      <li><a href="distributed.optim.html#torch.distributed.optim.ZeroRedundancyOptimizer.consolidate_state_dict">consolidate_state_dict() (torch.distributed.optim.ZeroRedundancyOptimizer method)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.constant_">constant_() (in module torch.nn.init)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.ConstantLR.html#torch.optim.lr_scheduler.ConstantLR">ConstantLR (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="generated/torch.nn.ConstantPad1d.html#torch.nn.ConstantPad1d">ConstantPad1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ConstantPad2d.html#torch.nn.ConstantPad2d">ConstantPad2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ConstantPad3d.html#torch.nn.ConstantPad3d">ConstantPad3d (class in torch.nn)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraints.Constraint">Constraint (class in torch.distributions.constraints)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraint_registry.ConstraintRegistry">ConstraintRegistry (class in torch.distributions.constraint_registry)</a>
</li>
      <li><a href="rpc.html#torch.distributed.autograd.context">context (class in torch.distributed.autograd)</a>
</li>
      <li><a href="generated/torch.Tensor.contiguous.html#torch.Tensor.contiguous">contiguous() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli">ContinuousBernoulli (class in torch.distributions.continuous_bernoulli)</a>
</li>
      <li><a href="generated/torch.nn.Conv1d.html#torch.nn.Conv1d">Conv1d (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Conv1d">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.conv1d.html#torch.nn.functional.conv1d">conv1d() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.conv1d">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.Conv2d.html#torch.nn.Conv2d">Conv2d (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.qat.html#torch.nn.qat.Conv2d">(class in torch.nn.qat)</a>
</li>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Conv2d">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.conv2d.html#torch.nn.functional.conv2d">conv2d() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.conv2d">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.Conv3d.html#torch.nn.Conv3d">Conv3d (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Conv3d">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.conv3d.html#torch.nn.functional.conv3d">conv3d() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.conv3d">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.conv_transpose1d.html#torch.nn.functional.conv_transpose1d">conv_transpose1d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.conv_transpose2d.html#torch.nn.functional.conv_transpose2d">conv_transpose2d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.conv_transpose3d.html#torch.nn.functional.conv_transpose3d">conv_transpose3d() (in module torch.nn.functional)</a>
</li>
      <li><a href="torch.nn.intrinsic.html#torch.nn.intrinsic.ConvBn1d">ConvBn1d (class in torch.nn.intrinsic)</a>
</li>
      <li><a href="torch.nn.intrinsic.html#torch.nn.intrinsic.ConvBn2d">ConvBn2d (class in torch.nn.intrinsic)</a>

      <ul>
        <li><a href="torch.nn.intrinsic.qat.html#torch.nn.intrinsic.qat.ConvBn2d">(class in torch.nn.intrinsic.qat)</a>
</li>
      </ul></li>
      <li><a href="torch.nn.intrinsic.html#torch.nn.intrinsic.ConvBn3d">ConvBn3d (class in torch.nn.intrinsic)</a>

      <ul>
        <li><a href="torch.nn.intrinsic.qat.html#torch.nn.intrinsic.qat.ConvBn3d">(class in torch.nn.intrinsic.qat)</a>
</li>
      </ul></li>
      <li><a href="torch.nn.intrinsic.html#torch.nn.intrinsic.ConvBnReLU1d">ConvBnReLU1d (class in torch.nn.intrinsic)</a>
</li>
      <li><a href="torch.nn.intrinsic.html#torch.nn.intrinsic.ConvBnReLU2d">ConvBnReLU2d (class in torch.nn.intrinsic)</a>

      <ul>
        <li><a href="torch.nn.intrinsic.qat.html#torch.nn.intrinsic.qat.ConvBnReLU2d">(class in torch.nn.intrinsic.qat)</a>
</li>
      </ul></li>
      <li><a href="torch.nn.intrinsic.html#torch.nn.intrinsic.ConvBnReLU3d">ConvBnReLU3d (class in torch.nn.intrinsic)</a>

      <ul>
        <li><a href="torch.nn.intrinsic.qat.html#torch.nn.intrinsic.qat.ConvBnReLU3d">(class in torch.nn.intrinsic.qat)</a>
</li>
      </ul></li>
      <li><a href="torch.quantization.html#torch.quantization.convert">convert() (in module torch.quantization)</a>
</li>
      <li><a href="generated/torch.nn.SyncBatchNorm.html#torch.nn.SyncBatchNorm.convert_sync_batchnorm">convert_sync_batchnorm() (torch.nn.SyncBatchNorm class method)</a>
</li>
      <li><a href="torch.nn.intrinsic.html#torch.nn.intrinsic.ConvReLU1d">ConvReLU1d (class in torch.nn.intrinsic)</a>
</li>
      <li><a href="torch.nn.intrinsic.html#torch.nn.intrinsic.ConvReLU2d">ConvReLU2d (class in torch.nn.intrinsic)</a>

      <ul>
        <li><a href="torch.nn.intrinsic.qat.html#torch.nn.intrinsic.qat.ConvReLU2d">(class in torch.nn.intrinsic.qat)</a>
</li>
        <li><a href="torch.nn.intrinsic.quantized.html#torch.nn.intrinsic.quantized.ConvReLU2d">(class in torch.nn.intrinsic.quantized)</a>
</li>
      </ul></li>
      <li><a href="torch.nn.intrinsic.html#torch.nn.intrinsic.ConvReLU3d">ConvReLU3d (class in torch.nn.intrinsic)</a>

      <ul>
        <li><a href="torch.nn.intrinsic.qat.html#torch.nn.intrinsic.qat.ConvReLU3d">(class in torch.nn.intrinsic.qat)</a>
</li>
        <li><a href="torch.nn.intrinsic.quantized.html#torch.nn.intrinsic.quantized.ConvReLU3d">(class in torch.nn.intrinsic.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.ConvTranspose1d.html#torch.nn.ConvTranspose1d">ConvTranspose1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ConvTranspose2d.html#torch.nn.ConvTranspose2d">ConvTranspose2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ConvTranspose3d.html#torch.nn.ConvTranspose3d">ConvTranspose3d (class in torch.nn)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.copy_">copy_() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.copy_">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.copy_">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.copy_">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.copy_">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.copy_">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.copy_">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.copy_">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.copy_">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.copy_">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.copy_">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.copy_">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.copy_">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.copy_">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.copy_">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.copy_">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.copy_.html#torch.Tensor.copy_">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.copysign.html#torch.copysign">copysign() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.copysign.html#torch.Tensor.copysign">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.copysign_.html#torch.Tensor.copysign_">copysign_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.CorrCholeskyTransform">CorrCholeskyTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="generated/torch.corrcoef.html#torch.corrcoef">corrcoef() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.corrcoef.html#torch.Tensor.corrcoef">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cos.html#torch.cos">cos() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.cos.html#torch.Tensor.cos">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.cos_.html#torch.Tensor.cos_">cos_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.cosh.html#torch.cosh">cosh() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.cosh.html#torch.Tensor.cosh">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.cosh_.html#torch.Tensor.cosh_">cosh_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.functional.cosine_embedding_loss.html#torch.nn.functional.cosine_embedding_loss">cosine_embedding_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.cosine_similarity.html#torch.nn.functional.cosine_similarity">cosine_similarity() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingLR.html#torch.optim.lr_scheduler.CosineAnnealingLR">CosineAnnealingLR (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.html#torch.optim.lr_scheduler.CosineAnnealingWarmRestarts">CosineAnnealingWarmRestarts (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="generated/torch.nn.CosineEmbeddingLoss.html#torch.nn.CosineEmbeddingLoss">CosineEmbeddingLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.CosineSimilarity.html#torch.nn.CosineSimilarity">CosineSimilarity (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.jit.Attribute.html#torch.jit.Attribute.count">count() (torch.jit.Attribute method)</a>

      <ul>
        <li><a href="generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.count">(torch.nn.utils.rnn.PackedSequence method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.count_nonzero.html#torch.count_nonzero">count_nonzero() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.count_nonzero.html#torch.Tensor.count_nonzero">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.CallgrindStats.counts">counts() (torch.utils.benchmark.CallgrindStats method)</a>
</li>
      <li><a href="generated/torch.cov.html#torch.cov">cov() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.cov.html#torch.Tensor.cov">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.covariance_matrix">covariance_matrix() (torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.covariance_matrix">(torch.distributions.multivariate_normal.MultivariateNormal property)</a>
</li>
      </ul></li>
      <li><a href="cpp_extension.html#torch.utils.cpp_extension.CppExtension">CppExtension() (in module torch.utils.cpp_extension)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.cpu">cpu() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.cpu">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.cpu">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.cpu">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.cpu">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.cpu">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.cpu">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.cpu">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.cpu">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.cpu">(torch.IntStorage method)</a>
</li>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.cpu">(torch.jit.ScriptModule method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.cpu">(torch.LongStorage method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.cpu">(torch.nn.Module method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.cpu">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.cpu">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.cpu">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.cpu">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.cpu">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.cpu.html#torch.Tensor.cpu">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Tracer.create_arg">create_arg() (torch.fx.Tracer method)</a>
</li>
      <li><a href="fx.html#torch.fx.Tracer.create_args_for_root">create_args_for_root() (torch.fx.Tracer method)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.c10d_rendezvous_backend.create_backend">create_backend() (in module torch.distributed.elastic.rendezvous.c10d_rendezvous_backend)</a>

      <ul>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_rendezvous_backend.create_backend">(in module torch.distributed.elastic.rendezvous.etcd_rendezvous_backend)</a>
</li>
      </ul></li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.create_handler">create_handler() (in module torch.distributed.elastic.rendezvous.dynamic_rendezvous)</a>

      <ul>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandlerRegistry.create_handler">(torch.distributed.elastic.rendezvous.RendezvousHandlerRegistry method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Graph.create_node">create_node() (torch.fx.Graph method)</a>

      <ul>
        <li><a href="fx.html#torch.fx.Tracer.create_node">(torch.fx.Tracer method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Tracer.create_proxy">create_proxy() (torch.fx.Tracer method)</a>
</li>
      <li><a href="generated/torch.cross.html#torch.cross">cross() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.cross.html#torch.Tensor.cross">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.cross_entropy.html#torch.nn.functional.cross_entropy">cross_entropy() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.CrossEntropyLoss.html#torch.nn.CrossEntropyLoss">CrossEntropyLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.ctc_loss.html#torch.nn.functional.ctc_loss">ctc_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.CTCLoss.html#torch.nn.CTCLoss">CTCLoss (class in torch.nn)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.cuda">cuda() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.cuda">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.cuda">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.cuda">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.cuda">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.cuda">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.cuda">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.cuda">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.cuda">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.cuda">(torch.IntStorage method)</a>
</li>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.cuda">(torch.jit.ScriptModule method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.cuda">(torch.LongStorage method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.cuda">(torch.nn.Module method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.cuda">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.cuda">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.cuda">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.cuda">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.cuda">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.cuda.html#torch.Tensor.cuda">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="cpp_extension.html#torch.utils.cpp_extension.CUDAExtension">CUDAExtension() (in module torch.utils.cpp_extension)</a>
</li>
      <li><a href="generated/torch.cuda.CUDAGraph.html#torch.cuda.CUDAGraph">CUDAGraph (class in torch.cuda)</a>
</li>
      <li><a href="backends.html#torch.backends.cuda.cufft_plan_cache">cufft_plan_cache (torch.backends.cuda attribute)</a>
</li>
      <li><a href="generated/torch.cummax.html#torch.cummax">cummax() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.cummax.html#torch.Tensor.cummax">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cummin.html#torch.cummin">cummin() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.cummin.html#torch.Tensor.cummin">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cumprod.html#torch.cumprod">cumprod() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.cumprod.html#torch.Tensor.cumprod">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.cumprod_.html#torch.Tensor.cumprod_">cumprod_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.cumsum.html#torch.cumsum">cumsum() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.cumsum.html#torch.Tensor.cumsum">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.cumsum_.html#torch.Tensor.cumsum_">cumsum_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.cumulative_trapezoid.html#torch.cumulative_trapezoid">cumulative_trapezoid() (in module torch)</a>
</li>
      <li><a href="generated/torch.cuda.current_blas_handle.html#torch.cuda.current_blas_handle">current_blas_handle() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.current_device.html#torch.cuda.current_device">current_device() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.current_stream.html#torch.cuda.current_stream">current_stream() (in module torch.cuda)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.custom_bwd">custom_bwd() (in module torch.cuda.amp)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.custom_from_mask.html#torch.nn.utils.prune.custom_from_mask">custom_from_mask() (in module torch.nn.utils.prune)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.custom_fwd">custom_fwd() (in module torch.cuda.amp)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.CustomFromMask.html#torch.nn.utils.prune.CustomFromMask">CustomFromMask (class in torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.CyclicLR.html#torch.optim.lr_scheduler.CyclicLR">CyclicLR (class in torch.optim.lr_scheduler)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="D">D</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.data">data (torch.nn.utils.rnn.PackedSequence attribute)</a>
</li>
      <li><a href="generated/torch.nn.functional.torch.nn.parallel.data_parallel.html#torch.nn.parallel.data_parallel">data_parallel() (in module torch.nn.parallel)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.data_ptr">data_ptr() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.data_ptr">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.data_ptr">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.data_ptr">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.data_ptr">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.data_ptr">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.data_ptr">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.data_ptr">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.data_ptr">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.data_ptr">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.data_ptr">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.data_ptr">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.data_ptr">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.data_ptr">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.data_ptr">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.data_ptr">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.data_ptr.html#torch.Tensor.data_ptr">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="data.html#torch.utils.data.DataLoader">DataLoader (class in torch.utils.data)</a>
</li>
      <li><a href="generated/torch.nn.DataParallel.html#torch.nn.DataParallel">DataParallel (class in torch.nn)</a>
</li>
      <li><a href="data.html#torch.utils.data.Dataset">Dataset (class in torch.utils.data)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.default_eval_fn">default_eval_fn() (in module torch.quantization)</a>
</li>
      <li><a href="torch.html#torch.torch.default_generator">default_generator (torch.torch attribute)</a>
</li>
      <li><a href="generated/torch.cuda.default_stream.html#torch.cuda.default_stream">default_stream() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.deg2rad.html#torch.deg2rad">deg2rad() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.deg2rad.html#torch.Tensor.deg2rad">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.GraphModule.delete_all_unused_submodules">delete_all_unused_submodules() (torch.fx.GraphModule method)</a>
</li>
      <li><a href="distributed.html#torch.distributed.Store.delete_key">delete_key() (in module torch.distributed.Store)</a>
</li>
      <li><a href="fx.html#torch.fx.GraphModule.delete_submodule">delete_submodule() (torch.fx.GraphModule method)</a>
</li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.CallgrindStats.delta">delta() (torch.utils.benchmark.CallgrindStats method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.denied_modules">denied_modules() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.FunctionCounts.denoise">denoise() (torch.utils.benchmark.FunctionCounts method)</a>
</li>
      <li><a href="generated/torch.Tensor.dense_dim.html#torch.Tensor.dense_dim">dense_dim() (torch.Tensor method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.deny">deny() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.dependency_graph_string">dependency_graph_string() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraints.dependent_property">dependent_property (in module torch.distributions.constraints)</a>
</li>
      <li><a href="torch.nn.quantized.html#torch.nn.quantized.DeQuantize">DeQuantize (class in torch.nn.quantized)</a>
</li>
      <li><a href="generated/torch.dequantize.html#torch.dequantize">dequantize() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.dequantize.html#torch.Tensor.dequantize">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="torch.quantization.html#torch.quantization.DeQuantStub">DeQuantStub (class in torch.quantization)</a>
</li>
      <li><a href="generated/torch.det.html#torch.det">det() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.det.html#torch.linalg.det">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.det.html#torch.Tensor.det">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.detach.html#torch.Tensor.detach">detach() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.detach_.html#torch.Tensor.detach_">detach_() (torch.Tensor method)</a>
</li>
      <li><a href="autograd.html#torch.autograd.detect_anomaly">detect_anomaly (class in torch.autograd)</a>
</li>
      <li><a href="backends.html#torch.backends.cudnn.deterministic">deterministic (torch.backends.cudnn attribute)</a>
</li>
      <li><a href="generated/torch.cuda.device.html#torch.cuda.device">device (class in torch.cuda)</a>

      <ul>
        <li><a href="storage.html#torch.BFloat16Storage.device">(torch.BFloat16Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.BoolStorage.device">(torch.BoolStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.device">(torch.ByteStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.device">(torch.CharStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.device">(torch.ComplexDoubleStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.device">(torch.ComplexFloatStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.device">(torch.DoubleStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.device">(torch.FloatStorage attribute)</a>
</li>
        <li><a href="generated/torch.Generator.html#torch.Generator.device">(torch.Generator attribute)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.device">(torch.HalfStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.device">(torch.IntStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.device">(torch.LongStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.device">(torch.QInt32Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.device">(torch.QInt8Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.device">(torch.QUInt4x2Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.device">(torch.QUInt8Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.device">(torch.ShortStorage attribute)</a>
</li>
        <li><a href="generated/torch.Tensor.device.html#torch.Tensor.device">(torch.Tensor attribute)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.device_count.html#torch.cuda.device_count">device_count() (in module torch.cuda)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.TensorPipeRpcBackendOptions.device_maps">device_maps() (torch.distributed.rpc.TensorPipeRpcBackendOptions property)</a>
</li>
      <li><a href="generated/torch.cuda.device_of.html#torch.cuda.device_of">device_of (class in torch.cuda)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.TensorPipeRpcBackendOptions.devices">devices() (torch.distributed.rpc.TensorPipeRpcBackendOptions property)</a>
</li>
      <li><a href="distributions.html#torch.distributions.chi2.Chi2.df">df() (torch.distributions.chi2.Chi2 property)</a>
</li>
      <li><a href="generated/torch.diag.html#torch.diag">diag() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.diag.html#torch.Tensor.diag">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.diag_embed.html#torch.diag_embed">diag_embed() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.diag_embed.html#torch.Tensor.diag_embed">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.diagflat.html#torch.diagflat">diagflat() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.diagflat.html#torch.Tensor.diagflat">(torch.Tensor method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.diagonal.html#torch.diagonal">diagonal() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.diagonal.html#torch.Tensor.diagonal">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.diff.html#torch.diff">diff() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.diff.html#torch.Tensor.diff">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.digamma.html#torch.digamma">digamma() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.digamma">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.digamma.html#torch.Tensor.digamma">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.digamma_.html#torch.Tensor.digamma_">digamma_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.dim.html#torch.Tensor.dim">dim() (torch.Tensor method)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.dirac_">dirac_() (in module torch.nn.init)</a>
</li>
      <li><a href="package.html#torch.package.Directory">Directory (class in torch.package)</a>
</li>
      <li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet">Dirichlet (class in torch.distributions.dirichlet)</a>
</li>
      <li><a href="generated/torch.dist.html#torch.dist">dist() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.dist.html#torch.Tensor.dist">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel">DistributedDataParallel (class in torch.nn.parallel)</a>
</li>
      <li><a href="rpc.html#torch.distributed.optim.DistributedOptimizer">DistributedOptimizer (class in torch.distributed.optim)</a>
</li>
      <li><a href="data.html#torch.utils.data.distributed.DistributedSampler">DistributedSampler (class in torch.utils.data.distributed)</a>
</li>
      <li><a href="distributions.html#torch.distributions.distribution.Distribution">Distribution (class in torch.distributions.distribution)</a>
</li>
      <li><a href="generated/torch.div.html#torch.div">div() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.div.html#torch.Tensor.div">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.div_.html#torch.Tensor.div_">div_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.divide.html#torch.divide">divide() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.divide.html#torch.Tensor.divide">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.divide_.html#torch.Tensor.divide_">divide_() (torch.Tensor method)</a>
</li>
      <li><a href="futures.html#torch.futures.Future.done">done() (torch.futures.Future method)</a>
</li>
      <li><a href="generated/torch.dot.html#torch.dot">dot() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.dot.html#torch.Tensor.dot">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.BFloat16Storage.double">double() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.double">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.double">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.double">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.double">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.double">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.double">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.double">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.double">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.double">(torch.IntStorage method)</a>
</li>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.double">(torch.jit.ScriptModule method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.double">(torch.LongStorage method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.double">(torch.nn.Module method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.double">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.double">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.double">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.double">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.double">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.double.html#torch.Tensor.double">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.DoubleStorage">DoubleStorage (class in torch)</a>
</li>
      <li><a href="hub.html#torch.hub.download_url_to_file">download_url_to_file() (in module torch.hub)</a>
</li>
      <li><a href="generated/torch.quasirandom.SobolEngine.html#torch.quasirandom.SobolEngine.draw">draw() (torch.quasirandom.SobolEngine method)</a>
</li>
      <li><a href="generated/torch.quasirandom.SobolEngine.html#torch.quasirandom.SobolEngine.draw_base2">draw_base2() (torch.quasirandom.SobolEngine method)</a>
</li>
      <li><a href="generated/torch.nn.Dropout.html#torch.nn.Dropout">Dropout (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.dropout.html#torch.nn.functional.dropout">dropout() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.Dropout2d.html#torch.nn.Dropout2d">Dropout2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.dropout2d.html#torch.nn.functional.dropout2d">dropout2d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.Dropout3d.html#torch.nn.Dropout3d">Dropout3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.dropout3d.html#torch.nn.functional.dropout3d">dropout3d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.dsplit.html#torch.dsplit">dsplit() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.dsplit.html#torch.Tensor.dsplit">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.dstack.html#torch.dstack">dstack() (in module torch)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.dtype">dtype (torch.BFloat16Storage attribute)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.dtype">(torch.BoolStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.dtype">(torch.ByteStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.dtype">(torch.CharStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.dtype">(torch.ComplexDoubleStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.dtype">(torch.ComplexFloatStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.dtype">(torch.DoubleStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.dtype">(torch.FloatStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.dtype">(torch.HalfStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.dtype">(torch.IntStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.dtype">(torch.LongStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.dtype">(torch.QInt32Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.dtype">(torch.QInt8Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.dtype">(torch.QUInt4x2Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.dtype">(torch.QUInt8Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.dtype">(torch.ShortStorage attribute)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.Module.html#torch.nn.Module.dump_patches">dump_patches (torch.nn.Module attribute)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.DynamicRendezvousHandler">DynamicRendezvousHandler (class in torch.distributed.elastic.rendezvous.dynamic_rendezvous)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="E">E</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.eig.html#torch.eig">eig() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.eig.html#torch.linalg.eig">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.eig.html#torch.Tensor.eig">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.linalg.eigh.html#torch.linalg.eigh">eigh() (in module torch.linalg)</a>
</li>
      <li><a href="generated/torch.linalg.eigvals.html#torch.linalg.eigvals">eigvals() (in module torch.linalg)</a>
</li>
      <li><a href="generated/torch.linalg.eigvalsh.html#torch.linalg.eigvalsh">eigvalsh() (in module torch.linalg)</a>
</li>
      <li><a href="generated/torch.einsum.html#torch.einsum">einsum() (in module torch)</a>
</li>
      <li><a href="generated/torch.cuda.Event.html#torch.cuda.Event.elapsed_time">elapsed_time() (torch.cuda.Event method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.ElasticAgent">ElasticAgent (class in torch.distributed.elastic.agent.server)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.element_size">element_size() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.element_size">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.element_size">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.element_size">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.element_size">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.element_size">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.element_size">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.element_size">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.element_size">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.element_size">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.element_size">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.element_size">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.element_size">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.element_size">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.element_size">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.element_size">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.element_size.html#torch.Tensor.element_size">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Graph.eliminate_dead_code">eliminate_dead_code() (torch.fx.Graph method)</a>
</li>
      <li><a href="generated/torch.nn.ELU.html#torch.nn.ELU">ELU (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.ELU">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.elu.html#torch.nn.functional.elu">elu() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.elu_.html#torch.nn.functional.elu_">elu_() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.Embedding.html#torch.nn.Embedding">Embedding (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Embedding">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.embedding.html#torch.nn.functional.embedding">embedding() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.embedding_bag.html#torch.nn.functional.embedding_bag">embedding_bag() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.EmbeddingBag.html#torch.nn.EmbeddingBag">EmbeddingBag (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.EmbeddingBag">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="autograd.html#torch.autograd.profiler.emit_nvtx">emit_nvtx (class in torch.autograd.profiler)</a>
</li>
      <li><a href="generated/torch.empty.html#torch.empty">empty() (in module torch)</a>
</li>
      <li><a href="generated/torch.cuda.empty_cache.html#torch.cuda.empty_cache">empty_cache() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.empty_like.html#torch.empty_like">empty_like() (in module torch)</a>
</li>
      <li><a href="generated/torch.empty_strided.html#torch.empty_strided">empty_strided() (in module torch)</a>
</li>
      <li><a href="package.html#torch.package.EmptyMatchError">EmptyMatchError (class in torch.package)</a>
</li>
      <li><a href="generated/torch.enable_grad.html#torch.enable_grad">enable_grad (class in torch)</a>

      <ul>
        <li><a href="generated/torch.autograd.enable_grad.html#torch.autograd.enable_grad">(class in torch.autograd)</a>
</li>
      </ul></li>
      <li><a href="backends.html#torch.backends.cudnn.enabled">enabled (torch.backends.cudnn attribute)</a>
</li>
      <li><a href="special.html#torch.special.entr">entr() (in module torch.special)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.entropy">entropy() (torch.distributions.bernoulli.Bernoulli method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.beta.Beta.entropy">(torch.distributions.beta.Beta method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.entropy">(torch.distributions.categorical.Categorical method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.entropy">(torch.distributions.cauchy.Cauchy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.entropy">(torch.distributions.continuous_bernoulli.ContinuousBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet.entropy">(torch.distributions.dirichlet.Dirichlet method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.entropy">(torch.distributions.distribution.Distribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exp_family.ExponentialFamily.entropy">(torch.distributions.exp_family.ExponentialFamily method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.entropy">(torch.distributions.exponential.Exponential method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gamma.Gamma.entropy">(torch.distributions.gamma.Gamma method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.geometric.Geometric.entropy">(torch.distributions.geometric.Geometric method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gumbel.Gumbel.entropy">(torch.distributions.gumbel.Gumbel method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.entropy">(torch.distributions.half_cauchy.HalfCauchy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.entropy">(torch.distributions.half_normal.HalfNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.independent.Independent.entropy">(torch.distributions.independent.Independent method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.kumaraswamy.Kumaraswamy.entropy">(torch.distributions.kumaraswamy.Kumaraswamy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.entropy">(torch.distributions.laplace.Laplace method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.log_normal.LogNormal.entropy">(torch.distributions.log_normal.LogNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.entropy">(torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.entropy">(torch.distributions.multivariate_normal.MultivariateNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.entropy">(torch.distributions.normal.Normal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.entropy">(torch.distributions.one_hot_categorical.OneHotCategorical method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.pareto.Pareto.entropy">(torch.distributions.pareto.Pareto method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.studentT.StudentT.entropy">(torch.distributions.studentT.StudentT method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.entropy">(torch.distributions.uniform.Uniform method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.weibull.Weibull.entropy">(torch.distributions.weibull.Weibull method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.enumerate_support">enumerate_support() (torch.distributions.bernoulli.Bernoulli method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.enumerate_support">(torch.distributions.binomial.Binomial method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.enumerate_support">(torch.distributions.categorical.Categorical method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.enumerate_support">(torch.distributions.distribution.Distribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.independent.Independent.enumerate_support">(torch.distributions.independent.Independent method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.enumerate_support">(torch.distributions.one_hot_categorical.OneHotCategorical method)</a>
</li>
      </ul></li>
      <li>
    environment variable

      <ul>
        <li><a href="jit.html#envvar-PYTORCH_JIT">PYTORCH_JIT</a>
</li>
      </ul></li>
      <li><a href="generated/torch.eq.html#torch.eq">eq() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.eq.html#torch.Tensor.eq">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.eq_.html#torch.Tensor.eq_">eq_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.equal.html#torch.equal">equal() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.equal.html#torch.Tensor.equal">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Graph.erase_node">erase_node() (torch.fx.Graph method)</a>
</li>
      <li><a href="generated/torch.erf.html#torch.erf">erf() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.erf">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.erf.html#torch.Tensor.erf">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.erf_.html#torch.Tensor.erf_">erf_() (torch.Tensor method)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.erfc.html#torch.erfc">erfc() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.erfc">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.erfc.html#torch.Tensor.erfc">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.erfc_.html#torch.Tensor.erfc_">erfc_() (torch.Tensor method)</a>
</li>
      <li><a href="special.html#torch.special.erfcx">erfcx() (in module torch.special)</a>
</li>
      <li><a href="generated/torch.erfinv.html#torch.erfinv">erfinv() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.erfinv">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.erfinv.html#torch.Tensor.erfinv">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.erfinv_.html#torch.Tensor.erfinv_">erfinv_() (torch.Tensor method)</a>
</li>
      <li><a href="elastic/errors.html#torch.distributed.elastic.multiprocessing.errors.ErrorHandler">ErrorHandler (class in torch.distributed.elastic.multiprocessing.errors)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_rendezvous_backend.EtcdRendezvousBackend">EtcdRendezvousBackend (class in torch.distributed.elastic.rendezvous.etcd_rendezvous_backend)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_rendezvous.EtcdRendezvousHandler">EtcdRendezvousHandler (class in torch.distributed.elastic.rendezvous.etcd_rendezvous)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_server.EtcdServer">EtcdServer (class in torch.distributed.elastic.rendezvous.etcd_server)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_store.EtcdStore">EtcdStore (class in torch.distributed.elastic.rendezvous.etcd_store)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.eval">eval() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.eval">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.Event.html#torch.cuda.Event">Event (class in torch.cuda)</a>

      <ul>
        <li><a href="elastic/events.html#torch.distributed.elastic.events.api.Event">(class in torch.distributed.elastic.events.api)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.distribution.Distribution.event_shape">event_shape() (torch.distributions.distribution.Distribution property)</a>
</li>
      <li><a href="elastic/events.html#torch.distributed.elastic.events.api.EventMetadataValue">EventMetadataValue (in module torch.distributed.elastic.events.api)</a>
</li>
      <li><a href="profiler.html#torch.profiler.profile.events">events() (torch.profiler.profile method)</a>
</li>
      <li><a href="elastic/events.html#torch.distributed.elastic.events.api.EventSource">EventSource (class in torch.distributed.elastic.events.api)</a>
</li>
      <li><a href="generated/torch.exp.html#torch.exp">exp() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.exp.html#torch.Tensor.exp">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.exp2.html#torch.exp2">exp2() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.exp2">(in module torch.special)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.exp_.html#torch.Tensor.exp_">exp_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.expand">expand() (torch.distributions.bernoulli.Bernoulli method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.beta.Beta.expand">(torch.distributions.beta.Beta method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.expand">(torch.distributions.binomial.Binomial method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.expand">(torch.distributions.categorical.Categorical method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.expand">(torch.distributions.cauchy.Cauchy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.chi2.Chi2.expand">(torch.distributions.chi2.Chi2 method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.expand">(torch.distributions.continuous_bernoulli.ContinuousBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet.expand">(torch.distributions.dirichlet.Dirichlet method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.expand">(torch.distributions.distribution.Distribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.expand">(torch.distributions.exponential.Exponential method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.fishersnedecor.FisherSnedecor.expand">(torch.distributions.fishersnedecor.FisherSnedecor method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gamma.Gamma.expand">(torch.distributions.gamma.Gamma method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.geometric.Geometric.expand">(torch.distributions.geometric.Geometric method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gumbel.Gumbel.expand">(torch.distributions.gumbel.Gumbel method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.expand">(torch.distributions.half_cauchy.HalfCauchy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.expand">(torch.distributions.half_normal.HalfNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.independent.Independent.expand">(torch.distributions.independent.Independent method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.kumaraswamy.Kumaraswamy.expand">(torch.distributions.kumaraswamy.Kumaraswamy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.expand">(torch.distributions.laplace.Laplace method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lkj_cholesky.LKJCholesky.expand">(torch.distributions.lkj_cholesky.LKJCholesky method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.log_normal.LogNormal.expand">(torch.distributions.log_normal.LogNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.expand">(torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.expand">(torch.distributions.mixture_same_family.MixtureSameFamily method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.expand">(torch.distributions.multinomial.Multinomial method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.expand">(torch.distributions.multivariate_normal.MultivariateNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.expand">(torch.distributions.negative_binomial.NegativeBinomial method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.expand">(torch.distributions.normal.Normal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.expand">(torch.distributions.one_hot_categorical.OneHotCategorical method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.pareto.Pareto.expand">(torch.distributions.pareto.Pareto method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.poisson.Poisson.expand">(torch.distributions.poisson.Poisson method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli.expand">(torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.RelaxedBernoulli.expand">(torch.distributions.relaxed_bernoulli.RelaxedBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_categorical.RelaxedOneHotCategorical.expand">(torch.distributions.relaxed_categorical.RelaxedOneHotCategorical method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.studentT.StudentT.expand">(torch.distributions.studentT.StudentT method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.expand">(torch.distributions.transformed_distribution.TransformedDistribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.expand">(torch.distributions.uniform.Uniform method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.von_mises.VonMises.expand">(torch.distributions.von_mises.VonMises method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.weibull.Weibull.expand">(torch.distributions.weibull.Weibull method)</a>
</li>
        <li><a href="generated/torch.Tensor.expand.html#torch.Tensor.expand">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.expand_as.html#torch.Tensor.expand_as">expand_as() (torch.Tensor method)</a>
</li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.expires">expires() (in module torch.distributed.elastic.timer)</a>
</li>
      <li><a href="special.html#torch.special.expit">expit() (in module torch.special)</a>
</li>
      <li><a href="generated/torch.expm1.html#torch.expm1">expm1() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.expm1">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.expm1.html#torch.Tensor.expm1">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.expm1_.html#torch.Tensor.expm1_">expm1_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.exponential.Exponential">Exponential (class in torch.distributions.exponential)</a>
</li>
      <li><a href="generated/torch.Tensor.exponential_.html#torch.Tensor.exponential_">exponential_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.exp_family.ExponentialFamily">ExponentialFamily (class in torch.distributions.exp_family)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.ExponentialLR.html#torch.optim.lr_scheduler.ExponentialLR">ExponentialLR (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="jit.html#torch.jit.export">export() (in module torch.jit)</a>

      <ul>
        <li><a href="onnx.html#torch.onnx.export">(in module torch.onnx)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.autograd.profiler.profile.export_chrome_trace.html#torch.autograd.profiler.profile.export_chrome_trace">export_chrome_trace() (torch.autograd.profiler.profile method)</a>

      <ul>
        <li><a href="profiler.html#torch.profiler.profile.export_chrome_trace">(torch.profiler.profile method)</a>
</li>
      </ul></li>
      <li><a href="profiler.html#torch.profiler.profile.export_stacks">export_stacks() (torch.profiler.profile method)</a>
</li>
      <li><a href="onnx.html#torch.onnx.export_to_pretty_string">export_to_pretty_string() (in module torch.onnx)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.ExpTransform">ExpTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="generated/torch.nn.ModuleList.html#torch.nn.ModuleList.extend">extend() (torch.nn.ModuleList method)</a>

      <ul>
        <li><a href="generated/torch.nn.ParameterList.html#torch.nn.ParameterList.extend">(torch.nn.ParameterList method)</a>
</li>
      </ul></li>
      <li><a href="package.html#torch.package.PackageExporter.extern">extern() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.externed_modules">externed_modules() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.extra_repr">extra_repr() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.extra_repr">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.eye.html#torch.eye">eye() (in module torch)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.eye_">eye_() (in module torch.nn.init)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="F">F</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.fake_quantize_per_channel_affine.html#torch.fake_quantize_per_channel_affine">fake_quantize_per_channel_affine() (in module torch)</a>
</li>
      <li><a href="generated/torch.fake_quantize_per_tensor_affine.html#torch.fake_quantize_per_tensor_affine">fake_quantize_per_tensor_affine() (in module torch)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.FakeQuantize">FakeQuantize (class in torch.quantization)</a>
</li>
      <li><a href="generated/torch.quasirandom.SobolEngine.html#torch.quasirandom.SobolEngine.fast_forward">fast_forward() (torch.quasirandom.SobolEngine method)</a>
</li>
      <li><a href="generated/torch.nn.functional.feature_alpha_dropout.html#torch.nn.functional.feature_alpha_dropout">feature_alpha_dropout() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.FeatureAlphaDropout.html#torch.nn.FeatureAlphaDropout">FeatureAlphaDropout (class in torch.nn)</a>
</li>
      <li><a href="fx.html#torch.fx.Interpreter.fetch_args_kwargs_from_env">fetch_args_kwargs_from_env() (torch.fx.Interpreter method)</a>
</li>
      <li><a href="fx.html#torch.fx.Interpreter.fetch_attr">fetch_attr() (torch.fx.Interpreter method)</a>
</li>
      <li><a href="generated/torch.fft.fft.html#torch.fft.fft">fft() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.fft2.html#torch.fft.fft2">fft2() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.fftfreq.html#torch.fft.fftfreq">fftfreq() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.fftn.html#torch.fft.fftn">fftn() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.fftshift.html#torch.fft.fftshift">fftshift() (in module torch.fft)</a>
</li>
      <li><a href="package.html#torch.package.PackageImporter.file_structure">file_structure() (torch.package.PackageImporter method)</a>
</li>
      <li><a href="distributed.html#torch.distributed.FileStore">FileStore (class in torch.distributed)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.fill_">fill_() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.fill_">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.fill_">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.fill_">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.fill_">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.fill_">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.fill_">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.fill_">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.fill_">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.fill_">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.fill_">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.fill_">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.fill_">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.fill_">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.fill_">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.fill_">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.fill_.html#torch.Tensor.fill_">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.fill_diagonal_.html#torch.Tensor.fill_diagonal_">fill_diagonal_() (torch.Tensor method)</a>
</li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.FunctionCounts.filter">filter() (torch.utils.benchmark.FunctionCounts method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.fishersnedecor.FisherSnedecor">FisherSnedecor (class in torch.distributions.fishersnedecor)</a>
</li>
      <li><a href="generated/torch.fix.html#torch.fix">fix() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.fix.html#torch.Tensor.fix">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.fix_.html#torch.Tensor.fix_">fix_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.Flatten.html#torch.nn.Flatten">Flatten (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.flatten.html#torch.flatten">flatten() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.flatten.html#torch.Tensor.flatten">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Graph.flatten_inps">flatten_inps() (torch.fx.Graph method)</a>
</li>
      <li><a href="generated/torch.nn.RNNBase.html#torch.nn.RNNBase.flatten_parameters">flatten_parameters() (torch.nn.RNNBase method)</a>
</li>
      <li><a href="generated/torch.flip.html#torch.flip">flip() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.flip.html#torch.Tensor.flip">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.fliplr.html#torch.fliplr">fliplr() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.fliplr.html#torch.Tensor.fliplr">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.flipud.html#torch.flipud">flipud() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.flipud.html#torch.Tensor.flipud">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.BFloat16Storage.float">float() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.float">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.float">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.float">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.float">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.float">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.float">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.float">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.float">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.float">(torch.IntStorage method)</a>
</li>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.float">(torch.jit.ScriptModule method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.float">(torch.LongStorage method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.float">(torch.nn.Module method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.float">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.float">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.float">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.float">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.float">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.float.html#torch.Tensor.float">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.float_power.html#torch.float_power">float_power() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.float_power.html#torch.Tensor.float_power">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.float_power_.html#torch.Tensor.float_power_">float_power_() (torch.Tensor method)</a>
</li>
      <li><a href="torch.nn.quantized.html#torch.nn.quantized.FloatFunctional">FloatFunctional (class in torch.nn.quantized)</a>
</li>
      <li><a href="storage.html#torch.FloatStorage">FloatStorage (class in torch)</a>
</li>
      <li><a href="generated/torch.floor.html#torch.floor">floor() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.floor.html#torch.Tensor.floor">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.floor_.html#torch.Tensor.floor_">floor_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.floor_divide.html#torch.floor_divide">floor_divide() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.floor_divide.html#torch.Tensor.floor_divide">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.floor_divide_.html#torch.Tensor.floor_divide_">floor_divide_() (torch.Tensor method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter.flush">flush() (torch.utils.tensorboard.writer.SummaryWriter method)</a>
</li>
      <li><a href="generated/torch.fmax.html#torch.fmax">fmax() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.fmax.html#torch.Tensor.fmax">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.fmin.html#torch.fmin">fmin() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.fmin.html#torch.Tensor.fmin">(torch.Tensor method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.fmod.html#torch.fmod">fmod() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.fmod.html#torch.Tensor.fmod">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.fmod_.html#torch.Tensor.fmod_">fmod_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.Fold.html#torch.nn.Fold">Fold (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.fold.html#torch.nn.functional.fold">fold() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.jit.fork.html#torch.jit.fork">fork() (in module torch.jit)</a>
</li>
      <li><a href="random.html#torch.random.fork_rng">fork_rng() (in module torch.random)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.format_node">format_node() (torch.fx.Node method)</a>
</li>
      <li><a href="generated/torch.autograd.Function.forward.html#torch.autograd.Function.forward">forward() (torch.autograd.Function static method)</a>

      <ul>
        <li><a href="pipeline.html#torch.distributed.pipeline.sync.Pipe.forward">(torch.distributed.pipeline.sync.Pipe method)</a>
</li>
        <li><a href="generated/torch.nn.EmbeddingBag.html#torch.nn.EmbeddingBag.forward">(torch.nn.EmbeddingBag method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.forward">(torch.nn.Module method)</a>
</li>
        <li><a href="generated/torch.nn.MultiheadAttention.html#torch.nn.MultiheadAttention.forward">(torch.nn.MultiheadAttention method)</a>
</li>
        <li><a href="generated/torch.nn.Transformer.html#torch.nn.Transformer.forward">(torch.nn.Transformer method)</a>
</li>
        <li><a href="generated/torch.nn.TransformerDecoder.html#torch.nn.TransformerDecoder.forward">(torch.nn.TransformerDecoder method)</a>
</li>
        <li><a href="generated/torch.nn.TransformerDecoderLayer.html#torch.nn.TransformerDecoderLayer.forward">(torch.nn.TransformerDecoderLayer method)</a>
</li>
        <li><a href="generated/torch.nn.TransformerEncoder.html#torch.nn.TransformerEncoder.forward">(torch.nn.TransformerEncoder method)</a>
</li>
        <li><a href="generated/torch.nn.TransformerEncoderLayer.html#torch.nn.TransformerEncoderLayer.forward">(torch.nn.TransformerEncoderLayer method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.transforms.Transform.forward_shape">forward_shape() (torch.distributions.transforms.Transform method)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.algorithms.ddp_comm_hooks.default_hooks.fp16_compress_hook">fp16_compress_hook() (in module torch.distributed.algorithms.ddp_comm_hooks.default_hooks)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.algorithms.ddp_comm_hooks.default_hooks.fp16_compress_wrapper">fp16_compress_wrapper() (in module torch.distributed.algorithms.ddp_comm_hooks.default_hooks)</a>
</li>
      <li><a href="generated/torch.frac.html#torch.frac">frac() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.frac.html#torch.Tensor.frac">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.frac_.html#torch.Tensor.frac_">frac_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.functional.fractional_max_pool2d.html#torch.nn.functional.fractional_max_pool2d">fractional_max_pool2d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.fractional_max_pool3d.html#torch.nn.functional.fractional_max_pool3d">fractional_max_pool3d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.FractionalMaxPool2d.html#torch.nn.FractionalMaxPool2d">FractionalMaxPool2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.FractionalMaxPool3d.html#torch.nn.FractionalMaxPool3d">FractionalMaxPool3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.jit.freeze.html#torch.jit.freeze">freeze() (in module torch.jit)</a>
</li>
      <li><a href="generated/torch.frexp.html#torch.frexp">frexp() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.frexp.html#torch.Tensor.frexp">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.DynamicRendezvousHandler.from_backend">from_backend() (torch.distributed.elastic.rendezvous.dynamic_rendezvous.DynamicRendezvousHandler class method)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.from_buffer">from_buffer() (torch.BFloat16Storage static method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.from_buffer">(torch.BoolStorage static method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.from_buffer">(torch.ByteStorage static method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.from_buffer">(torch.CharStorage static method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.from_buffer">(torch.ComplexDoubleStorage static method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.from_buffer">(torch.ComplexFloatStorage static method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.from_buffer">(torch.DoubleStorage static method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.from_buffer">(torch.FloatStorage static method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.from_buffer">(torch.HalfStorage static method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.from_buffer">(torch.IntStorage static method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.from_buffer">(torch.LongStorage static method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.from_buffer">(torch.QInt32Storage static method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.from_buffer">(torch.QInt8Storage static method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.from_buffer">(torch.QUInt4x2Storage static method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.from_buffer">(torch.QUInt8Storage static method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.from_buffer">(torch.ShortStorage static method)</a>
</li>
      </ul></li>
      <li><a href="dlpack.html#torch.utils.dlpack.from_dlpack">from_dlpack() (in module torch.utils.dlpack)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.from_file">from_file() (torch.BFloat16Storage static method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.from_file">(torch.BoolStorage static method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.from_file">(torch.ByteStorage static method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.from_file">(torch.CharStorage static method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.from_file">(torch.ComplexDoubleStorage static method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.from_file">(torch.ComplexFloatStorage static method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.from_file">(torch.DoubleStorage static method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.from_file">(torch.FloatStorage static method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.from_file">(torch.HalfStorage static method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.from_file">(torch.IntStorage static method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.from_file">(torch.LongStorage static method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.from_file">(torch.QInt32Storage static method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.from_file">(torch.QInt8Storage static method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.from_file">(torch.QUInt4x2Storage static method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.from_file">(torch.QUInt8Storage static method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.from_file">(torch.ShortStorage static method)</a>
</li>
      </ul></li>
      <li><a href="torch.nn.qat.html#torch.nn.qat.Conv2d.from_float">from_float() (torch.nn.qat.Conv2d class method)</a>

      <ul>
        <li><a href="torch.nn.qat.html#torch.nn.qat.Linear.from_float">(torch.nn.qat.Linear class method)</a>
</li>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Conv1d.from_float">(torch.nn.quantized.Conv1d class method)</a>
</li>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Conv2d.from_float">(torch.nn.quantized.Conv2d class method)</a>
</li>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Conv3d.from_float">(torch.nn.quantized.Conv3d class method)</a>
</li>
        <li><a href="torch.nn.quantized.dynamic.html#torch.nn.quantized.dynamic.Linear.from_float">(torch.nn.quantized.dynamic.Linear class method)</a>
</li>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Embedding.from_float">(torch.nn.quantized.Embedding class method)</a>
</li>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.EmbeddingBag.from_float">(torch.nn.quantized.EmbeddingBag class method)</a>
</li>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Linear.from_float">(torch.nn.quantized.Linear class method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.Event.html#torch.cuda.Event.from_ipc_handle">from_ipc_handle() (torch.cuda.Event class method)</a>
</li>
      <li><a href="generated/torch.from_numpy.html#torch.from_numpy">from_numpy() (in module torch)</a>
</li>
      <li><a href="generated/torch.nn.Embedding.html#torch.nn.Embedding.from_pretrained">from_pretrained() (torch.nn.Embedding class method)</a>

      <ul>
        <li><a href="generated/torch.nn.EmbeddingBag.html#torch.nn.EmbeddingBag.from_pretrained">(torch.nn.EmbeddingBag class method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.frombuffer.html#torch.frombuffer">frombuffer() (in module torch)</a>
</li>
      <li><a href="generated/torch.full.html#torch.full">full() (in module torch)</a>
</li>
      <li><a href="generated/torch.full_like.html#torch.full_like">full_like() (in module torch)</a>
</li>
      <li><a href="autograd.html#torch.autograd.Function">Function (class in torch.autograd)</a>
</li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.FunctionCounts">FunctionCounts (class in torch.utils.benchmark)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.fuse_modules">fuse_modules() (in module torch.quantization)</a>
</li>
      <li><a href="futures.html#torch.futures.Future">Future (class in torch.futures)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="G">G</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="distributions.html#torch.distributions.gamma.Gamma">Gamma (class in torch.distributions.gamma)</a>
</li>
      <li><a href="special.html#torch.special.gammainc">gammainc() (in module torch.special)</a>
</li>
      <li><a href="special.html#torch.special.gammaincc">gammaincc() (in module torch.special)</a>
</li>
      <li><a href="special.html#torch.special.gammaln">gammaln() (in module torch.special)</a>
</li>
      <li><a href="generated/torch.gather.html#torch.gather">gather() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.cuda.comm.gather.html#torch.cuda.comm.gather">(in module torch.cuda.comm)</a>
</li>
        <li><a href="distributed.html#torch.distributed.gather">(in module torch.distributed)</a>
</li>
        <li><a href="generated/torch.Tensor.gather.html#torch.Tensor.gather">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributed.html#torch.distributed.gather_object">gather_object() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.nn.functional.gaussian_nll_loss.html#torch.nn.functional.gaussian_nll_loss">gaussian_nll_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.GaussianNLLLoss.html#torch.nn.GaussianNLLLoss">GaussianNLLLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.gcd.html#torch.gcd">gcd() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.gcd.html#torch.Tensor.gcd">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.gcd_.html#torch.Tensor.gcd_">gcd_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.ge.html#torch.ge">ge() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.ge.html#torch.Tensor.ge">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.ge_.html#torch.Tensor.ge_">ge_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.GELU.html#torch.nn.GELU">GELU (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.gelu.html#torch.nn.functional.gelu">gelu() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.Transformer.html#torch.nn.Transformer.generate_square_subsequent_mask">generate_square_subsequent_mask() (torch.nn.Transformer static method)</a>
</li>
      <li><a href="generated/torch.Generator.html#torch.Generator">Generator (class in torch)</a>
</li>
      <li><a href="distributions.html#torch.distributions.geometric.Geometric">Geometric (class in torch.distributions.geometric)</a>
</li>
      <li><a href="generated/torch.Tensor.geometric_.html#torch.Tensor.geometric_">geometric_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.geqrf.html#torch.geqrf">geqrf() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.geqrf.html#torch.Tensor.geqrf">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.ger.html#torch.ger">ger() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.ger.html#torch.Tensor.ger">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributed.html#torch.distributed.Store.get">get() (in module torch.distributed.Store)</a>

      <ul>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_store.EtcdStore.get">(torch.distributed.elastic.rendezvous.etcd_store.EtcdStore method)</a>
</li>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousParameters.get">(torch.distributed.elastic.rendezvous.RendezvousParameters method)</a>
</li>
      </ul></li>
      <li><a href="multiprocessing.html#torch.multiprocessing.get_all_sharing_strategies">get_all_sharing_strategies() (in module torch.multiprocessing)</a>
</li>
      <li><a href="generated/torch.cuda.get_arch_list.html#torch.cuda.get_arch_list">get_arch_list() (in module torch.cuda)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousParameters.get_as_bool">get_as_bool() (torch.distributed.elastic.rendezvous.RendezvousParameters method)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousParameters.get_as_int">get_as_int() (torch.distributed.elastic.rendezvous.RendezvousParameters method)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.get_attr">get_attr() (torch.fx.Graph method)</a>

      <ul>
        <li><a href="fx.html#torch.fx.Interpreter.get_attr">(torch.fx.Interpreter method)</a>
</li>
        <li><a href="fx.html#torch.fx.Transformer.get_attr">(torch.fx.Transformer method)</a>
</li>
      </ul></li>
      <li><a href="distributed.html#torch.distributed.get_backend">get_backend() (in module torch.distributed)</a>

      <ul>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandler.get_backend">(torch.distributed.elastic.rendezvous.RendezvousHandler method)</a>
</li>
      </ul></li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.get_backoff_factor">get_backoff_factor() (torch.cuda.amp.GradScaler method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.get_buffer">get_buffer() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.get_buffer">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptFunction.html#torch.jit.ScriptFunction.get_debug_state">get_debug_state() (torch.jit.ScriptFunction method)</a>
</li>
      <li><a href="generated/torch.get_default_dtype.html#torch.get_default_dtype">get_default_dtype() (in module torch)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.get_device">get_device() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.get_device">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.get_device">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.get_device">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.get_device">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.get_device">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.get_device">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.get_device">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.get_device">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.get_device">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.get_device">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.get_device">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.get_device">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.get_device">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.get_device">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.get_device">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.get_device.html#torch.Tensor.get_device">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.get_device_capability.html#torch.cuda.get_device_capability">get_device_capability() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.get_device_name.html#torch.cuda.get_device_name">get_device_name() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.get_device_properties.html#torch.cuda.get_device_properties">get_device_properties() (in module torch.cuda)</a>
</li>
      <li><a href="hub.html#torch.hub.get_dir">get_dir() (in module torch.hub)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.WorkerSpec.get_entrypoint_name">get_entrypoint_name() (torch.distributed.elastic.agent.server.WorkerSpec method)</a>
</li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.TimerServer.get_expired_timers">get_expired_timers() (torch.distributed.elastic.timer.TimerServer method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.get_extra_state">get_extra_state() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.get_extra_state">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.get_gencode_flags.html#torch.cuda.get_gencode_flags">get_gencode_flags() (in module torch.cuda)</a>
</li>
      <li><a href="rpc.html#torch.distributed.autograd.get_gradients">get_gradients() (in module torch.distributed.autograd)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.get_growth_factor">get_growth_factor() (torch.cuda.amp.GradScaler method)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.get_growth_interval">get_growth_interval() (torch.cuda.amp.GradScaler method)</a>
</li>
      <li><a href="torch.overrides.html#torch.overrides.get_ignored_functions">get_ignored_functions() (in module torch.overrides)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.ChainedScheduler.html#torch.optim.lr_scheduler.ChainedScheduler.get_last_lr">get_last_lr() (torch.optim.lr_scheduler.ChainedScheduler method)</a>

      <ul>
        <li><a href="generated/torch.optim.lr_scheduler.ConstantLR.html#torch.optim.lr_scheduler.ConstantLR.get_last_lr">(torch.optim.lr_scheduler.ConstantLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingLR.html#torch.optim.lr_scheduler.CosineAnnealingLR.get_last_lr">(torch.optim.lr_scheduler.CosineAnnealingLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.html#torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.get_last_lr">(torch.optim.lr_scheduler.CosineAnnealingWarmRestarts method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CyclicLR.html#torch.optim.lr_scheduler.CyclicLR.get_last_lr">(torch.optim.lr_scheduler.CyclicLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.ExponentialLR.html#torch.optim.lr_scheduler.ExponentialLR.get_last_lr">(torch.optim.lr_scheduler.ExponentialLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.LambdaLR.html#torch.optim.lr_scheduler.LambdaLR.get_last_lr">(torch.optim.lr_scheduler.LambdaLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.LinearLR.html#torch.optim.lr_scheduler.LinearLR.get_last_lr">(torch.optim.lr_scheduler.LinearLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.MultiplicativeLR.html#torch.optim.lr_scheduler.MultiplicativeLR.get_last_lr">(torch.optim.lr_scheduler.MultiplicativeLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.MultiStepLR.html#torch.optim.lr_scheduler.MultiStepLR.get_last_lr">(torch.optim.lr_scheduler.MultiStepLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.OneCycleLR.html#torch.optim.lr_scheduler.OneCycleLR.get_last_lr">(torch.optim.lr_scheduler.OneCycleLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.SequentialLR.html#torch.optim.lr_scheduler.SequentialLR.get_last_lr">(torch.optim.lr_scheduler.SequentialLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.StepLR.html#torch.optim.lr_scheduler.StepLR.get_last_lr">(torch.optim.lr_scheduler.StepLR method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="elastic/events.html#torch.distributed.elastic.events.get_logging_handler">get_logging_handler() (in module torch.distributed.elastic.events)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.CyclicLR.html#torch.optim.lr_scheduler.CyclicLR.get_lr">get_lr() (torch.optim.lr_scheduler.CyclicLR method)</a>
</li>
      <li><a href="rpc.html#torch.distributed.nn.api.remote_module.RemoteModule.get_module_rref">get_module_rref() (torch.distributed.nn.api.remote_module.RemoteModule method)</a>
</li>
      <li><a href="generated/torch.get_num_interop_threads.html#torch.get_num_interop_threads">get_num_interop_threads() (in module torch)</a>
</li>
      <li><a href="generated/torch.get_num_threads.html#torch.get_num_threads">get_num_threads() (in module torch)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.get_observer_dict">get_observer_dict() (in module torch.quantization)</a>
</li>
      <li><a href="torch.overrides.html#torch.overrides.get_overridable_functions">get_overridable_functions() (in module torch.overrides)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.get_parameter">get_parameter() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.get_parameter">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="distributed.html#torch.distributed.get_rank">get_rank() (in module torch.distributed)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.get_rdeps">get_rdeps() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="generated/torch.get_rng_state.html#torch.get_rng_state">get_rng_state() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.cuda.get_rng_state.html#torch.cuda.get_rng_state">(in module torch.cuda)</a>
</li>
        <li><a href="random.html#torch.random.get_rng_state">(in module torch.random)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.get_rng_state_all.html#torch.cuda.get_rng_state_all">get_rng_state_all() (in module torch.cuda)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandler.get_run_id">get_run_id() (torch.distributed.elastic.rendezvous.RendezvousHandler method)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.get_scale">get_scale() (torch.cuda.amp.GradScaler method)</a>
</li>
      <li><a href="multiprocessing.html#torch.multiprocessing.get_sharing_strategy">get_sharing_strategy() (in module torch.multiprocessing)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.c10d_rendezvous_backend.C10dRendezvousBackend.get_state">get_state() (torch.distributed.elastic.rendezvous.c10d_rendezvous_backend.C10dRendezvousBackend method)</a>

      <ul>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousBackend.get_state">(torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousBackend method)</a>
</li>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_rendezvous_backend.EtcdRendezvousBackend.get_state">(torch.distributed.elastic.rendezvous.etcd_rendezvous_backend.EtcdRendezvousBackend method)</a>
</li>
        <li><a href="generated/torch.Generator.html#torch.Generator.get_state">(torch.Generator method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.get_submodule">get_submodule() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.get_submodule">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.get_sync_debug_mode.html#torch.cuda.get_sync_debug_mode">get_sync_debug_mode() (in module torch.cuda)</a>
</li>
      <li><a href="torch.overrides.html#torch.overrides.get_testing_overrides">get_testing_overrides() (in module torch.overrides)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.get_unique_id">get_unique_id() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.ElasticAgent.get_worker_group">get_worker_group() (torch.distributed.elastic.agent.server.ElasticAgent method)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.get_worker_info">get_worker_info() (in module torch.distributed.rpc)</a>

      <ul>
        <li><a href="data.html#torch.utils.data.get_worker_info">(in module torch.utils.data)</a>
</li>
      </ul></li>
      <li><a href="distributed.html#torch.distributed.get_world_size">get_world_size() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.global_unstructured.html#torch.nn.utils.prune.global_unstructured">global_unstructured() (in module torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.nn.GLU.html#torch.nn.GLU">GLU (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.glu.html#torch.nn.functional.glu">glu() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.autograd.grad.html#torch.autograd.grad">grad() (in module torch.autograd)</a>

      <ul>
        <li><a href="generated/torch.Tensor.grad.html#torch.Tensor.grad">(torch.Tensor property)</a>
</li>
      </ul></li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.GradBucket">GradBucket (class in torch.distributed)</a>
</li>
      <li><a href="generated/torch.autograd.gradcheck.html#torch.autograd.gradcheck">gradcheck() (in module torch.autograd)</a>
</li>
      <li><a href="generated/torch.autograd.gradgradcheck.html#torch.autograd.gradgradcheck">gradgradcheck() (in module torch.autograd)</a>
</li>
      <li><a href="generated/torch.gradient.html#torch.gradient">gradient() (in module torch)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.GradBucket.gradients">gradients() (in module torch.distributed.GradBucket)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler">GradScaler (class in torch.cuda.amp)</a>
</li>
      <li><a href="generated/torch.cuda.graph.html#torch.cuda.graph">graph (class in torch.cuda)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph">Graph (class in torch.fx)</a>
</li>
      <li><a href="fx.html#torch.fx.GraphModule.graph">graph() (torch.fx.GraphModule property)</a>

      <ul>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.graph">(torch.jit.ScriptModule property)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Graph.graph_copy">graph_copy() (torch.fx.Graph method)</a>
</li>
      <li><a href="generated/torch.cuda.graph_pool_handle.html#torch.cuda.graph_pool_handle">graph_pool_handle() (in module torch.cuda)</a>
</li>
      <li><a href="fx.html#torch.fx.GraphModule">GraphModule (class in torch.fx)</a>
</li>
      <li><a href="generated/torch.greater.html#torch.greater">greater() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.greater.html#torch.Tensor.greater">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.greater_.html#torch.Tensor.greater_">greater_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.greater_equal.html#torch.greater_equal">greater_equal() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.greater_equal.html#torch.Tensor.greater_equal">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.greater_equal_.html#torch.Tensor.greater_equal_">greater_equal_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraints.greater_than">greater_than (in module torch.distributions.constraints)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraints.greater_than_eq">greater_than_eq (in module torch.distributions.constraints)</a>
</li>
      <li><a href="generated/torch.nn.functional.grid_sample.html#torch.nn.functional.grid_sample">grid_sample() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.group_norm.html#torch.nn.functional.group_norm">group_norm() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.GroupNorm.html#torch.nn.GroupNorm">GroupNorm (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.GroupNorm">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.GRU.html#torch.nn.GRU">GRU (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.GRUCell.html#torch.nn.GRUCell">GRUCell (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.dynamic.html#torch.nn.quantized.dynamic.GRUCell">(class in torch.nn.quantized.dynamic)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.gt.html#torch.gt">gt() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.gt.html#torch.Tensor.gt">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.gt_.html#torch.Tensor.gt_">gt_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.gumbel.Gumbel">Gumbel (class in torch.distributions.gumbel)</a>
</li>
      <li><a href="generated/torch.nn.functional.gumbel_softmax.html#torch.nn.functional.gumbel_softmax">gumbel_softmax() (in module torch.nn.functional)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="H">H</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="storage.html#torch.BFloat16Storage.half">half() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.half">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.half">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.half">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.half">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.half">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.half">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.half">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.half">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.half">(torch.IntStorage method)</a>
</li>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.half">(torch.jit.ScriptModule method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.half">(torch.LongStorage method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.half">(torch.nn.Module method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.half">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.half">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.half">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.half">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.half">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.half.html#torch.Tensor.half">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.constraints.half_open_interval">half_open_interval (in module torch.distributions.constraints)</a>
</li>
      <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy">HalfCauchy (class in torch.distributions.half_cauchy)</a>
</li>
      <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal">HalfNormal (class in torch.distributions.half_normal)</a>
</li>
      <li><a href="storage.html#torch.HalfStorage">HalfStorage (class in torch)</a>
</li>
      <li><a href="generated/torch.hamming_window.html#torch.hamming_window">hamming_window() (in module torch)</a>
</li>
      <li><a href="torch.overrides.html#torch.overrides.handle_torch_function">handle_torch_function() (in module torch.overrides)</a>
</li>
      <li><a href="generated/torch.hann_window.html#torch.hann_window">hann_window() (in module torch)</a>
</li>
      <li><a href="generated/torch.nn.Hardshrink.html#torch.nn.Hardshrink">Hardshrink (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.hardshrink.html#torch.nn.functional.hardshrink">hardshrink() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="generated/torch.Tensor.hardshrink.html#torch.Tensor.hardshrink">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.Hardsigmoid.html#torch.nn.Hardsigmoid">Hardsigmoid (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.hardsigmoid.html#torch.nn.functional.hardsigmoid">hardsigmoid() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.Hardswish.html#torch.nn.Hardswish">Hardswish (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Hardswish">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.hardswish.html#torch.nn.functional.hardswish">hardswish() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.hardswish">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.Hardtanh.html#torch.nn.Hardtanh">Hardtanh (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.hardtanh.html#torch.nn.functional.hardtanh">hardtanh() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.hardtanh_.html#torch.nn.functional.hardtanh_">hardtanh_() (in module torch.nn.functional)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.has_enumerate_support">has_enumerate_support (torch.distributions.bernoulli.Bernoulli attribute)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.has_enumerate_support">(torch.distributions.binomial.Binomial attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.has_enumerate_support">(torch.distributions.categorical.Categorical attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.has_enumerate_support">(torch.distributions.one_hot_categorical.OneHotCategorical attribute)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.independent.Independent.has_enumerate_support">has_enumerate_support() (torch.distributions.independent.Independent property)</a>
</li>
      <li><a href="package.html#torch.package.Directory.has_file">has_file() (torch.package.Directory method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.beta.Beta.has_rsample">has_rsample (torch.distributions.beta.Beta attribute)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.has_rsample">(torch.distributions.cauchy.Cauchy attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.has_rsample">(torch.distributions.continuous_bernoulli.ContinuousBernoulli attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet.has_rsample">(torch.distributions.dirichlet.Dirichlet attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.has_rsample">(torch.distributions.exponential.Exponential attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.fishersnedecor.FisherSnedecor.has_rsample">(torch.distributions.fishersnedecor.FisherSnedecor attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gamma.Gamma.has_rsample">(torch.distributions.gamma.Gamma attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.has_rsample">(torch.distributions.half_cauchy.HalfCauchy attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.has_rsample">(torch.distributions.half_normal.HalfNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.kumaraswamy.Kumaraswamy.has_rsample">(torch.distributions.kumaraswamy.Kumaraswamy attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.has_rsample">(torch.distributions.laplace.Laplace attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.log_normal.LogNormal.has_rsample">(torch.distributions.log_normal.LogNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.has_rsample">(torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.has_rsample">(torch.distributions.mixture_same_family.MixtureSameFamily attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.has_rsample">(torch.distributions.multivariate_normal.MultivariateNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.has_rsample">(torch.distributions.normal.Normal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.RelaxedBernoulli.has_rsample">(torch.distributions.relaxed_bernoulli.RelaxedBernoulli attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_categorical.RelaxedOneHotCategorical.has_rsample">(torch.distributions.relaxed_categorical.RelaxedOneHotCategorical attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.studentT.StudentT.has_rsample">(torch.distributions.studentT.StudentT attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.has_rsample">(torch.distributions.uniform.Uniform attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.von_mises.VonMises.has_rsample">(torch.distributions.von_mises.VonMises attribute)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="distributions.html#torch.distributions.independent.Independent.has_rsample">has_rsample() (torch.distributions.independent.Independent property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.has_rsample">(torch.distributions.transformed_distribution.TransformedDistribution property)</a>
</li>
      </ul></li>
      <li><a href="torch.overrides.html#torch.overrides.has_torch_function">has_torch_function() (in module torch.overrides)</a>
</li>
      <li><a href="generated/torch.nn.modules.lazy.LazyModuleMixin.html#torch.nn.modules.lazy.LazyModuleMixin.has_uninitialized_params">has_uninitialized_params() (torch.nn.modules.lazy.LazyModuleMixin method)</a>
</li>
      <li><a href="distributed.html#torch.distributed.HashStore">HashStore (class in torch.distributed)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousTimeout.heartbeat">heartbeat() (torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousTimeout property)</a>
</li>
      <li><a href="generated/torch.heaviside.html#torch.heaviside">heaviside() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.heaviside.html#torch.Tensor.heaviside">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="hub.html#torch.hub.help">help() (in module torch.hub)</a>
</li>
      <li><a href="generated/torch.autograd.functional.hessian.html#torch.autograd.functional.hessian">hessian() (in module torch.autograd.functional)</a>
</li>
      <li><a href="generated/torch.fft.hfft.html#torch.fft.hfft">hfft() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.nn.functional.hinge_embedding_loss.html#torch.nn.functional.hinge_embedding_loss">hinge_embedding_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.HingeEmbeddingLoss.html#torch.nn.HingeEmbeddingLoss">HingeEmbeddingLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.histc.html#torch.histc">histc() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.histc.html#torch.Tensor.histc">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.histogram.html#torch.histogram">histogram() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.histogram.html#torch.Tensor.histogram">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="torch.quantization.html#torch.quantization.HistogramObserver">HistogramObserver (class in torch.quantization)</a>
</li>
      <li><a href="generated/torch.linalg.householder_product.html#torch.linalg.householder_product">householder_product() (in module torch.linalg)</a>
</li>
      <li><a href="generated/torch.hsplit.html#torch.hsplit">hsplit() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.hsplit.html#torch.Tensor.hsplit">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.hspmm.html#torch.hspmm">hspmm() (in module torch)</a>
</li>
      <li><a href="generated/torch.hstack.html#torch.hstack">hstack() (in module torch)</a>
</li>
      <li><a href="generated/torch.nn.functional.huber_loss.html#torch.nn.functional.huber_loss">huber_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.HuberLoss.html#torch.nn.HuberLoss">HuberLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.autograd.functional.hvp.html#torch.autograd.functional.hvp">hvp() (in module torch.autograd.functional)</a>
</li>
      <li><a href="generated/torch.hypot.html#torch.hypot">hypot() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.hypot.html#torch.Tensor.hypot">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.hypot_.html#torch.Tensor.hypot_">hypot_() (torch.Tensor method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="I">I</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.i0.html#torch.i0">i0() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.i0">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.i0.html#torch.Tensor.i0">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.i0_.html#torch.Tensor.i0_">i0_() (torch.Tensor method)</a>
</li>
      <li><a href="special.html#torch.special.i0e">i0e() (in module torch.special)</a>
</li>
      <li><a href="special.html#torch.special.i1">i1() (in module torch.special)</a>
</li>
      <li><a href="special.html#torch.special.i1e">i1e() (in module torch.special)</a>
</li>
      <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.icdf">icdf() (torch.distributions.cauchy.Cauchy method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.icdf">(torch.distributions.continuous_bernoulli.ContinuousBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.icdf">(torch.distributions.distribution.Distribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.icdf">(torch.distributions.exponential.Exponential method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.icdf">(torch.distributions.half_cauchy.HalfCauchy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.icdf">(torch.distributions.half_normal.HalfNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.icdf">(torch.distributions.laplace.Laplace method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.icdf">(torch.distributions.normal.Normal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.icdf">(torch.distributions.transformed_distribution.TransformedDistribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.icdf">(torch.distributions.uniform.Uniform method)</a>
</li>
      </ul></li>
      <li><a href="rpc.html#torch.distributed.rpc.WorkerInfo.id">id() (torch.distributed.rpc.WorkerInfo property)</a>

      <ul>
        <li><a href="package.html#torch.package.PackageImporter.id">(torch.package.PackageImporter method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.Identity.html#torch.nn.Identity">Identity (class in torch.nn)</a>

      <ul>
        <li><a href="generated/torch.nn.utils.prune.Identity.html#torch.nn.utils.prune.Identity">(class in torch.nn.utils.prune)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.utils.prune.identity.html#torch.nn.utils.prune.identity">identity() (in module torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.fft.ifft.html#torch.fft.ifft">ifft() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.ifft2.html#torch.fft.ifft2">ifft2() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.ifftn.html#torch.fft.ifftn">ifftn() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.ifftshift.html#torch.fft.ifftshift">ifftshift() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.igamma.html#torch.igamma">igamma() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.igamma.html#torch.Tensor.igamma">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.igamma_.html#torch.Tensor.igamma_">igamma_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.igammac.html#torch.igammac">igammac() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.igammac.html#torch.Tensor.igammac">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.igammac_.html#torch.Tensor.igammac_">igammac_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.jit.ignore.html#torch.jit.ignore">ignore() (in module torch.jit)</a>
</li>
      <li><a href="generated/torch.fft.ihfft.html#torch.fft.ihfft">ihfft() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.Tensor.imag.html#torch.Tensor.imag">imag (torch.Tensor attribute)</a>
</li>
      <li><a href="generated/torch.imag.html#torch.imag">imag() (in module torch)</a>
</li>
      <li><a href="package.html#torch.package.PackageImporter.import_module">import_module() (torch.package.PackageImporter method)</a>
</li>
      <li><a href="cpp_extension.html#torch.utils.cpp_extension.include_paths">include_paths() (in module torch.utils.cpp_extension)</a>
</li>
      <li><a href="distributions.html#torch.distributions.independent.Independent">Independent (class in torch.distributions.independent)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraints.independent">independent (in module torch.distributions.constraints)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.IndependentTransform">IndependentTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.GradBucket.index">index() (in module torch.distributed.GradBucket)</a>

      <ul>
        <li><a href="generated/torch.jit.Attribute.html#torch.jit.Attribute.index">(torch.jit.Attribute method)</a>
</li>
        <li><a href="generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.index">(torch.nn.utils.rnn.PackedSequence method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.index_add.html#torch.Tensor.index_add">index_add() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.index_add_.html#torch.Tensor.index_add_">index_add_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.index_copy.html#torch.Tensor.index_copy">index_copy() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.index_copy_.html#torch.Tensor.index_copy_">index_copy_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.index_fill.html#torch.Tensor.index_fill">index_fill() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.index_fill_.html#torch.Tensor.index_fill_">index_fill_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.index_put.html#torch.Tensor.index_put">index_put() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.index_put_.html#torch.Tensor.index_put_">index_put_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.index_select.html#torch.index_select">index_select() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.index_select.html#torch.Tensor.index_select">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.indices.html#torch.Tensor.indices">indices() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.inference_mode.html#torch.inference_mode">inference_mode (class in torch)</a>

      <ul>
        <li><a href="generated/torch.autograd.inference_mode.html#torch.autograd.inference_mode">(class in torch.autograd)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.init.html#torch.cuda.init">init() (in module torch.cuda)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.RpcBackendOptions.init_method">init_method() (torch.distributed.rpc.RpcBackendOptions property)</a>

      <ul>
        <li><a href="rpc.html#torch.distributed.rpc.TensorPipeRpcBackendOptions.init_method">(torch.distributed.rpc.TensorPipeRpcBackendOptions property)</a>
</li>
      </ul></li>
      <li><a href="distributed.html#torch.distributed.init_process_group">init_process_group() (in module torch.distributed)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.init_rpc">init_rpc() (in module torch.distributed.rpc)</a>
</li>
      <li><a href="generated/torch.initial_seed.html#torch.initial_seed">initial_seed() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.cuda.initial_seed.html#torch.cuda.initial_seed">(in module torch.cuda)</a>
</li>
        <li><a href="random.html#torch.random.initial_seed">(in module torch.random)</a>
</li>
        <li><a href="generated/torch.Generator.html#torch.Generator.initial_seed">(torch.Generator method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.modules.lazy.LazyModuleMixin.html#torch.nn.modules.lazy.LazyModuleMixin.initialize_parameters">initialize_parameters() (torch.nn.modules.lazy.LazyModuleMixin method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.inlined_graph">inlined_graph() (torch.jit.ScriptModule property)</a>
</li>
      <li><a href="generated/torch.inner.html#torch.inner">inner() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.inner.html#torch.Tensor.inner">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.ModuleList.html#torch.nn.ModuleList.insert">insert() (torch.nn.ModuleList method)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.inserting_after">inserting_after() (torch.fx.Graph method)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.inserting_before">inserting_before() (torch.fx.Graph method)</a>
</li>
      <li><a href="generated/torch.nn.functional.instance_norm.html#torch.nn.functional.instance_norm">instance_norm() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.InstanceNorm1d.html#torch.nn.InstanceNorm1d">InstanceNorm1d (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.InstanceNorm1d">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.InstanceNorm2d.html#torch.nn.InstanceNorm2d">InstanceNorm2d (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.InstanceNorm2d">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.InstanceNorm3d.html#torch.nn.InstanceNorm3d">InstanceNorm3d (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.InstanceNorm3d">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.BFloat16Storage.int">int() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.int">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.int">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.int">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.int">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.int">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.int">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.int">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.int">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.int">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.int">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.int">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.int">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.int">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.int">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.int">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.int.html#torch.Tensor.int">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.int_repr.html#torch.Tensor.int_repr">int_repr() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraints.integer_interval">integer_interval (in module torch.distributions.constraints)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.intern">intern() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.interned_modules">interned_modules() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="generated/torch.nn.functional.interpolate.html#torch.nn.functional.interpolate">interpolate() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.interpolate">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Interpreter">Interpreter (class in torch.fx)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraints.interval">interval (in module torch.distributions.constraints)</a>
</li>
      <li><a href="storage.html#torch.IntStorage">IntStorage (class in torch)</a>
</li>
      <li><a href="generated/torch.linalg.inv.html#torch.linalg.inv">inv() (in module torch.linalg)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.transforms.Transform.inv">(torch.distributions.transforms.Transform property)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.linalg.inv_ex.html#torch.linalg.inv_ex">inv_ex() (in module torch.linalg)</a>
</li>
      <li><a href="generated/torch.inverse.html#torch.inverse">inverse() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.inverse.html#torch.Tensor.inverse">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.transforms.Transform.inverse_shape">inverse_shape() (torch.distributions.transforms.Transform method)</a>
</li>
      <li><a href="generated/torch.cuda.ipc_collect.html#torch.cuda.ipc_collect">ipc_collect() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.Event.html#torch.cuda.Event.ipc_handle">ipc_handle() (torch.cuda.Event method)</a>
</li>
      <li><a href="distributed.html#torch.distributed.irecv">irecv() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.fft.irfft.html#torch.fft.irfft">irfft() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.irfft2.html#torch.fft.irfft2">irfft2() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.irfftn.html#torch.fft.irfftn">irfftn() (in module torch.fft)</a>
</li>
      <li><a href="backends.html#torch.backends.cudnn.is_available">is_available() (in module torch.backends.cudnn)</a>

      <ul>
        <li><a href="backends.html#torch.backends.mkl.is_available">(in module torch.backends.mkl)</a>
</li>
        <li><a href="backends.html#torch.backends.mkldnn.is_available">(in module torch.backends.mkldnn)</a>
</li>
        <li><a href="backends.html#torch.backends.openmp.is_available">(in module torch.backends.openmp)</a>
</li>
        <li><a href="generated/torch.cuda.is_available.html#torch.cuda.is_available">(in module torch.cuda)</a>
</li>
        <li><a href="distributed.html#torch.distributed.is_available">(in module torch.distributed)</a>
</li>
      </ul></li>
      <li><a href="backends.html#torch.backends.cuda.is_built">is_built() (in module torch.backends.cuda)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandler.is_closed">is_closed() (torch.distributed.elastic.rendezvous.RendezvousHandler method)</a>
</li>
      <li><a href="generated/torch.Tensor.is_coalesced.html#torch.Tensor.is_coalesced">is_coalesced() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.is_complex.html#torch.is_complex">is_complex() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.is_complex.html#torch.Tensor.is_complex">(torch.Tensor method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.is_conj.html#torch.is_conj">is_conj() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.is_conj.html#torch.Tensor.is_conj">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.is_contiguous.html#torch.Tensor.is_contiguous">is_contiguous() (torch.Tensor method)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.is_cuda">is_cuda (torch.BFloat16Storage attribute)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.is_cuda">(torch.BoolStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.is_cuda">(torch.ByteStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.is_cuda">(torch.CharStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.is_cuda">(torch.ComplexDoubleStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.is_cuda">(torch.ComplexFloatStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.is_cuda">(torch.DoubleStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.is_cuda">(torch.FloatStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.is_cuda">(torch.HalfStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.is_cuda">(torch.IntStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.is_cuda">(torch.LongStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.is_cuda">(torch.QInt32Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.is_cuda">(torch.QInt8Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.is_cuda">(torch.QUInt4x2Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.is_cuda">(torch.QUInt8Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.is_cuda">(torch.ShortStorage attribute)</a>
</li>
        <li><a href="generated/torch.Tensor.is_cuda.html#torch.Tensor.is_cuda">(torch.Tensor attribute)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.is_cuda">is_cuda() (torch.nn.utils.rnn.PackedSequence property)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.is_enabled">is_enabled() (torch.cuda.amp.GradScaler method)</a>
</li>
      <li><a href="generated/torch.is_floating_point.html#torch.is_floating_point">is_floating_point() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.is_floating_point.html#torch.Tensor.is_floating_point">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.is_grad_enabled.html#torch.is_grad_enabled">is_grad_enabled() (in module torch)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.is_impure">is_impure() (torch.fx.Node method)</a>
</li>
      <li><a href="onnx.html#torch.onnx.is_in_onnx_export">is_in_onnx_export() (in module torch.onnx)</a>
</li>
      <li><a href="generated/torch.Tensor.is_inference.html#torch.Tensor.is_inference">is_inference() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.is_inference_mode_enabled.html#torch.is_inference_mode_enabled">is_inference_mode_enabled() (in module torch)</a>
</li>
      <li><a href="generated/torch.cuda.is_initialized.html#torch.cuda.is_initialized">is_initialized() (in module torch.cuda)</a>

      <ul>
        <li><a href="distributed.html#torch.distributed.is_initialized">(in module torch.distributed)</a>
</li>
      </ul></li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.GradBucket.is_last">is_last() (in module torch.distributed.GradBucket)</a>
</li>
      <li><a href="generated/torch.Tensor.is_leaf.html#torch.Tensor.is_leaf">is_leaf (torch.Tensor attribute)</a>
</li>
      <li><a href="fx.html#torch.fx.Tracer.is_leaf_module">is_leaf_module() (torch.fx.Tracer method)</a>
</li>
      <li><a href="generated/torch.Tensor.is_meta.html#torch.Tensor.is_meta">is_meta (torch.Tensor attribute)</a>
</li>
      <li><a href="distributed.html#torch.distributed.is_mpi_available">is_mpi_available() (in module torch.distributed)</a>
</li>
      <li><a href="distributed.html#torch.distributed.is_nccl_available">is_nccl_available() (in module torch.distributed)</a>
</li>
      <li><a href="cpp_extension.html#torch.utils.cpp_extension.is_ninja_available">is_ninja_available() (in module torch.utils.cpp_extension)</a>
</li>
      <li><a href="generated/torch.is_nonzero.html#torch.is_nonzero">is_nonzero() (in module torch)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.RRef.is_owner">is_owner() (torch.distributed.rpc.RRef method)</a>
</li>
      <li><a href="generated/torch.nn.utils.parametrize.is_parametrized.html#torch.nn.utils.parametrize.is_parametrized">is_parametrized() (in module torch.nn.utils.parametrize)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.is_pinned">is_pinned() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.is_pinned">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.is_pinned">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.is_pinned">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.is_pinned">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.is_pinned">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.is_pinned">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.is_pinned">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.is_pinned">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.is_pinned">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.is_pinned">(torch.LongStorage method)</a>
</li>
        <li><a href="generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.is_pinned">(torch.nn.utils.rnn.PackedSequence method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.is_pinned">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.is_pinned">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.is_pinned">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.is_pinned">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.is_pinned">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.is_pinned.html#torch.Tensor.is_pinned">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.utils.prune.is_pruned.html#torch.nn.utils.prune.is_pruned">is_pruned() (in module torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.Tensor.is_quantized.html#torch.Tensor.is_quantized">is_quantized (torch.Tensor attribute)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.WorkerState.is_running">is_running() (torch.distributed.elastic.agent.server.WorkerState static method)</a>
</li>
      <li><a href="jit_language_reference.html#torch.jit.is_scripting">is_scripting() (in module torch.jit)</a>
</li>
      <li><a href="generated/torch.Tensor.is_set_to.html#torch.Tensor.is_set_to">is_set_to() (torch.Tensor method)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.is_shared">is_shared() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.is_shared">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.is_shared">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.is_shared">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.is_shared">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.is_shared">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.is_shared">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.is_shared">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.is_shared">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.is_shared">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.is_shared">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.is_shared">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.is_shared">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.is_shared">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.is_shared">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.is_shared">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.is_shared.html#torch.Tensor.is_shared">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.is_signed.html#torch.Tensor.is_signed">is_signed() (torch.Tensor method)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.is_sparse">is_sparse (torch.BFloat16Storage attribute)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.is_sparse">(torch.BoolStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.is_sparse">(torch.ByteStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.is_sparse">(torch.CharStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.is_sparse">(torch.ComplexDoubleStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.is_sparse">(torch.ComplexFloatStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.is_sparse">(torch.DoubleStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.is_sparse">(torch.FloatStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.is_sparse">(torch.HalfStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.is_sparse">(torch.IntStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.is_sparse">(torch.LongStorage attribute)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.is_sparse">(torch.QInt32Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.is_sparse">(torch.QInt8Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.is_sparse">(torch.QUInt4x2Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.is_sparse">(torch.QUInt8Storage attribute)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.is_sparse">(torch.ShortStorage attribute)</a>
</li>
        <li><a href="generated/torch.Tensor.is_sparse.html#torch.Tensor.is_sparse">(torch.Tensor attribute)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.is_storage.html#torch.is_storage">is_storage() (in module torch)</a>
</li>
      <li><a href="generated/torch.is_tensor.html#torch.is_tensor">is_tensor() (in module torch)</a>
</li>
      <li><a href="torch.overrides.html#torch.overrides.is_tensor_like">is_tensor_like() (in module torch.overrides)</a>
</li>
      <li><a href="torch.overrides.html#torch.overrides.is_tensor_method_or_property">is_tensor_method_or_property() (in module torch.overrides)</a>
</li>
      <li><a href="distributed.html#torch.distributed.is_torchelastic_launched">is_torchelastic_launched() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.is_warn_always_enabled.html#torch.is_warn_always_enabled">is_warn_always_enabled() (in module torch)</a>
</li>
      <li><a href="generated/torch.isclose.html#torch.isclose">isclose() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.isclose.html#torch.Tensor.isclose">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributed.html#torch.distributed.isend">isend() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.isfinite.html#torch.isfinite">isfinite() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.isfinite.html#torch.Tensor.isfinite">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.isin.html#torch.isin">isin() (in module torch)</a>
</li>
      <li><a href="generated/torch.isinf.html#torch.isinf">isinf() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.isinf.html#torch.Tensor.isinf">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.isinstance.html#torch.jit.isinstance">isinstance() (in module torch.jit)</a>
</li>
      <li><a href="generated/torch.isnan.html#torch.isnan">isnan() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.isnan.html#torch.Tensor.isnan">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.isneginf.html#torch.isneginf">isneginf() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.isneginf.html#torch.Tensor.isneginf">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.isposinf.html#torch.isposinf">isposinf() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.isposinf.html#torch.Tensor.isposinf">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.isreal.html#torch.isreal">isreal() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.isreal.html#torch.Tensor.isreal">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.istft.html#torch.istft">istft() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.istft.html#torch.Tensor.istft">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.item.html#torch.Tensor.item">item() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.ModuleDict.html#torch.nn.ModuleDict.items">items() (torch.nn.ModuleDict method)</a>

      <ul>
        <li><a href="generated/torch.nn.ParameterDict.html#torch.nn.ParameterDict.items">(torch.nn.ParameterDict method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Tracer.iter">iter() (torch.fx.Tracer method)</a>
</li>
      <li><a href="data.html#torch.utils.data.IterableDataset">IterableDataset (class in torch.utils.data)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="J">J</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.autograd.functional.jacobian.html#torch.autograd.functional.jacobian">jacobian() (in module torch.autograd.functional)</a>
</li>
      <li><a href="distributed.algorithms.join.html#torch.distributed.algorithms.Join">Join (class in torch.distributed.algorithms)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousTimeout.join">join() (torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousTimeout property)</a>

      <ul>
        <li><a href="multiprocessing.html#torch.multiprocessing.SpawnContext.join">(torch.multiprocessing.SpawnContext method)</a>
</li>
        <li><a href="generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel.join">(torch.nn.parallel.DistributedDataParallel method)</a>
</li>
      </ul></li>
      <li><a href="distributed.algorithms.join.html#torch.distributed.algorithms.Joinable.join_device">join_device() (torch.distributed.algorithms.Joinable property)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="distributed.algorithms.join.html#torch.distributed.algorithms.Joinable.join_hook">join_hook() (torch.distributed.algorithms.Joinable method)</a>

      <ul>
        <li><a href="distributed.optim.html#torch.distributed.optim.ZeroRedundancyOptimizer.join_hook">(torch.distributed.optim.ZeroRedundancyOptimizer method)</a>
</li>
        <li><a href="generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel.join_hook">(torch.nn.parallel.DistributedDataParallel method)</a>
</li>
      </ul></li>
      <li><a href="distributed.algorithms.join.html#torch.distributed.algorithms.Joinable.join_process_group">join_process_group() (torch.distributed.algorithms.Joinable property)</a>
</li>
      <li><a href="distributed.algorithms.join.html#torch.distributed.algorithms.Joinable">Joinable (class in torch.distributed.algorithms)</a>
</li>
      <li><a href="distributed.algorithms.join.html#torch.distributed.algorithms.JoinHook">JoinHook (class in torch.distributed.algorithms)</a>
</li>
      <li><a href="generated/torch.autograd.functional.jvp.html#torch.autograd.functional.jvp">jvp() (in module torch.autograd.functional)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="K">K</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="nn.init.html#torch.nn.init.kaiming_normal_">kaiming_normal_() (in module torch.nn.init)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.kaiming_uniform_">kaiming_uniform_() (in module torch.nn.init)</a>
</li>
      <li><a href="generated/torch.kaiser_window.html#torch.kaiser_window">kaiser_window() (in module torch)</a>
</li>
      <li><a href="generated/torch.autograd.profiler.profile.key_averages.html#torch.autograd.profiler.profile.key_averages">key_averages() (torch.autograd.profiler.profile method)</a>

      <ul>
        <li><a href="profiler.html#torch.profiler.profile.key_averages">(torch.profiler.profile method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Tracer.keys">keys() (torch.fx.Tracer method)</a>

      <ul>
        <li><a href="generated/torch.nn.ModuleDict.html#torch.nn.ModuleDict.keys">(torch.nn.ModuleDict method)</a>
</li>
        <li><a href="generated/torch.nn.ParameterDict.html#torch.nn.ParameterDict.keys">(torch.nn.ParameterDict method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.nn.functional.kl_div.html#torch.nn.functional.kl_div">kl_div() (in module torch.nn.functional)</a>
</li>
      <li><a href="distributions.html#torch.distributions.kl.kl_divergence">kl_divergence() (in module torch.distributions.kl)</a>
</li>
      <li><a href="generated/torch.nn.KLDivLoss.html#torch.nn.KLDivLoss">KLDivLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.kron.html#torch.kron">kron() (in module torch)</a>
</li>
      <li><a href="generated/torch.kthvalue.html#torch.kthvalue">kthvalue() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.kthvalue.html#torch.Tensor.kthvalue">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.kumaraswamy.Kumaraswamy">Kumaraswamy (class in torch.distributions.kumaraswamy)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.kwargs">kwargs() (torch.fx.Node property)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="L">L</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.nn.functional.l1_loss.html#torch.nn.functional.l1_loss">l1_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.l1_unstructured.html#torch.nn.utils.prune.l1_unstructured">l1_unstructured() (in module torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.nn.L1Loss.html#torch.nn.L1Loss">L1Loss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.L1Unstructured.html#torch.nn.utils.prune.L1Unstructured">L1Unstructured (class in torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.LambdaLR.html#torch.optim.lr_scheduler.LambdaLR">LambdaLR (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="distributions.html#torch.distributions.laplace.Laplace">Laplace (class in torch.distributions.laplace)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousTimeout.last_call">last_call() (torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousTimeout property)</a>
</li>
      <li><a href="generated/torch.nn.functional.layer_norm.html#torch.nn.functional.layer_norm">layer_norm() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.LayerNorm.html#torch.nn.LayerNorm">LayerNorm (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.LayerNorm">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.LazyBatchNorm1d.html#torch.nn.LazyBatchNorm1d">LazyBatchNorm1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyBatchNorm2d.html#torch.nn.LazyBatchNorm2d">LazyBatchNorm2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyBatchNorm3d.html#torch.nn.LazyBatchNorm3d">LazyBatchNorm3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyConv1d.html#torch.nn.LazyConv1d">LazyConv1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyConv2d.html#torch.nn.LazyConv2d">LazyConv2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyConv3d.html#torch.nn.LazyConv3d">LazyConv3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyConvTranspose1d.html#torch.nn.LazyConvTranspose1d">LazyConvTranspose1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyConvTranspose2d.html#torch.nn.LazyConvTranspose2d">LazyConvTranspose2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyConvTranspose3d.html#torch.nn.LazyConvTranspose3d">LazyConvTranspose3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyInstanceNorm1d.html#torch.nn.LazyInstanceNorm1d">LazyInstanceNorm1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyInstanceNorm2d.html#torch.nn.LazyInstanceNorm2d">LazyInstanceNorm2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyInstanceNorm3d.html#torch.nn.LazyInstanceNorm3d">LazyInstanceNorm3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LazyLinear.html#torch.nn.LazyLinear">LazyLinear (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.modules.lazy.LazyModuleMixin.html#torch.nn.modules.lazy.LazyModuleMixin">LazyModuleMixin (class in torch.nn.modules.lazy)</a>
</li>
      <li><a href="generated/torch.optim.LBFGS.html#torch.optim.LBFGS">LBFGS (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.lcm.html#torch.lcm">lcm() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.lcm.html#torch.Tensor.lcm">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.lcm_.html#torch.Tensor.lcm_">lcm_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.ldexp.html#torch.ldexp">ldexp() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.ldexp.html#torch.Tensor.ldexp">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.ldexp_.html#torch.Tensor.ldexp_">ldexp_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.le.html#torch.le">le() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.le.html#torch.Tensor.le">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.le_.html#torch.Tensor.le_">le_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.functional.leaky_relu.html#torch.nn.functional.leaky_relu">leaky_relu() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.leaky_relu_.html#torch.nn.functional.leaky_relu_">leaky_relu_() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.LeakyReLU.html#torch.nn.LeakyReLU">LeakyReLU (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.lerp.html#torch.lerp">lerp() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.lerp.html#torch.Tensor.lerp">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.lerp_.html#torch.Tensor.lerp_">lerp_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.less.html#torch.less">less() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.less.html#torch.Tensor.less">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.less_.html#torch.Tensor.less_">less_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.less_equal.html#torch.less_equal">less_equal() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.less_equal.html#torch.Tensor.less_equal">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.less_equal_.html#torch.Tensor.less_equal_">less_equal_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraints.less_than">less_than (in module torch.distributions.constraints)</a>
</li>
      <li><a href="generated/torch.lgamma.html#torch.lgamma">lgamma() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.lgamma.html#torch.Tensor.lgamma">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.lgamma_.html#torch.Tensor.lgamma_">lgamma_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.Linear.html#torch.nn.Linear">Linear (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.qat.html#torch.nn.qat.Linear">(class in torch.nn.qat)</a>
</li>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.Linear">(class in torch.nn.quantized)</a>
</li>
        <li><a href="torch.nn.quantized.dynamic.html#torch.nn.quantized.dynamic.Linear">(class in torch.nn.quantized.dynamic)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.linear.html#torch.nn.functional.linear">linear() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.linear">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.optim.lr_scheduler.LinearLR.html#torch.optim.lr_scheduler.LinearLR">LinearLR (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="torch.nn.intrinsic.qat.html#torch.nn.intrinsic.qat.LinearReLU">LinearReLU (class in torch.nn.intrinsic.qat)</a>

      <ul>
        <li><a href="torch.nn.intrinsic.quantized.html#torch.nn.intrinsic.quantized.LinearReLU">(class in torch.nn.intrinsic.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.linspace.html#torch.linspace">linspace() (in module torch)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.lint">lint() (torch.fx.Graph method)</a>
</li>
      <li><a href="hub.html#torch.hub.list">list() (in module torch.hub)</a>
</li>
      <li><a href="generated/torch.cuda.list_gpu_processes.html#torch.cuda.list_gpu_processes">list_gpu_processes() (in module torch.cuda)</a>
</li>
      <li><a href="distributions.html#torch.distributions.lkj_cholesky.LKJCholesky">LKJCholesky (class in torch.distributions.lkj_cholesky)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.ln_structured.html#torch.nn.utils.prune.ln_structured">ln_structured() (in module torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.LnStructured.html#torch.nn.utils.prune.LnStructured">LnStructured (class in torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.load.html#torch.load">load() (in module torch)</a>

      <ul>
        <li><a href="hub.html#torch.hub.load">(in module torch.hub)</a>
</li>
        <li><a href="generated/torch.jit.load.html#torch.jit.load">(in module torch.jit)</a>
</li>
        <li><a href="cpp_extension.html#torch.utils.cpp_extension.load">(in module torch.utils.cpp_extension)</a>
</li>
      </ul></li>
      <li><a href="package.html#torch.package.PackageImporter.load_binary">load_binary() (torch.package.PackageImporter method)</a>
</li>
      <li><a href="cpp_extension.html#torch.utils.cpp_extension.load_inline">load_inline() (in module torch.utils.cpp_extension)</a>
</li>
      <li><a href="generated/torch.autograd.profiler.load_nvprof.html#torch.autograd.profiler.load_nvprof">load_nvprof() (in module torch.autograd.profiler)</a>
</li>
      <li><a href="package.html#torch.package.PackageImporter.load_pickle">load_pickle() (torch.package.PackageImporter method)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.load_state_dict">load_state_dict() (torch.cuda.amp.GradScaler method)</a>

      <ul>
        <li><a href="distributed.optim.html#torch.distributed.optim.ZeroRedundancyOptimizer.load_state_dict">(torch.distributed.optim.ZeroRedundancyOptimizer method)</a>
</li>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.load_state_dict">(torch.jit.ScriptModule method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.load_state_dict">(torch.nn.Module method)</a>
</li>
        <li><a href="generated/torch.optim.Adadelta.html#torch.optim.Adadelta.load_state_dict">(torch.optim.Adadelta method)</a>
</li>
        <li><a href="generated/torch.optim.Adagrad.html#torch.optim.Adagrad.load_state_dict">(torch.optim.Adagrad method)</a>
</li>
        <li><a href="generated/torch.optim.Adam.html#torch.optim.Adam.load_state_dict">(torch.optim.Adam method)</a>
</li>
        <li><a href="generated/torch.optim.Adamax.html#torch.optim.Adamax.load_state_dict">(torch.optim.Adamax method)</a>
</li>
        <li><a href="generated/torch.optim.AdamW.html#torch.optim.AdamW.load_state_dict">(torch.optim.AdamW method)</a>
</li>
        <li><a href="generated/torch.optim.ASGD.html#torch.optim.ASGD.load_state_dict">(torch.optim.ASGD method)</a>
</li>
        <li><a href="generated/torch.optim.LBFGS.html#torch.optim.LBFGS.load_state_dict">(torch.optim.LBFGS method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.ChainedScheduler.html#torch.optim.lr_scheduler.ChainedScheduler.load_state_dict">(torch.optim.lr_scheduler.ChainedScheduler method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.ConstantLR.html#torch.optim.lr_scheduler.ConstantLR.load_state_dict">(torch.optim.lr_scheduler.ConstantLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingLR.html#torch.optim.lr_scheduler.CosineAnnealingLR.load_state_dict">(torch.optim.lr_scheduler.CosineAnnealingLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.html#torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.load_state_dict">(torch.optim.lr_scheduler.CosineAnnealingWarmRestarts method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CyclicLR.html#torch.optim.lr_scheduler.CyclicLR.load_state_dict">(torch.optim.lr_scheduler.CyclicLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.ExponentialLR.html#torch.optim.lr_scheduler.ExponentialLR.load_state_dict">(torch.optim.lr_scheduler.ExponentialLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.LambdaLR.html#torch.optim.lr_scheduler.LambdaLR.load_state_dict">(torch.optim.lr_scheduler.LambdaLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.LinearLR.html#torch.optim.lr_scheduler.LinearLR.load_state_dict">(torch.optim.lr_scheduler.LinearLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.MultiplicativeLR.html#torch.optim.lr_scheduler.MultiplicativeLR.load_state_dict">(torch.optim.lr_scheduler.MultiplicativeLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.MultiStepLR.html#torch.optim.lr_scheduler.MultiStepLR.load_state_dict">(torch.optim.lr_scheduler.MultiStepLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.OneCycleLR.html#torch.optim.lr_scheduler.OneCycleLR.load_state_dict">(torch.optim.lr_scheduler.OneCycleLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.SequentialLR.html#torch.optim.lr_scheduler.SequentialLR.load_state_dict">(torch.optim.lr_scheduler.SequentialLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.StepLR.html#torch.optim.lr_scheduler.StepLR.load_state_dict">(torch.optim.lr_scheduler.StepLR method)</a>
</li>
        <li><a href="generated/torch.optim.NAdam.html#torch.optim.NAdam.load_state_dict">(torch.optim.NAdam method)</a>
</li>
        <li><a href="generated/torch.optim.Optimizer.load_state_dict.html#torch.optim.Optimizer.load_state_dict">(torch.optim.Optimizer method)</a>
</li>
        <li><a href="generated/torch.optim.RAdam.html#torch.optim.RAdam.load_state_dict">(torch.optim.RAdam method)</a>
</li>
        <li><a href="generated/torch.optim.RMSprop.html#torch.optim.RMSprop.load_state_dict">(torch.optim.RMSprop method)</a>
</li>
        <li><a href="generated/torch.optim.Rprop.html#torch.optim.Rprop.load_state_dict">(torch.optim.Rprop method)</a>
</li>
        <li><a href="generated/torch.optim.SGD.html#torch.optim.SGD.load_state_dict">(torch.optim.SGD method)</a>
</li>
        <li><a href="generated/torch.optim.SparseAdam.html#torch.optim.SparseAdam.load_state_dict">(torch.optim.SparseAdam method)</a>
</li>
      </ul></li>
      <li><a href="hub.html#torch.hub.load_state_dict_from_url">load_state_dict_from_url() (in module torch.hub)</a>
</li>
      <li><a href="package.html#torch.package.PackageImporter.load_text">load_text() (torch.package.PackageImporter method)</a>
</li>
      <li><a href="model_zoo.html#torch.utils.model_zoo.load_url">load_url() (in module torch.utils.model_zoo)</a>
</li>
      <li><a href="generated/torch.lobpcg.html#torch.lobpcg">lobpcg() (in module torch)</a>
</li>
      <li><a href="distributions.html#torch.distributions.log_normal.LogNormal.loc">loc() (torch.distributions.log_normal.LogNormal property)</a>
</li>
      <li><a href="generated/torch.nn.functional.local_response_norm.html#torch.nn.functional.local_response_norm">local_response_norm() (in module torch.nn.functional)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.RRef.local_value">local_value() (torch.distributed.rpc.RRef method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.local_elastic_agent.LocalElasticAgent">LocalElasticAgent (class in torch.distributed.elastic.agent.server.local_elastic_agent)</a>
</li>
      <li><a href="generated/torch.nn.LocalResponseNorm.html#torch.nn.LocalResponseNorm">LocalResponseNorm (class in torch.nn)</a>
</li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.LocalTimerClient">LocalTimerClient (class in torch.distributed.elastic.timer)</a>
</li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.LocalTimerServer">LocalTimerServer (class in torch.distributed.elastic.timer)</a>
</li>
      <li><a href="generated/torch.log.html#torch.log">log() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.log.html#torch.Tensor.log">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.log10.html#torch.log10">log10() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.log10.html#torch.Tensor.log10">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.log10_.html#torch.Tensor.log10_">log10_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.log1p.html#torch.log1p">log1p() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.log1p">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.log1p.html#torch.Tensor.log1p">(torch.Tensor method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.Tensor.log1p_.html#torch.Tensor.log1p_">log1p_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.log2.html#torch.log2">log2() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.log2.html#torch.Tensor.log2">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.log2_.html#torch.Tensor.log2_">log2_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.log_.html#torch.Tensor.log_">log_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.Transform.log_abs_det_jacobian">log_abs_det_jacobian() (torch.distributions.transforms.Transform method)</a>
</li>
      <li><a href="generated/torch.Tensor.log_normal_.html#torch.Tensor.log_normal_">log_normal_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.log_prob">log_prob() (torch.distributions.bernoulli.Bernoulli method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.beta.Beta.log_prob">(torch.distributions.beta.Beta method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.log_prob">(torch.distributions.binomial.Binomial method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.log_prob">(torch.distributions.categorical.Categorical method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.log_prob">(torch.distributions.cauchy.Cauchy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.log_prob">(torch.distributions.continuous_bernoulli.ContinuousBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet.log_prob">(torch.distributions.dirichlet.Dirichlet method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.log_prob">(torch.distributions.distribution.Distribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.log_prob">(torch.distributions.exponential.Exponential method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.fishersnedecor.FisherSnedecor.log_prob">(torch.distributions.fishersnedecor.FisherSnedecor method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gamma.Gamma.log_prob">(torch.distributions.gamma.Gamma method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.geometric.Geometric.log_prob">(torch.distributions.geometric.Geometric method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gumbel.Gumbel.log_prob">(torch.distributions.gumbel.Gumbel method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.log_prob">(torch.distributions.half_cauchy.HalfCauchy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.log_prob">(torch.distributions.half_normal.HalfNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.independent.Independent.log_prob">(torch.distributions.independent.Independent method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.log_prob">(torch.distributions.laplace.Laplace method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lkj_cholesky.LKJCholesky.log_prob">(torch.distributions.lkj_cholesky.LKJCholesky method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.log_prob">(torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.log_prob">(torch.distributions.mixture_same_family.MixtureSameFamily method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.log_prob">(torch.distributions.multinomial.Multinomial method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.log_prob">(torch.distributions.multivariate_normal.MultivariateNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.log_prob">(torch.distributions.negative_binomial.NegativeBinomial method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.log_prob">(torch.distributions.normal.Normal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.log_prob">(torch.distributions.one_hot_categorical.OneHotCategorical method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.poisson.Poisson.log_prob">(torch.distributions.poisson.Poisson method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli.log_prob">(torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.studentT.StudentT.log_prob">(torch.distributions.studentT.StudentT method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.log_prob">(torch.distributions.transformed_distribution.TransformedDistribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.log_prob">(torch.distributions.uniform.Uniform method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.von_mises.VonMises.log_prob">(torch.distributions.von_mises.VonMises method)</a>
</li>
        <li><a href="generated/torch.nn.AdaptiveLogSoftmaxWithLoss.html#torch.nn.AdaptiveLogSoftmaxWithLoss.log_prob">(torch.nn.AdaptiveLogSoftmaxWithLoss method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.log_softmax.html#torch.nn.functional.log_softmax">log_softmax() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="generated/torch.sparse.log_softmax.html#torch.sparse.log_softmax">(in module torch.sparse)</a>
</li>
        <li><a href="special.html#torch.special.log_softmax">(in module torch.special)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.logaddexp.html#torch.logaddexp">logaddexp() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.logaddexp.html#torch.Tensor.logaddexp">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.logaddexp2.html#torch.logaddexp2">logaddexp2() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.logaddexp2.html#torch.Tensor.logaddexp2">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.logcumsumexp.html#torch.logcumsumexp">logcumsumexp() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.logcumsumexp.html#torch.Tensor.logcumsumexp">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.logdet.html#torch.logdet">logdet() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.logdet.html#torch.Tensor.logdet">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.logical_and.html#torch.logical_and">logical_and() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.logical_and.html#torch.Tensor.logical_and">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.logical_and_.html#torch.Tensor.logical_and_">logical_and_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.logical_not.html#torch.logical_not">logical_not() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.logical_not.html#torch.Tensor.logical_not">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.logical_not_.html#torch.Tensor.logical_not_">logical_not_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.logical_or.html#torch.logical_or">logical_or() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.logical_or.html#torch.Tensor.logical_or">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.logical_or_.html#torch.Tensor.logical_or_">logical_or_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.logical_xor.html#torch.logical_xor">logical_xor() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.logical_xor.html#torch.Tensor.logical_xor">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.logical_xor_.html#torch.Tensor.logical_xor_">logical_xor_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.logit.html#torch.logit">logit() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.logit">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.logit.html#torch.Tensor.logit">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.logit_.html#torch.Tensor.logit_">logit_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli">LogitRelaxedBernoulli (class in torch.distributions.relaxed_bernoulli)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.logits">logits() (torch.distributions.bernoulli.Bernoulli property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.logits">(torch.distributions.binomial.Binomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.logits">(torch.distributions.categorical.Categorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.logits">(torch.distributions.continuous_bernoulli.ContinuousBernoulli property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.geometric.Geometric.logits">(torch.distributions.geometric.Geometric property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.logits">(torch.distributions.multinomial.Multinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.logits">(torch.distributions.negative_binomial.NegativeBinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.logits">(torch.distributions.one_hot_categorical.OneHotCategorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli.logits">(torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.RelaxedBernoulli.logits">(torch.distributions.relaxed_bernoulli.RelaxedBernoulli property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_categorical.RelaxedOneHotCategorical.logits">(torch.distributions.relaxed_categorical.RelaxedOneHotCategorical property)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.log_normal.LogNormal">LogNormal (class in torch.distributions.log_normal)</a>
</li>
      <li><a href="generated/torch.nn.LogSigmoid.html#torch.nn.LogSigmoid">LogSigmoid (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.logsigmoid.html#torch.nn.functional.logsigmoid">logsigmoid() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.LogSoftmax.html#torch.nn.LogSoftmax">LogSoftmax (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.logspace.html#torch.logspace">logspace() (in module torch)</a>
</li>
      <li><a href="generated/torch.logsumexp.html#torch.logsumexp">logsumexp() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.logsumexp">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.logsumexp.html#torch.Tensor.logsumexp">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.BFloat16Storage.long">long() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.long">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.long">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.long">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.long">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.long">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.long">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.long">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.long">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.long">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.long">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.long">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.long">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.long">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.long">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.long">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.long.html#torch.Tensor.long">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.LongStorage">LongStorage (class in torch)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.LowerCholeskyTransform">LowerCholeskyTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal">LowRankMultivariateNormal (class in torch.distributions.lowrank_multivariate_normal)</a>
</li>
      <li><a href="generated/torch.nn.functional.lp_pool1d.html#torch.nn.functional.lp_pool1d">lp_pool1d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.lp_pool2d.html#torch.nn.functional.lp_pool2d">lp_pool2d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.LPPool1d.html#torch.nn.LPPool1d">LPPool1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LPPool2d.html#torch.nn.LPPool2d">LPPool2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.LSTM.html#torch.nn.LSTM">LSTM (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.dynamic.html#torch.nn.quantized.dynamic.LSTM">(class in torch.nn.quantized.dynamic)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.LSTMCell.html#torch.nn.LSTMCell">LSTMCell (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.dynamic.html#torch.nn.quantized.dynamic.LSTMCell">(class in torch.nn.quantized.dynamic)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.lstsq.html#torch.lstsq">lstsq() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.lstsq.html#torch.linalg.lstsq">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.lstsq.html#torch.Tensor.lstsq">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.lt.html#torch.lt">lt() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.lt.html#torch.Tensor.lt">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.lt_.html#torch.Tensor.lt_">lt_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.lu.html#torch.lu">lu() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.lu.html#torch.Tensor.lu">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.lu_solve.html#torch.lu_solve">lu_solve() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.lu_solve.html#torch.Tensor.lu_solve">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.lu_unpack.html#torch.lu_unpack">lu_unpack() (in module torch)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="M">M</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="distributed.algorithms.join.html#torch.distributed.algorithms.JoinHook.main_hook">main_hook() (torch.distributed.algorithms.JoinHook method)</a>
</li>
      <li><a href="generated/torch.cuda.make_graphed_callables.html#torch.cuda.make_graphed_callables">make_graphed_callables() (in module torch.cuda)</a>
</li>
      <li><a href="testing.html#torch.testing.make_tensor">make_tensor() (in module torch.testing)</a>
</li>
      <li><a href="generated/torch.manual_seed.html#torch.manual_seed">manual_seed() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.cuda.manual_seed.html#torch.cuda.manual_seed">(in module torch.cuda)</a>
</li>
        <li><a href="random.html#torch.random.manual_seed">(in module torch.random)</a>
</li>
        <li><a href="generated/torch.Generator.html#torch.Generator.manual_seed">(torch.Generator method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.manual_seed_all.html#torch.cuda.manual_seed_all">manual_seed_all() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.Tensor.map_.html#torch.Tensor.map_">map_() (torch.Tensor method)</a>
</li>
      <li><a href="fx.html#torch.fx.Interpreter.map_nodes_to_values">map_nodes_to_values() (torch.fx.Interpreter method)</a>
</li>
      <li><a href="generated/torch.nn.functional.margin_ranking_loss.html#torch.nn.functional.margin_ranking_loss">margin_ranking_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.MarginRankingLoss.html#torch.nn.MarginRankingLoss">MarginRankingLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.cuda.nvtx.mark.html#torch.cuda.nvtx.mark">mark() (in module torch.cuda.nvtx)</a>
</li>
      <li><a href="generated/torch.autograd.function.FunctionCtx.mark_dirty.html#torch.autograd.function.FunctionCtx.mark_dirty">mark_dirty() (torch.autograd.function.FunctionCtx method)</a>
</li>
      <li><a href="generated/torch.autograd.function.FunctionCtx.mark_non_differentiable.html#torch.autograd.function.FunctionCtx.mark_non_differentiable">mark_non_differentiable() (torch.autograd.function.FunctionCtx method)</a>
</li>
      <li><a href="generated/torch.Tensor.masked_fill.html#torch.Tensor.masked_fill">masked_fill() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.masked_fill_.html#torch.Tensor.masked_fill_">masked_fill_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.masked_scatter.html#torch.Tensor.masked_scatter">masked_scatter() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.masked_scatter_.html#torch.Tensor.masked_scatter_">masked_scatter_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.masked_select.html#torch.masked_select">masked_select() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.masked_select.html#torch.Tensor.masked_select">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.matmul.html#torch.matmul">matmul() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.matmul.html#torch.linalg.matmul">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.matmul.html#torch.Tensor.matmul">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.matrix_exp.html#torch.matrix_exp">matrix_exp() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.matrix_exp.html#torch.Tensor.matrix_exp">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.linalg.matrix_norm.html#torch.linalg.matrix_norm">matrix_norm() (in module torch.linalg)</a>
</li>
      <li><a href="generated/torch.matrix_power.html#torch.matrix_power">matrix_power() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.matrix_power.html#torch.linalg.matrix_power">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.matrix_power.html#torch.Tensor.matrix_power">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.matrix_rank.html#torch.matrix_rank">matrix_rank() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.matrix_rank.html#torch.linalg.matrix_rank">(in module torch.linalg)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.max.html#torch.max">max() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.max.html#torch.Tensor.max">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.max_memory_allocated.html#torch.cuda.max_memory_allocated">max_memory_allocated() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.max_memory_cached.html#torch.cuda.max_memory_cached">max_memory_cached() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.max_memory_reserved.html#torch.cuda.max_memory_reserved">max_memory_reserved() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.nn.functional.max_pool1d.html#torch.nn.functional.max_pool1d">max_pool1d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.max_pool2d.html#torch.nn.functional.max_pool2d">max_pool2d() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.max_pool2d">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.max_pool3d.html#torch.nn.functional.max_pool3d">max_pool3d() (in module torch.nn.functional)</a>
</li>
      <li><a href="backends.html#max_size">max_size</a>
</li>
      <li><a href="generated/torch.nn.functional.max_unpool1d.html#torch.nn.functional.max_unpool1d">max_unpool1d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.max_unpool2d.html#torch.nn.functional.max_unpool2d">max_unpool2d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.max_unpool3d.html#torch.nn.functional.max_unpool3d">max_unpool3d() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.maximum.html#torch.maximum">maximum() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.maximum.html#torch.Tensor.maximum">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.MaxPool1d.html#torch.nn.MaxPool1d">MaxPool1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.MaxPool2d.html#torch.nn.MaxPool2d">MaxPool2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.MaxPool3d.html#torch.nn.MaxPool3d">MaxPool3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.MaxUnpool1d.html#torch.nn.MaxUnpool1d">MaxUnpool1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.MaxUnpool2d.html#torch.nn.MaxUnpool2d">MaxUnpool2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.MaxUnpool3d.html#torch.nn.MaxUnpool3d">MaxUnpool3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.mean.html#torch.mean">mean() (in module torch)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.mean">(torch.distributions.bernoulli.Bernoulli property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.beta.Beta.mean">(torch.distributions.beta.Beta property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.mean">(torch.distributions.binomial.Binomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.mean">(torch.distributions.categorical.Categorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.mean">(torch.distributions.cauchy.Cauchy property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.mean">(torch.distributions.continuous_bernoulli.ContinuousBernoulli property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet.mean">(torch.distributions.dirichlet.Dirichlet property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.mean">(torch.distributions.distribution.Distribution property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.mean">(torch.distributions.exponential.Exponential property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.fishersnedecor.FisherSnedecor.mean">(torch.distributions.fishersnedecor.FisherSnedecor property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gamma.Gamma.mean">(torch.distributions.gamma.Gamma property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.geometric.Geometric.mean">(torch.distributions.geometric.Geometric property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gumbel.Gumbel.mean">(torch.distributions.gumbel.Gumbel property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.mean">(torch.distributions.half_cauchy.HalfCauchy property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.mean">(torch.distributions.half_normal.HalfNormal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.independent.Independent.mean">(torch.distributions.independent.Independent property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.kumaraswamy.Kumaraswamy.mean">(torch.distributions.kumaraswamy.Kumaraswamy property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.mean">(torch.distributions.laplace.Laplace property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.log_normal.LogNormal.mean">(torch.distributions.log_normal.LogNormal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.mean">(torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.mean">(torch.distributions.mixture_same_family.MixtureSameFamily property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.mean">(torch.distributions.multinomial.Multinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.mean">(torch.distributions.multivariate_normal.MultivariateNormal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.mean">(torch.distributions.negative_binomial.NegativeBinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.mean">(torch.distributions.normal.Normal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.mean">(torch.distributions.one_hot_categorical.OneHotCategorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.pareto.Pareto.mean">(torch.distributions.pareto.Pareto property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.poisson.Poisson.mean">(torch.distributions.poisson.Poisson property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.studentT.StudentT.mean">(torch.distributions.studentT.StudentT property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.mean">(torch.distributions.uniform.Uniform property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.von_mises.VonMises.mean">(torch.distributions.von_mises.VonMises property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.weibull.Weibull.mean">(torch.distributions.weibull.Weibull property)</a>
</li>
        <li><a href="generated/torch.Tensor.mean.html#torch.Tensor.mean">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.Measurement">Measurement (class in torch.utils.benchmark)</a>
</li>
      <li><a href="generated/torch.median.html#torch.median">median() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.median.html#torch.Tensor.median">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.memory_allocated.html#torch.cuda.memory_allocated">memory_allocated() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.memory_cached.html#torch.cuda.memory_cached">memory_cached() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.memory_reserved.html#torch.cuda.memory_reserved">memory_reserved() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.memory_snapshot.html#torch.cuda.memory_snapshot">memory_snapshot() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.memory_stats.html#torch.cuda.memory_stats">memory_stats() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.memory_summary.html#torch.cuda.memory_summary">memory_summary() (in module torch.cuda)</a>
</li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.Measurement.merge">merge() (torch.utils.benchmark.Measurement static method)</a>
</li>
      <li><a href="generated/torch.meshgrid.html#torch.meshgrid">meshgrid() (in module torch)</a>
</li>
      <li><a href="elastic/metrics.html#torch.distributed.elastic.metrics.api.MetricHandler">MetricHandler (class in torch.distributed.elastic.metrics.api)</a>
</li>
      <li><a href="generated/torch.min.html#torch.min">min() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.min.html#torch.Tensor.min">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.minimum.html#torch.minimum">minimum() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.minimum.html#torch.Tensor.minimum">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="torch.quantization.html#torch.quantization.MinMaxObserver">MinMaxObserver (class in torch.quantization)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.nn.Mish.html#torch.nn.Mish">Mish (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.mish.html#torch.nn.functional.mish">mish() (in module torch.nn.functional)</a>
</li>
      <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.mixture_distribution">mixture_distribution() (torch.distributions.mixture_same_family.MixtureSameFamily property)</a>
</li>
      <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily">MixtureSameFamily (class in torch.distributions.mixture_same_family)</a>
</li>
      <li><a href="generated/torch.mm.html#torch.mm">mm() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.sparse.mm.html#torch.sparse.mm">(in module torch.sparse)</a>
</li>
        <li><a href="generated/torch.Tensor.mm.html#torch.Tensor.mm">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="package.html#torch.package.PackageExporter.mock">mock() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.mocked_modules">mocked_modules() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="generated/torch.mode.html#torch.mode">mode() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.mode.html#torch.Tensor.mode">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li>
    module

      <ul>
        <li><a href="__config__.html#module-torch.__config__">torch.__config__</a>
</li>
        <li><a href="autograd.html#module-torch.autograd">torch.autograd</a>
</li>
        <li><a href="cuda.html#module-torch.cuda">torch.cuda</a>
</li>
        <li><a href="amp.html#module-torch.cuda.amp">torch.cuda.amp</a>
</li>
        <li><a href="distributed.html#module-torch.distributed">torch.distributed</a>
</li>
        <li><a href="rpc.html#module-torch.distributed.autograd">torch.distributed.autograd</a>
</li>
        <li><a href="elastic/agent.html#module-torch.distributed.elastic.agent">torch.distributed.elastic.agent</a>
</li>
        <li><a href="elastic/agent.html#module-torch.distributed.elastic.agent.server">torch.distributed.elastic.agent.server</a>
</li>
        <li><a href="elastic/events.html#module-torch.distributed.elastic.events">torch.distributed.elastic.events</a>
</li>
        <li><a href="elastic/metrics.html#module-torch.distributed.elastic.metrics">torch.distributed.elastic.metrics</a>
</li>
        <li><a href="elastic/multiprocessing.html#module-torch.distributed.elastic.multiprocessing">torch.distributed.elastic.multiprocessing</a>
</li>
        <li><a href="elastic/errors.html#module-torch.distributed.elastic.multiprocessing.errors">torch.distributed.elastic.multiprocessing.errors</a>
</li>
        <li><a href="elastic/rendezvous.html#module-torch.distributed.elastic.rendezvous">torch.distributed.elastic.rendezvous</a>
</li>
        <li><a href="elastic/rendezvous.html#module-torch.distributed.elastic.rendezvous.registry">torch.distributed.elastic.rendezvous.registry</a>
</li>
        <li><a href="elastic/timer.html#module-torch.distributed.elastic.timer">torch.distributed.elastic.timer</a>
</li>
        <li><a href="distributed.html#module-torch.distributed.launch">torch.distributed.launch</a>
</li>
        <li><a href="rpc.html#module-torch.distributed.optim">torch.distributed.optim</a>
</li>
        <li><a href="rpc.html#module-torch.distributed.rpc">torch.distributed.rpc</a>
</li>
        <li><a href="elastic/run.html#module-torch.distributed.run">torch.distributed.run</a>
</li>
        <li><a href="distributions.html#module-torch.distributions">torch.distributions</a>
</li>
        <li><a href="distributions.html#module-torch.distributions.constraint_registry">torch.distributions.constraint_registry</a>
</li>
        <li><a href="distributions.html#module-torch.distributions.constraints">torch.distributions.constraints</a>
</li>
        <li><a href="distributions.html#module-torch.distributions.kl">torch.distributions.kl</a>
</li>
        <li><a href="distributions.html#module-torch.distributions.transforms">torch.distributions.transforms</a>
</li>
        <li><a href="futures.html#module-torch.futures">torch.futures</a>
</li>
        <li><a href="fx.html#module-torch.fx">torch.fx</a>
</li>
        <li><a href="hub.html#module-torch.hub">torch.hub</a>
</li>
        <li><a href="jit.html#module-torch.jit">torch.jit</a>
</li>
        <li><a href="jit_builtin_functions.html#module-torch.jit.supported_ops">torch.jit.supported_ops</a>
</li>
        <li><a href="jit_unsupported.html#module-torch.jit.unsupported_tensor_ops">torch.jit.unsupported_tensor_ops</a>
</li>
        <li><a href="linalg.html#module-torch.linalg">torch.linalg</a>
</li>
        <li><a href="multiprocessing.html#module-torch.multiprocessing">torch.multiprocessing</a>
</li>
        <li><a href="torch.nn.intrinsic.html#module-torch.nn.intrinsic">torch.nn.intrinsic</a>
</li>
        <li><a href="torch.nn.intrinsic.qat.html#module-torch.nn.intrinsic.qat">torch.nn.intrinsic.qat</a>
</li>
        <li><a href="torch.nn.intrinsic.quantized.html#module-torch.nn.intrinsic.quantized">torch.nn.intrinsic.quantized</a>
</li>
        <li><a href="torch.nn.qat.html#module-torch.nn.qat">torch.nn.qat</a>
</li>
        <li><a href="torch.nn.quantized.html#module-torch.nn.quantized">torch.nn.quantized</a>
</li>
        <li><a href="torch.nn.quantized.dynamic.html#module-torch.nn.quantized.dynamic">torch.nn.quantized.dynamic</a>
</li>
        <li><a href="torch.nn.quantized.html#module-torch.nn.quantized.functional">torch.nn.quantized.functional</a>
</li>
        <li><a href="onnx.html#module-torch.onnx">torch.onnx</a>
</li>
        <li><a href="optim.html#module-torch.optim">torch.optim</a>
</li>
        <li><a href="profiler.html#module-torch.profiler">torch.profiler</a>
</li>
        <li><a href="torch.quantization.html#module-torch.quantization">torch.quantization</a>
</li>
        <li><a href="random.html#module-torch.random">torch.random</a>
</li>
        <li><a href="testing.html#module-torch.testing">torch.testing</a>
</li>
        <li><a href="benchmark_utils.html#module-torch.utils.benchmark">torch.utils.benchmark</a>
</li>
        <li><a href="data.html#module-torch.utils.data">torch.utils.data</a>
</li>
        <li><a href="model_zoo.html#module-torch.utils.model_zoo">torch.utils.model_zoo</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.Module.html#torch.nn.Module">Module (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ModuleDict.html#torch.nn.ModuleDict">ModuleDict (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ModuleList.html#torch.nn.ModuleList">ModuleList (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.modules">modules() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.modules">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="distributed.html#torch.distributed.monitored_barrier">monitored_barrier() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.moveaxis.html#torch.moveaxis">moveaxis() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.moveaxis.html#torch.Tensor.moveaxis">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.movedim.html#torch.movedim">movedim() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.movedim.html#torch.Tensor.movedim">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="torch.quantization.html#torch.quantization.MovingAverageMinMaxObserver">MovingAverageMinMaxObserver (class in torch.quantization)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.MovingAveragePerChannelMinMaxObserver">MovingAveragePerChannelMinMaxObserver (class in torch.quantization)</a>
</li>
      <li><a href="generated/torch.nn.functional.mse_loss.html#torch.nn.functional.mse_loss">mse_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.MSELoss.html#torch.nn.MSELoss">MSELoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.msort.html#torch.msort">msort() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.msort.html#torch.Tensor.msort">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.mul.html#torch.mul">mul() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.mul.html#torch.Tensor.mul">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.mul_.html#torch.Tensor.mul_">mul_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.linalg.multi_dot.html#torch.linalg.multi_dot">multi_dot() (in module torch.linalg)</a>
</li>
      <li><a href="generated/torch.nn.functional.multi_margin_loss.html#torch.nn.functional.multi_margin_loss">multi_margin_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="special.html#torch.special.multigammaln">multigammaln() (in module torch.special)</a>
</li>
      <li><a href="generated/torch.nn.MultiheadAttention.html#torch.nn.MultiheadAttention">MultiheadAttention (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.multilabel_margin_loss.html#torch.nn.functional.multilabel_margin_loss">multilabel_margin_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.multilabel_soft_margin_loss.html#torch.nn.functional.multilabel_soft_margin_loss">multilabel_soft_margin_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.MultiLabelMarginLoss.html#torch.nn.MultiLabelMarginLoss">MultiLabelMarginLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.MultiLabelSoftMarginLoss.html#torch.nn.MultiLabelSoftMarginLoss">MultiLabelSoftMarginLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.MultiMarginLoss.html#torch.nn.MultiMarginLoss">MultiMarginLoss (class in torch.nn)</a>
</li>
      <li><a href="distributions.html#torch.distributions.multinomial.Multinomial">Multinomial (class in torch.distributions.multinomial)</a>
</li>
      <li><a href="distributions.html#torch.distributions.constraints.multinomial">multinomial (in module torch.distributions.constraints)</a>
</li>
      <li><a href="generated/torch.multinomial.html#torch.multinomial">multinomial() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.multinomial.html#torch.Tensor.multinomial">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.optim.lr_scheduler.MultiplicativeLR.html#torch.optim.lr_scheduler.MultiplicativeLR">MultiplicativeLR (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="generated/torch.multiply.html#torch.multiply">multiply() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.multiply.html#torch.Tensor.multiply">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.multiply_.html#torch.Tensor.multiply_">multiply_() (torch.Tensor method)</a>
</li>
      <li><a href="elastic/multiprocessing.html#torch.distributed.elastic.multiprocessing.api.MultiprocessContext">MultiprocessContext (class in torch.distributed.elastic.multiprocessing.api)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.MultiStepLR.html#torch.optim.lr_scheduler.MultiStepLR">MultiStepLR (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal">MultivariateNormal (class in torch.distributions.multivariate_normal)</a>
</li>
      <li><a href="generated/torch.mv.html#torch.mv">mv() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.mv.html#torch.Tensor.mv">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.mvlgamma.html#torch.mvlgamma">mvlgamma() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.mvlgamma.html#torch.Tensor.mvlgamma">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.mvlgamma_.html#torch.Tensor.mvlgamma_">mvlgamma_() (torch.Tensor method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="N">N</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.optim.NAdam.html#torch.optim.NAdam">NAdam (class in torch.optim)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.c10d_rendezvous_backend.C10dRendezvousBackend.name">name() (torch.distributed.elastic.rendezvous.c10d_rendezvous_backend.C10dRendezvousBackend property)</a>

      <ul>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousBackend.name">(torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousBackend property)</a>
</li>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_rendezvous_backend.EtcdRendezvousBackend.name">(torch.distributed.elastic.rendezvous.etcd_rendezvous_backend.EtcdRendezvousBackend property)</a>
</li>
        <li><a href="rpc.html#torch.distributed.rpc.WorkerInfo.name">(torch.distributed.rpc.WorkerInfo property)</a>
</li>
        <li><a href="profiler.html#torch.profiler.ProfilerActivity.name">(torch.profiler.ProfilerActivity property)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.named_buffers">named_buffers() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.named_buffers">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.named_children">named_children() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.named_children">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.named_modules">named_modules() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.named_modules">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.named_parameters">named_parameters() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.named_parameters">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="named_tensor.html#torch.Tensor.names">names (torch.Tensor attribute)</a>
</li>
      <li><a href="generated/torch.nan_to_num.html#torch.nan_to_num">nan_to_num() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.nan_to_num.html#torch.Tensor.nan_to_num">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.nan_to_num_.html#torch.Tensor.nan_to_num_">nan_to_num_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nanmean.html#torch.nanmean">nanmean() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.nanmean.html#torch.Tensor.nanmean">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nanmedian.html#torch.nanmedian">nanmedian() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.nanmedian.html#torch.Tensor.nanmedian">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nanquantile.html#torch.nanquantile">nanquantile() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.nanquantile.html#torch.Tensor.nanquantile">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nansum.html#torch.nansum">nansum() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.nansum.html#torch.Tensor.nansum">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.narrow.html#torch.narrow">narrow() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.narrow.html#torch.Tensor.narrow">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.narrow_copy.html#torch.Tensor.narrow_copy">narrow_copy() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.ndim.html#torch.Tensor.ndim">ndim (torch.Tensor attribute)</a>
</li>
      <li><a href="generated/torch.Tensor.ndimension.html#torch.Tensor.ndimension">ndimension() (torch.Tensor method)</a>
</li>
      <li><a href="special.html#torch.special.ndtr">ndtr() (in module torch.special)</a>
</li>
      <li><a href="special.html#torch.special.ndtri">ndtri() (in module torch.special)</a>
</li>
      <li><a href="generated/torch.ne.html#torch.ne">ne() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.ne.html#torch.Tensor.ne">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.ne_.html#torch.Tensor.ne_">ne_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.neg.html#torch.neg">neg() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.neg.html#torch.Tensor.neg">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.neg_.html#torch.Tensor.neg_">neg_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.negative.html#torch.negative">negative() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.negative.html#torch.Tensor.negative">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.negative_.html#torch.Tensor.negative_">negative_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial">NegativeBinomial (class in torch.distributions.negative_binomial)</a>
</li>
      <li><a href="generated/torch.Tensor.nelement.html#torch.Tensor.nelement">nelement() (torch.Tensor method)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.new">new() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.new">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.new">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.new">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.new">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.new">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.new">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.new">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.new">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.new">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.new">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.new">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.new">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.new">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.new">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.new">(torch.ShortStorage method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.Tensor.new_empty.html#torch.Tensor.new_empty">new_empty() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.new_full.html#torch.Tensor.new_full">new_full() (torch.Tensor method)</a>
</li>
      <li><a href="distributed.html#torch.distributed.new_group">new_group() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.Tensor.new_ones.html#torch.Tensor.new_ones">new_ones() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.new_tensor.html#torch.Tensor.new_tensor">new_tensor() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.new_zeros.html#torch.Tensor.new_zeros">new_zeros() (torch.Tensor method)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.next">next() (torch.fx.Node property)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandler.next_rendezvous">next_rendezvous() (torch.distributed.elastic.rendezvous.RendezvousHandler method)</a>
</li>
      <li><a href="generated/torch.nextafter.html#torch.nextafter">nextafter() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.nextafter.html#torch.Tensor.nextafter">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.nextafter_.html#torch.Tensor.nextafter_">nextafter_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.functional.nll_loss.html#torch.nn.functional.nll_loss">nll_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.NLLLoss.html#torch.nn.NLLLoss">NLLLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.no_grad.html#torch.no_grad">no_grad (class in torch)</a>

      <ul>
        <li><a href="generated/torch.autograd.no_grad.html#torch.autograd.no_grad">(class in torch.autograd)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel.no_sync">no_sync() (torch.nn.parallel.DistributedDataParallel method)</a>
</li>
      <li><a href="fx.html#torch.fx.Node">Node (class in torch.fx)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.node_copy">node_copy() (torch.fx.Graph method)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.nodes">nodes() (torch.fx.Graph property)</a>
</li>
      <li><a href="generated/torch.nonzero.html#torch.nonzero">nonzero() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.nonzero.html#torch.Tensor.nonzero">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.algorithms.ddp_comm_hooks.debugging_hooks.noop_hook">noop_hook() (in module torch.distributed.algorithms.ddp_comm_hooks.debugging_hooks)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.NoopObserver">NoopObserver (class in torch.quantization)</a>
</li>
      <li><a href="generated/torch.norm.html#torch.norm">norm() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.norm.html#torch.linalg.norm">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.norm.html#torch.Tensor.norm">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.normal.Normal">Normal (class in torch.distributions.normal)</a>
</li>
      <li><a href="generated/torch.normal.html#torch.normal">normal() (in module torch)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.normal_">normal_() (in module torch.nn.init)</a>

      <ul>
        <li><a href="generated/torch.Tensor.normal_.html#torch.Tensor.normal_">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.normalize.html#torch.nn.functional.normalize">normalize() (in module torch.nn.functional)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.normalized_arguments">normalized_arguments() (torch.fx.Node method)</a>
</li>
      <li><a href="generated/torch.not_equal.html#torch.not_equal">not_equal() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.not_equal.html#torch.Tensor.not_equal">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.not_equal_.html#torch.Tensor.not_equal_">not_equal_() (torch.Tensor method)</a>
</li>
      <li><a href="distributed.algorithms.join.html#torch.distributed.algorithms.Join.notify_join_context">notify_join_context() (torch.distributed.algorithms.Join static method)</a>
</li>
      <li><a href="elastic/metrics.html#torch.distributed.elastic.metrics.api.NullMetricHandler">NullMetricHandler (class in torch.distributed.elastic.metrics.api)</a>
</li>
      <li><a href="distributed.html#torch.distributed.Store.num_keys">num_keys() (in module torch.distributed.Store)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandler.num_nodes_waiting">num_nodes_waiting() (torch.distributed.elastic.rendezvous.RendezvousHandler method)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.TensorPipeRpcBackendOptions.num_worker_threads">num_worker_threads() (torch.distributed.rpc.TensorPipeRpcBackendOptions property)</a>
</li>
      <li><a href="generated/torch.numel.html#torch.numel">numel() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.numel.html#torch.Tensor.numel">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.numpy.html#torch.Tensor.numpy">numpy() (torch.Tensor method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="O">O</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="torch.quantization.html#torch.quantization.ObserverBase">ObserverBase (class in torch.quantization)</a>
</li>
      <li><a href="generated/torch.nn.functional.one_hot.html#torch.nn.functional.one_hot">one_hot() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.OneCycleLR.html#torch.optim.lr_scheduler.OneCycleLR">OneCycleLR (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical">OneHotCategorical (class in torch.distributions.one_hot_categorical)</a>
</li>
      <li><a href="generated/torch.ones.html#torch.ones">ones() (in module torch)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.ones_">ones_() (in module torch.nn.init)</a>
</li>
      <li><a href="generated/torch.ones_like.html#torch.ones_like">ones_like() (in module torch)</a>
</li>
      <li><a href="generated/torch.jit.optimize_for_inference.html#torch.jit.optimize_for_inference">optimize_for_inference() (in module torch.jit)</a>
</li>
      <li><a href="mobile_optimizer.html#torch.utils.mobile_optimizer.optimize_for_mobile">optimize_for_mobile() (in module torch.utils.mobile_optimizer)</a>
</li>
      <li><a href="optim.html#torch.optim.Optimizer">Optimizer (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.orgqr.html#torch.orgqr">orgqr() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.orgqr.html#torch.Tensor.orgqr">(torch.Tensor method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.ormqr.html#torch.ormqr">ormqr() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.ormqr.html#torch.Tensor.ormqr">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.utils.parametrizations.orthogonal.html#torch.nn.utils.parametrizations.orthogonal">orthogonal() (in module torch.nn.utils.parametrizations)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.orthogonal_">orthogonal_() (in module torch.nn.init)</a>
</li>
      <li><a href="generated/torch.outer.html#torch.outer">outer() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.outer.html#torch.Tensor.outer">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Graph.output">output() (torch.fx.Graph method)</a>

      <ul>
        <li><a href="fx.html#torch.fx.Interpreter.output">(torch.fx.Interpreter method)</a>
</li>
      </ul></li>
      <li><a href="rpc.html#torch.distributed.rpc.RRef.owner">owner() (torch.distributed.rpc.RRef method)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.RRef.owner_name">owner_name() (torch.distributed.rpc.RRef method)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.owning_module">owning_module() (torch.fx.Graph property)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="P">P</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.nn.utils.rnn.pack_padded_sequence.html#torch.nn.utils.rnn.pack_padded_sequence">pack_padded_sequence() (in module torch.nn.utils.rnn)</a>
</li>
      <li><a href="generated/torch.nn.utils.rnn.pack_sequence.html#torch.nn.utils.rnn.pack_sequence">pack_sequence() (in module torch.nn.utils.rnn)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter">PackageExporter (class in torch.package)</a>
</li>
      <li><a href="package.html#torch.package.PackageImporter">PackageImporter (class in torch.package)</a>
</li>
      <li><a href="package.html#torch.package.PackagingError">PackagingError (class in torch.package)</a>
</li>
      <li><a href="generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence">PackedSequence (class in torch.nn.utils.rnn)</a>
</li>
      <li><a href="generated/torch.nn.functional.pad.html#torch.nn.functional.pad">pad() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.utils.rnn.pad_packed_sequence.html#torch.nn.utils.rnn.pad_packed_sequence">pad_packed_sequence() (in module torch.nn.utils.rnn)</a>
</li>
      <li><a href="generated/torch.nn.utils.rnn.pad_sequence.html#torch.nn.utils.rnn.pad_sequence">pad_sequence() (in module torch.nn.utils.rnn)</a>
</li>
      <li><a href="generated/torch.nn.functional.pairwise_distance.html#torch.nn.functional.pairwise_distance">pairwise_distance() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.PairwiseDistance.html#torch.nn.PairwiseDistance">PairwiseDistance (class in torch.nn)</a>
</li>
      <li><a href="__config__.html#torch.__config__.parallel_info">parallel_info() (in module torch.__config__)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.param_shape">param_shape() (torch.distributions.bernoulli.Bernoulli property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.param_shape">(torch.distributions.binomial.Binomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.param_shape">(torch.distributions.categorical.Categorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.param_shape">(torch.distributions.continuous_bernoulli.ContinuousBernoulli property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.param_shape">(torch.distributions.multinomial.Multinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.param_shape">(torch.distributions.negative_binomial.NegativeBinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.param_shape">(torch.distributions.one_hot_categorical.OneHotCategorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli.param_shape">(torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli property)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.parameter.Parameter.html#torch.nn.parameter.Parameter">Parameter (class in torch.nn.parameter)</a>
</li>
      <li><a href="generated/torch.nn.ParameterDict.html#torch.nn.ParameterDict">ParameterDict (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ParameterList.html#torch.nn.ParameterList">ParameterList (class in torch.nn)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.GradBucket.parameters">parameters() (in module torch.distributed.GradBucket)</a>

      <ul>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.parameters">(torch.jit.ScriptModule method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.parameters">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.utils.parameters_to_vector.html#torch.nn.utils.parameters_to_vector">parameters_to_vector() (in module torch.nn.utils)</a>
</li>
      <li><a href="generated/torch.nn.utils.parametrize.ParametrizationList.html#torch.nn.utils.parametrize.ParametrizationList">ParametrizationList (class in torch.nn.utils.parametrize)</a>
</li>
      <li><a href="distributions.html#torch.distributions.pareto.Pareto">Pareto (class in torch.distributions.pareto)</a>
</li>
      <li><a href="fx.html#torch.fx.Tracer.path_of_module">path_of_module() (torch.fx.Tracer method)</a>
</li>
      <li><a href="generated/torch.pca_lowrank.html#torch.pca_lowrank">pca_lowrank() (in module torch)</a>
</li>
      <li><a href="elastic/multiprocessing.html#torch.distributed.elastic.multiprocessing.api.PContext">PContext (class in torch.distributed.elastic.multiprocessing.api)</a>
</li>
      <li><a href="generated/torch.nn.functional.pdist.html#torch.nn.functional.pdist">pdist() (in module torch.nn.functional)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.PerChannelMinMaxObserver">PerChannelMinMaxObserver (class in torch.quantization)</a>
</li>
      <li><a href="generated/torch.permute.html#torch.permute">permute() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.permute.html#torch.Tensor.permute">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.distribution.Distribution.perplexity">perplexity() (torch.distributions.distribution.Distribution method)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.pin_memory">pin_memory() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.pin_memory">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.pin_memory">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.pin_memory">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.pin_memory">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.pin_memory">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.pin_memory">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.pin_memory">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.pin_memory">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.pin_memory">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.pin_memory">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.pin_memory">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.pin_memory">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.pin_memory">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.pin_memory">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.pin_memory">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.pin_memory.html#torch.Tensor.pin_memory">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.linalg.pinv.html#torch.linalg.pinv">pinv() (in module torch.linalg)</a>
</li>
      <li><a href="generated/torch.pinverse.html#torch.pinverse">pinverse() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.pinverse.html#torch.Tensor.pinverse">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="pipeline.html#torch.distributed.pipeline.sync.Pipe">Pipe (class in torch.distributed.pipeline.sync)</a>
</li>
      <li><a href="generated/torch.nn.functional.pixel_shuffle.html#torch.nn.functional.pixel_shuffle">pixel_shuffle() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.pixel_unshuffle.html#torch.nn.functional.pixel_unshuffle">pixel_unshuffle() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.PixelShuffle.html#torch.nn.PixelShuffle">PixelShuffle (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.PixelUnshuffle.html#torch.nn.PixelUnshuffle">PixelUnshuffle (class in torch.nn)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.placeholder">placeholder() (torch.fx.Graph method)</a>

      <ul>
        <li><a href="fx.html#torch.fx.Interpreter.placeholder">(torch.fx.Interpreter method)</a>
</li>
        <li><a href="fx.html#torch.fx.Transformer.placeholder">(torch.fx.Transformer method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.poisson.Poisson">Poisson (class in torch.distributions.poisson)</a>
</li>
      <li><a href="generated/torch.poisson.html#torch.poisson">poisson() (in module torch)</a>
</li>
      <li><a href="generated/torch.nn.functional.poisson_nll_loss.html#torch.nn.functional.poisson_nll_loss">poisson_nll_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.PoissonNLLLoss.html#torch.nn.PoissonNLLLoss">PoissonNLLLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.polar.html#torch.polar">polar() (in module torch)</a>
</li>
      <li><a href="generated/torch.polygamma.html#torch.polygamma">polygamma() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.polygamma">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.polygamma.html#torch.Tensor.polygamma">(torch.Tensor method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.Tensor.polygamma_.html#torch.Tensor.polygamma_">polygamma_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.cuda.CUDAGraph.html#torch.cuda.CUDAGraph.pool">pool() (torch.cuda.CUDAGraph method)</a>
</li>
      <li><a href="pipeline.html#torch.distributed.pipeline.sync.skip.skippable.pop">pop (class in torch.distributed.pipeline.sync.skip.skippable)</a>
</li>
      <li><a href="generated/torch.nn.ModuleDict.html#torch.nn.ModuleDict.pop">pop() (torch.nn.ModuleDict method)</a>

      <ul>
        <li><a href="generated/torch.nn.ParameterDict.html#torch.nn.ParameterDict.pop">(torch.nn.ParameterDict method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.positive.html#torch.positive">positive() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.positive.html#torch.Tensor.positive">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributed.algorithms.join.html#torch.distributed.algorithms.JoinHook.post_hook">post_hook() (torch.distributed.algorithms.JoinHook method)</a>
</li>
      <li><a href="generated/torch.pow.html#torch.pow">pow() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.pow.html#torch.Tensor.pow">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.pow_.html#torch.Tensor.pow_">pow_() (torch.Tensor method)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.algorithms.ddp_comm_hooks.powerSGD_hook.powerSGD_hook">powerSGD_hook() (in module torch.distributed.algorithms.ddp_comm_hooks.powerSGD_hook)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.algorithms.ddp_comm_hooks.powerSGD_hook.PowerSGDState">PowerSGDState (class in torch.distributed.algorithms.ddp_comm_hooks.powerSGD_hook)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.PowerTransform">PowerTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.precision_matrix">precision_matrix() (torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.precision_matrix">(torch.distributions.multivariate_normal.MultivariateNormal property)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.AdaptiveLogSoftmaxWithLoss.html#torch.nn.AdaptiveLogSoftmaxWithLoss.predict">predict() (torch.nn.AdaptiveLogSoftmaxWithLoss method)</a>
</li>
      <li><a href="distributed.html#torch.distributed.PrefixStore">PrefixStore (class in torch.distributed)</a>
</li>
      <li><a href="generated/torch.nn.PReLU.html#torch.nn.PReLU">PReLU (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.prelu.html#torch.nn.functional.prelu">prelu() (in module torch.nn.functional)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.prepare">prepare() (in module torch.quantization)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.prepare_qat">prepare_qat() (in module torch.quantization)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.prepend">prepend() (torch.fx.Node method)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.prev">prev() (torch.fx.Node property)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.ChainedScheduler.html#torch.optim.lr_scheduler.ChainedScheduler.print_lr">print_lr() (torch.optim.lr_scheduler.ChainedScheduler method)</a>

      <ul>
        <li><a href="generated/torch.optim.lr_scheduler.ConstantLR.html#torch.optim.lr_scheduler.ConstantLR.print_lr">(torch.optim.lr_scheduler.ConstantLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingLR.html#torch.optim.lr_scheduler.CosineAnnealingLR.print_lr">(torch.optim.lr_scheduler.CosineAnnealingLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.html#torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.print_lr">(torch.optim.lr_scheduler.CosineAnnealingWarmRestarts method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CyclicLR.html#torch.optim.lr_scheduler.CyclicLR.print_lr">(torch.optim.lr_scheduler.CyclicLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.ExponentialLR.html#torch.optim.lr_scheduler.ExponentialLR.print_lr">(torch.optim.lr_scheduler.ExponentialLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.LambdaLR.html#torch.optim.lr_scheduler.LambdaLR.print_lr">(torch.optim.lr_scheduler.LambdaLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.LinearLR.html#torch.optim.lr_scheduler.LinearLR.print_lr">(torch.optim.lr_scheduler.LinearLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.MultiplicativeLR.html#torch.optim.lr_scheduler.MultiplicativeLR.print_lr">(torch.optim.lr_scheduler.MultiplicativeLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.MultiStepLR.html#torch.optim.lr_scheduler.MultiStepLR.print_lr">(torch.optim.lr_scheduler.MultiStepLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.OneCycleLR.html#torch.optim.lr_scheduler.OneCycleLR.print_lr">(torch.optim.lr_scheduler.OneCycleLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.SequentialLR.html#torch.optim.lr_scheduler.SequentialLR.print_lr">(torch.optim.lr_scheduler.SequentialLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.StepLR.html#torch.optim.lr_scheduler.StepLR.print_lr">(torch.optim.lr_scheduler.StepLR method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Graph.print_tabular">print_tabular() (torch.fx.Graph method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.probs">probs() (torch.distributions.bernoulli.Bernoulli property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.probs">(torch.distributions.binomial.Binomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.probs">(torch.distributions.categorical.Categorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.probs">(torch.distributions.continuous_bernoulli.ContinuousBernoulli property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.geometric.Geometric.probs">(torch.distributions.geometric.Geometric property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.probs">(torch.distributions.multinomial.Multinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.probs">(torch.distributions.negative_binomial.NegativeBinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.probs">(torch.distributions.one_hot_categorical.OneHotCategorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli.probs">(torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.RelaxedBernoulli.probs">(torch.distributions.relaxed_bernoulli.RelaxedBernoulli property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_categorical.RelaxedOneHotCategorical.probs">(torch.distributions.relaxed_categorical.RelaxedOneHotCategorical property)</a>
</li>
      </ul></li>
      <li><a href="elastic/errors.html#torch.distributed.elastic.multiprocessing.errors.ProcessFailure">ProcessFailure (class in torch.distributed.elastic.multiprocessing.errors)</a>
</li>
      <li><a href="generated/torch.prod.html#torch.prod">prod() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.prod.html#torch.Tensor.prod">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="elastic/metrics.html#torch.distributed.elastic.metrics.prof">prof() (in module torch.distributed.elastic.metrics)</a>
</li>
      <li><a href="autograd.html#torch.autograd.profiler.profile">profile (class in torch.autograd.profiler)</a>

      <ul>
        <li><a href="profiler.html#torch.profiler.profile">(class in torch.profiler)</a>
</li>
      </ul></li>
      <li><a href="profiler.html#torch.profiler.ProfilerAction">ProfilerAction (class in torch.profiler)</a>
</li>
      <li><a href="profiler.html#torch.profiler.ProfilerActivity">ProfilerActivity (class in torch.profiler)</a>
</li>
      <li><a href="generated/torch.promote_types.html#torch.promote_types">promote_types() (in module torch)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.propagate_qconfig_">propagate_qconfig_() (in module torch.quantization)</a>
</li>
      <li><a href="fx.html#torch.fx.Proxy">Proxy (class in torch.fx)</a>
</li>
      <li><a href="fx.html#torch.fx.Tracer.proxy">proxy() (torch.fx.Tracer method)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.BasePruningMethod.html#torch.nn.utils.prune.BasePruningMethod.prune">prune() (torch.nn.utils.prune.BasePruningMethod method)</a>

      <ul>
        <li><a href="generated/torch.nn.utils.prune.CustomFromMask.html#torch.nn.utils.prune.CustomFromMask.prune">(torch.nn.utils.prune.CustomFromMask method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.Identity.html#torch.nn.utils.prune.Identity.prune">(torch.nn.utils.prune.Identity method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.L1Unstructured.html#torch.nn.utils.prune.L1Unstructured.prune">(torch.nn.utils.prune.L1Unstructured method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.LnStructured.html#torch.nn.utils.prune.LnStructured.prune">(torch.nn.utils.prune.LnStructured method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.PruningContainer.html#torch.nn.utils.prune.PruningContainer.prune">(torch.nn.utils.prune.PruningContainer method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.RandomStructured.html#torch.nn.utils.prune.RandomStructured.prune">(torch.nn.utils.prune.RandomStructured method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.RandomUnstructured.html#torch.nn.utils.prune.RandomUnstructured.prune">(torch.nn.utils.prune.RandomUnstructured method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.utils.prune.PruningContainer.html#torch.nn.utils.prune.PruningContainer">PruningContainer (class in torch.nn.utils.prune)</a>
</li>
      <li><a href="special.html#torch.special.psi">psi() (in module torch.special)</a>
</li>
      <li><a href="generated/torch.Tensor.put_.html#torch.Tensor.put_">put_() (torch.Tensor method)</a>
</li>
      <li><a href="elastic/metrics.html#torch.distributed.elastic.metrics.put_metric">put_metric() (in module torch.distributed.elastic.metrics)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.python_code">python_code() (torch.fx.Graph method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="Q">Q</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.Tensor.q_per_channel_axis.html#torch.Tensor.q_per_channel_axis">q_per_channel_axis() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.q_per_channel_scales.html#torch.Tensor.q_per_channel_scales">q_per_channel_scales() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.q_per_channel_zero_points.html#torch.Tensor.q_per_channel_zero_points">q_per_channel_zero_points() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.q_scale.html#torch.Tensor.q_scale">q_scale() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.q_zero_point.html#torch.Tensor.q_zero_point">q_zero_point() (torch.Tensor method)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.QConfig">QConfig (class in torch.quantization)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.QConfigDynamic">QConfigDynamic (class in torch.quantization)</a>
</li>
      <li><a href="torch.nn.quantized.html#torch.nn.quantized.QFunctional">QFunctional (class in torch.nn.quantized)</a>
</li>
      <li><a href="storage.html#torch.QInt32Storage">QInt32Storage (class in torch)</a>
</li>
      <li><a href="storage.html#torch.QInt8Storage">QInt8Storage (class in torch)</a>
</li>
      <li><a href="generated/torch.qr.html#torch.qr">qr() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.qr.html#torch.linalg.qr">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.qr.html#torch.Tensor.qr">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.qscheme.html#torch.Tensor.qscheme">qscheme() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.quantile.html#torch.quantile">quantile() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.quantile.html#torch.Tensor.quantile">(torch.Tensor method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="torch.nn.quantized.html#torch.nn.quantized.Quantize">Quantize (class in torch.nn.quantized)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.quantize">quantize() (in module torch.quantization)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.quantize_dynamic">quantize_dynamic() (in module torch.quantization)</a>
</li>
      <li><a href="generated/torch.quantize_per_channel.html#torch.quantize_per_channel">quantize_per_channel() (in module torch)</a>
</li>
      <li><a href="generated/torch.quantize_per_tensor.html#torch.quantize_per_tensor">quantize_per_tensor() (in module torch)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.quantize_qat">quantize_qat() (in module torch.quantization)</a>
</li>
      <li><a href="generated/torch.quantized_batch_norm.html#torch.quantized_batch_norm">quantized_batch_norm() (in module torch)</a>
</li>
      <li><a href="generated/torch.quantized_max_pool1d.html#torch.quantized_max_pool1d">quantized_max_pool1d() (in module torch)</a>
</li>
      <li><a href="generated/torch.quantized_max_pool2d.html#torch.quantized_max_pool2d">quantized_max_pool2d() (in module torch)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.QuantStub">QuantStub (class in torch.quantization)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.QuantWrapper">QuantWrapper (class in torch.quantization)</a>
</li>
      <li><a href="generated/torch.cuda.Event.html#torch.cuda.Event.query">query() (torch.cuda.Event method)</a>

      <ul>
        <li><a href="generated/torch.cuda.Stream.html#torch.cuda.Stream.query">(torch.cuda.Stream method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.QUInt4x2Storage">QUInt4x2Storage (class in torch)</a>
</li>
      <li><a href="storage.html#torch.QUInt8Storage">QUInt8Storage (class in torch)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="R">R</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.rad2deg.html#torch.rad2deg">rad2deg() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.rad2deg.html#torch.Tensor.rad2deg">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.optim.RAdam.html#torch.optim.RAdam">RAdam (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.rand.html#torch.rand">rand() (in module torch)</a>
</li>
      <li><a href="generated/torch.rand_like.html#torch.rand_like">rand_like() (in module torch)</a>
</li>
      <li><a href="generated/torch.randint.html#torch.randint">randint() (in module torch)</a>
</li>
      <li><a href="generated/torch.randint_like.html#torch.randint_like">randint_like() (in module torch)</a>
</li>
      <li><a href="generated/torch.randn.html#torch.randn">randn() (in module torch)</a>
</li>
      <li><a href="generated/torch.randn_like.html#torch.randn_like">randn_like() (in module torch)</a>
</li>
      <li><a href="generated/torch.Tensor.random_.html#torch.Tensor.random_">random_() (torch.Tensor method)</a>
</li>
      <li><a href="data.html#torch.utils.data.random_split">random_split() (in module torch.utils.data)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.random_structured.html#torch.nn.utils.prune.random_structured">random_structured() (in module torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.random_unstructured.html#torch.nn.utils.prune.random_unstructured">random_unstructured() (in module torch.nn.utils.prune)</a>
</li>
      <li><a href="data.html#torch.utils.data.RandomSampler">RandomSampler (class in torch.utils.data)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.RandomStructured.html#torch.nn.utils.prune.RandomStructured">RandomStructured (class in torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.RandomUnstructured.html#torch.nn.utils.prune.RandomUnstructured">RandomUnstructured (class in torch.nn.utils.prune)</a>
</li>
      <li><a href="generated/torch.randperm.html#torch.randperm">randperm() (in module torch)</a>
</li>
      <li><a href="generated/torch.range.html#torch.range">range() (in module torch)</a>
</li>
      <li><a href="generated/torch.cuda.nvtx.range_pop.html#torch.cuda.nvtx.range_pop">range_pop() (in module torch.cuda.nvtx)</a>
</li>
      <li><a href="generated/torch.cuda.nvtx.range_push.html#torch.cuda.nvtx.range_push">range_push() (in module torch.cuda.nvtx)</a>
</li>
      <li><a href="generated/torch.ravel.html#torch.ravel">ravel() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.ravel.html#torch.Tensor.ravel">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.real.html#torch.Tensor.real">real (torch.Tensor attribute)</a>
</li>
      <li><a href="generated/torch.real.html#torch.real">real() (in module torch)</a>
</li>
      <li><a href="generated/torch.reciprocal.html#torch.reciprocal">reciprocal() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.reciprocal.html#torch.Tensor.reciprocal">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.reciprocal_.html#torch.Tensor.reciprocal_">reciprocal_() (torch.Tensor method)</a>
</li>
      <li><a href="fx.html#torch.fx.GraphModule.recompile">recompile() (torch.fx.GraphModule method)</a>
</li>
      <li><a href="elastic/events.html#torch.distributed.elastic.events.record">record() (in module torch.distributed.elastic.events)</a>

      <ul>
        <li><a href="elastic/errors.html#torch.distributed.elastic.multiprocessing.errors.record">(in module torch.distributed.elastic.multiprocessing.errors)</a>
</li>
        <li><a href="generated/torch.cuda.Event.html#torch.cuda.Event.record">(torch.cuda.Event method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.Stream.html#torch.cuda.Stream.record_event">record_event() (torch.cuda.Stream method)</a>
</li>
      <li><a href="generated/torch.Tensor.record_stream.html#torch.Tensor.record_stream">record_stream() (torch.Tensor method)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.RecordingObserver">RecordingObserver (class in torch.quantization)</a>
</li>
      <li><a href="distributed.html#torch.distributed.recv">recv() (in module torch.distributed)</a>
</li>
      <li><a href="distributed.html#torch.distributed.reduce">reduce() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.cuda.comm.reduce_add.html#torch.cuda.comm.reduce_add">reduce_add() (in module torch.cuda.comm)</a>
</li>
      <li><a href="distributed.html#torch.distributed.reduce_multigpu">reduce_multigpu() (in module torch.distributed)</a>
</li>
      <li><a href="distributed.html#torch.distributed.reduce_op">reduce_op (class in torch.distributed)</a>
</li>
      <li><a href="distributed.html#torch.distributed.reduce_scatter">reduce_scatter() (in module torch.distributed)</a>
</li>
      <li><a href="distributed.html#torch.distributed.reduce_scatter_multigpu">reduce_scatter_multigpu() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.ReduceLROnPlateau.html#torch.optim.lr_scheduler.ReduceLROnPlateau">ReduceLROnPlateau (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="distributed.html#torch.distributed.ReduceOp">ReduceOp (class in torch.distributed)</a>
</li>
      <li><a href="named_tensor.html#torch.Tensor.refine_names">refine_names() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.ReflectionPad1d.html#torch.nn.ReflectionPad1d">ReflectionPad1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ReflectionPad2d.html#torch.nn.ReflectionPad2d">ReflectionPad2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ReflectionPad3d.html#torch.nn.ReflectionPad3d">ReflectionPad3d (class in torch.nn)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandlerRegistry.register">register() (torch.distributed.elastic.rendezvous.RendezvousHandlerRegistry method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.constraint_registry.ConstraintRegistry.register">(torch.distributions.constraint_registry.ConstraintRegistry method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.register_backward_hook">register_backward_hook() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.register_backward_hook">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.register_buffer">register_buffer() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.register_buffer">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel.register_comm_hook">register_comm_hook() (torch.nn.parallel.DistributedDataParallel method)</a>
</li>
      <li><a href="onnx.html#torch.onnx.register_custom_op_symbolic">register_custom_op_symbolic() (in module torch.onnx)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.register_extern_hook">register_extern_hook() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.register_forward_hook">register_forward_hook() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.register_forward_hook">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.register_forward_pre_hook">register_forward_pre_hook() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.register_forward_pre_hook">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.register_full_backward_hook">register_full_backward_hook() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.register_full_backward_hook">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.register_hook.html#torch.Tensor.register_hook">register_hook() (torch.Tensor method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.register_intern_hook">register_intern_hook() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.kl.register_kl">register_kl() (in module torch.distributions.kl)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.register_mock_hook">register_mock_hook() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="generated/torch.nn.modules.module.register_module_backward_hook.html#torch.nn.modules.module.register_module_backward_hook">register_module_backward_hook() (in module torch.nn.modules.module)</a>
</li>
      <li><a href="generated/torch.nn.modules.module.register_module_forward_hook.html#torch.nn.modules.module.register_module_forward_hook">register_module_forward_hook() (in module torch.nn.modules.module)</a>
</li>
      <li><a href="generated/torch.nn.modules.module.register_module_forward_pre_hook.html#torch.nn.modules.module.register_module_forward_pre_hook">register_module_forward_pre_hook() (in module torch.nn.modules.module)</a>
</li>
      <li><a href="generated/torch.nn.modules.module.register_module_full_backward_hook.html#torch.nn.modules.module.register_module_full_backward_hook">register_module_full_backward_hook() (in module torch.nn.modules.module)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.register_parameter">register_parameter() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.register_parameter">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.utils.parametrize.register_parametrization.html#torch.nn.utils.parametrize.register_parametrization">register_parametrization() (in module torch.nn.utils.parametrize)</a>
</li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.TimerServer.register_timers">register_timers() (torch.distributed.elastic.timer.TimerServer method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.RelaxedBernoulli">RelaxedBernoulli (class in torch.distributions.relaxed_bernoulli)</a>
</li>
      <li><a href="distributions.html#torch.distributions.relaxed_categorical.RelaxedOneHotCategorical">RelaxedOneHotCategorical (class in torch.distributions.relaxed_categorical)</a>
</li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.TimerClient.release">release() (torch.distributed.elastic.timer.TimerClient method)</a>
</li>
      <li><a href="generated/torch.nn.ReLU.html#torch.nn.ReLU">ReLU (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.relu.html#torch.nn.functional.relu">relu() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.ReLU6.html#torch.nn.ReLU6">ReLU6 (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.ReLU6">(class in torch.nn.quantized)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.relu6.html#torch.nn.functional.relu6">relu6() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.relu_.html#torch.nn.functional.relu_">relu_() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.remainder.html#torch.remainder">remainder() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.remainder.html#torch.Tensor.remainder">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.remainder_.html#torch.Tensor.remainder_">remainder_() (torch.Tensor method)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.remote">remote() (in module torch.distributed.rpc)</a>

      <ul>
        <li><a href="rpc.html#torch.distributed.rpc.RRef.remote">(torch.distributed.rpc.RRef method)</a>
</li>
      </ul></li>
      <li><a href="rpc.html#torch.distributed.nn.api.remote_module.RemoteModule.remote_parameters">remote_parameters() (torch.distributed.nn.api.remote_module.RemoteModule method)</a>
</li>
      <li><a href="rpc.html#torch.distributed.nn.api.remote_module.RemoteModule">RemoteModule (class in torch.distributed.nn.api.remote_module)</a>
</li>
      <li><a href="generated/torch.nn.utils.prune.remove.html#torch.nn.utils.prune.remove">remove() (in module torch.nn.utils.prune)</a>

      <ul>
        <li><a href="generated/torch.nn.utils.prune.BasePruningMethod.html#torch.nn.utils.prune.BasePruningMethod.remove">(torch.nn.utils.prune.BasePruningMethod method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.CustomFromMask.html#torch.nn.utils.prune.CustomFromMask.remove">(torch.nn.utils.prune.CustomFromMask method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.Identity.html#torch.nn.utils.prune.Identity.remove">(torch.nn.utils.prune.Identity method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.L1Unstructured.html#torch.nn.utils.prune.L1Unstructured.remove">(torch.nn.utils.prune.L1Unstructured method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.LnStructured.html#torch.nn.utils.prune.LnStructured.remove">(torch.nn.utils.prune.LnStructured method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.PruningContainer.html#torch.nn.utils.prune.PruningContainer.remove">(torch.nn.utils.prune.PruningContainer method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.RandomStructured.html#torch.nn.utils.prune.RandomStructured.remove">(torch.nn.utils.prune.RandomStructured method)</a>
</li>
        <li><a href="generated/torch.nn.utils.prune.RandomUnstructured.html#torch.nn.utils.prune.RandomUnstructured.remove">(torch.nn.utils.prune.RandomUnstructured method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.utils.parametrize.remove_parametrizations.html#torch.nn.utils.parametrize.remove_parametrizations">remove_parametrizations() (in module torch.nn.utils.parametrize)</a>
</li>
      <li><a href="generated/torch.nn.utils.remove_spectral_norm.html#torch.nn.utils.remove_spectral_norm">remove_spectral_norm() (in module torch.nn.utils)</a>
</li>
      <li><a href="generated/torch.nn.utils.remove_weight_norm.html#torch.nn.utils.remove_weight_norm">remove_weight_norm() (in module torch.nn.utils)</a>
</li>
      <li><a href="named_tensor.html#torch.Tensor.rename">rename() (torch.Tensor method)</a>
</li>
      <li><a href="named_tensor.html#torch.Tensor.rename_">rename_() (torch.Tensor method)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousBackend">RendezvousBackend (class in torch.distributed.elastic.rendezvous.dynamic_rendezvous)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousClosedError">RendezvousClosedError (class in torch.distributed.elastic.rendezvous)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousConnectionError">RendezvousConnectionError (class in torch.distributed.elastic.rendezvous)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousError">RendezvousError (class in torch.distributed.elastic.rendezvous)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandler">RendezvousHandler (class in torch.distributed.elastic.rendezvous)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandlerRegistry">RendezvousHandlerRegistry (class in torch.distributed.elastic.rendezvous)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousParameters">RendezvousParameters (class in torch.distributed.elastic.rendezvous)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousStateError">RendezvousStateError (class in torch.distributed.elastic.rendezvous)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousTimeout">RendezvousTimeout (class in torch.distributed.elastic.rendezvous.dynamic_rendezvous)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousTimeoutError">RendezvousTimeoutError (class in torch.distributed.elastic.rendezvous)</a>
</li>
      <li><a href="generated/torch.renorm.html#torch.renorm">renorm() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.renorm.html#torch.Tensor.renorm">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.renorm_.html#torch.Tensor.renorm_">renorm_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.repeat.html#torch.Tensor.repeat">repeat() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.repeat_interleave.html#torch.repeat_interleave">repeat_interleave() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.repeat_interleave.html#torch.Tensor.repeat_interleave">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Node.replace_all_uses_with">replace_all_uses_with() (torch.fx.Node method)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.replace_input_with">replace_input_with() (torch.fx.Node method)</a>
</li>
      <li><a href="fx.html#torch.fx.replace_pattern">replace_pattern() (in module torch.fx)</a>
</li>
      <li><a href="generated/torch.cuda.CUDAGraph.html#torch.cuda.CUDAGraph.replay">replay() (torch.cuda.CUDAGraph method)</a>
</li>
      <li><a href="generated/torch.nn.ReplicationPad1d.html#torch.nn.ReplicationPad1d">ReplicationPad1d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ReplicationPad2d.html#torch.nn.ReplicationPad2d">ReplicationPad2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.ReplicationPad3d.html#torch.nn.ReplicationPad3d">ReplicationPad3d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.Tensor.requires_grad.html#torch.Tensor.requires_grad">requires_grad (torch.Tensor attribute)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.requires_grad_">requires_grad_() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.requires_grad_">(torch.nn.Module method)</a>
</li>
        <li><a href="generated/torch.Tensor.requires_grad_.html#torch.Tensor.requires_grad_">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.CUDAGraph.html#torch.cuda.CUDAGraph.reset">reset() (torch.cuda.CUDAGraph method)</a>

      <ul>
        <li><a href="generated/torch.quasirandom.SobolEngine.html#torch.quasirandom.SobolEngine.reset">(torch.quasirandom.SobolEngine method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.reset_max_memory_allocated.html#torch.cuda.reset_max_memory_allocated">reset_max_memory_allocated() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.reset_max_memory_cached.html#torch.cuda.reset_max_memory_cached">reset_max_memory_cached() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.reset_peak_memory_stats.html#torch.cuda.reset_peak_memory_stats">reset_peak_memory_stats() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.reshape.html#torch.reshape">reshape() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.reshape.html#torch.Tensor.reshape">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.reshape_as.html#torch.Tensor.reshape_as">reshape_as() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.ReshapeTransform">ReshapeTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.resize_">resize_() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.resize_">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.resize_">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.resize_">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.resize_">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.resize_">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.resize_">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.resize_">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.resize_">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.resize_">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.resize_">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.resize_">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.resize_">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.resize_">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.resize_">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.resize_">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.resize_.html#torch.Tensor.resize_">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.resize_as_.html#torch.Tensor.resize_as_">resize_as_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.resolve_conj.html#torch.resolve_conj">resolve_conj() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.resolve_conj.html#torch.Tensor.resolve_conj">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.resolve_neg.html#torch.resolve_neg">resolve_neg() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.resolve_neg.html#torch.Tensor.resolve_neg">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.result_type.html#torch.result_type">result_type() (in module torch)</a>
</li>
      <li><a href="generated/torch.Tensor.retain_grad.html#torch.Tensor.retain_grad">retain_grad() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.retains_grad.html#torch.Tensor.retains_grad">retains_grad (torch.Tensor attribute)</a>
</li>
      <li><a href="generated/torch.fft.rfft.html#torch.fft.rfft">rfft() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.rfft2.html#torch.fft.rfft2">rfft2() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.rfftfreq.html#torch.fft.rfftfreq">rfftfreq() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.fft.rfftn.html#torch.fft.rfftn">rfftn() (in module torch.fft)</a>
</li>
      <li><a href="generated/torch.nn.utils.parametrize.ParametrizationList.html#torch.nn.utils.parametrize.ParametrizationList.right_inverse">right_inverse() (torch.nn.utils.parametrize.ParametrizationList method)</a>
</li>
      <li><a href="generated/torch.optim.RMSprop.html#torch.optim.RMSprop">RMSprop (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.nn.RNN.html#torch.nn.RNN">RNN (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.RNNBase.html#torch.nn.RNNBase">RNNBase (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.RNNCell.html#torch.nn.RNNCell">RNNCell (class in torch.nn)</a>

      <ul>
        <li><a href="torch.nn.quantized.dynamic.html#torch.nn.quantized.dynamic.RNNCell">(class in torch.nn.quantized.dynamic)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.roll.html#torch.roll">roll() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.roll.html#torch.Tensor.roll">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.rot90.html#torch.rot90">rot90() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.rot90.html#torch.Tensor.rot90">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.round.html#torch.round">round() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.round">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.round.html#torch.Tensor.round">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.round_.html#torch.Tensor.round_">round_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.row_stack.html#torch.row_stack">row_stack() (in module torch)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.rpc_async">rpc_async() (in module torch.distributed.rpc)</a>

      <ul>
        <li><a href="rpc.html#torch.distributed.rpc.RRef.rpc_async">(torch.distributed.rpc.RRef method)</a>
</li>
      </ul></li>
      <li><a href="rpc.html#torch.distributed.rpc.rpc_sync">rpc_sync() (in module torch.distributed.rpc)</a>

      <ul>
        <li><a href="rpc.html#torch.distributed.rpc.RRef.rpc_sync">(torch.distributed.rpc.RRef method)</a>
</li>
      </ul></li>
      <li><a href="rpc.html#torch.distributed.rpc.RpcBackendOptions.rpc_timeout">rpc_timeout() (torch.distributed.rpc.RpcBackendOptions property)</a>

      <ul>
        <li><a href="rpc.html#torch.distributed.rpc.TensorPipeRpcBackendOptions.rpc_timeout">(torch.distributed.rpc.TensorPipeRpcBackendOptions property)</a>
</li>
      </ul></li>
      <li><a href="rpc.html#torch.distributed.rpc.RpcBackendOptions">RpcBackendOptions (class in torch.distributed.rpc)</a>
</li>
      <li><a href="generated/torch.optim.Rprop.html#torch.optim.Rprop">Rprop (class in torch.optim)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.RRef">RRef (class in torch.distributed.rpc)</a>
</li>
      <li><a href="generated/torch.nn.RReLU.html#torch.nn.RReLU">RReLU (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.rrelu.html#torch.nn.functional.rrelu">rrelu() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.rrelu_.html#torch.nn.functional.rrelu_">rrelu_() (in module torch.nn.functional)</a>
</li>
      <li><a href="distributions.html#torch.distributions.beta.Beta.rsample">rsample() (torch.distributions.beta.Beta method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.rsample">(torch.distributions.cauchy.Cauchy method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.rsample">(torch.distributions.continuous_bernoulli.ContinuousBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet.rsample">(torch.distributions.dirichlet.Dirichlet method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.rsample">(torch.distributions.distribution.Distribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.rsample">(torch.distributions.exponential.Exponential method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.fishersnedecor.FisherSnedecor.rsample">(torch.distributions.fishersnedecor.FisherSnedecor method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gamma.Gamma.rsample">(torch.distributions.gamma.Gamma method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.independent.Independent.rsample">(torch.distributions.independent.Independent method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.rsample">(torch.distributions.laplace.Laplace method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.rsample">(torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.rsample">(torch.distributions.multivariate_normal.MultivariateNormal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.rsample">(torch.distributions.normal.Normal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli.rsample">(torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.studentT.StudentT.rsample">(torch.distributions.studentT.StudentT method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.rsample">(torch.distributions.transformed_distribution.TransformedDistribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.rsample">(torch.distributions.uniform.Uniform method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.rsqrt.html#torch.rsqrt">rsqrt() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.rsqrt.html#torch.Tensor.rsqrt">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.rsqrt_.html#torch.Tensor.rsqrt_">rsqrt_() (torch.Tensor method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.ElasticAgent.run">run() (torch.distributed.elastic.agent.server.ElasticAgent method)</a>

      <ul>
        <li><a href="fx.html#torch.fx.Interpreter.run">(torch.fx.Interpreter method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Interpreter.run_node">run_node() (torch.fx.Interpreter method)</a>
</li>
      <li><a href="elastic/multiprocessing.html#torch.distributed.elastic.multiprocessing.api.RunProcsResult">RunProcsResult (class in torch.distributed.elastic.multiprocessing.api)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.api.RunResult">RunResult (class in torch.distributed.elastic.agent.server.api)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="S">S</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.sample">sample() (torch.distributions.bernoulli.Bernoulli method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.sample">(torch.distributions.binomial.Binomial method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.sample">(torch.distributions.categorical.Categorical method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.sample">(torch.distributions.continuous_bernoulli.ContinuousBernoulli method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.sample">(torch.distributions.distribution.Distribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.geometric.Geometric.sample">(torch.distributions.geometric.Geometric method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.independent.Independent.sample">(torch.distributions.independent.Independent method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lkj_cholesky.LKJCholesky.sample">(torch.distributions.lkj_cholesky.LKJCholesky method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.sample">(torch.distributions.mixture_same_family.MixtureSameFamily method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.sample">(torch.distributions.multinomial.Multinomial method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.sample">(torch.distributions.negative_binomial.NegativeBinomial method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.sample">(torch.distributions.normal.Normal method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.sample">(torch.distributions.one_hot_categorical.OneHotCategorical method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.poisson.Poisson.sample">(torch.distributions.poisson.Poisson method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.sample">(torch.distributions.transformed_distribution.TransformedDistribution method)</a>
</li>
        <li><a href="distributions.html#torch.distributions.von_mises.VonMises.sample">(torch.distributions.von_mises.VonMises method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.distribution.Distribution.sample_n">sample_n() (torch.distributions.distribution.Distribution method)</a>
</li>
      <li><a href="data.html#torch.utils.data.Sampler">Sampler (class in torch.utils.data)</a>
</li>
      <li><a href="generated/torch.save.html#torch.save">save() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.jit.save.html#torch.jit.save">(in module torch.jit)</a>
</li>
        <li><a href="generated/torch.jit.ScriptFunction.html#torch.jit.ScriptFunction.save">(torch.jit.ScriptFunction method)</a>
</li>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.save">(torch.jit.ScriptModule method)</a>
</li>
      </ul></li>
      <li><a href="package.html#torch.package.PackageExporter.save_binary">save_binary() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="generated/torch.autograd.function.FunctionCtx.save_for_backward.html#torch.autograd.function.FunctionCtx.save_for_backward">save_for_backward() (torch.autograd.function.FunctionCtx method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.save_module">save_module() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="autograd.html#torch.autograd.graph.save_on_cpu">save_on_cpu (class in torch.autograd.graph)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.save_pickle">save_pickle() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.save_source_file">save_source_file() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.save_source_string">save_source_string() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="package.html#torch.package.PackageExporter.save_text">save_text() (torch.package.PackageExporter method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptFunction.html#torch.jit.ScriptFunction.save_to_buffer">save_to_buffer() (torch.jit.ScriptFunction method)</a>
</li>
      <li><a href="autograd.html#torch.autograd.graph.saved_tensors_hooks">saved_tensors_hooks (class in torch.autograd.graph)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.scale">scale() (torch.cuda.amp.GradScaler method)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.scale">(torch.distributions.half_cauchy.HalfCauchy property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.scale">(torch.distributions.half_normal.HalfNormal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.log_normal.LogNormal.scale">(torch.distributions.log_normal.LogNormal property)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.scale_tril">scale_tril() (torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.scale_tril">(torch.distributions.multivariate_normal.MultivariateNormal property)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.scatter.html#torch.scatter">scatter() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.cuda.comm.scatter.html#torch.cuda.comm.scatter">(in module torch.cuda.comm)</a>
</li>
        <li><a href="distributed.html#torch.distributed.scatter">(in module torch.distributed)</a>
</li>
        <li><a href="generated/torch.Tensor.scatter.html#torch.Tensor.scatter">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.scatter_.html#torch.Tensor.scatter_">scatter_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.scatter_add.html#torch.scatter_add">scatter_add() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.scatter_add.html#torch.Tensor.scatter_add">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.scatter_add_.html#torch.Tensor.scatter_add_">scatter_add_() (torch.Tensor method)</a>
</li>
      <li><a href="distributed.html#torch.distributed.scatter_object_list">scatter_object_list() (in module torch.distributed)</a>
</li>
      <li><a href="profiler.html#torch.profiler.schedule">schedule() (in module torch.profiler)</a>
</li>
      <li><a href="generated/torch.jit.script.html#torch.jit.script">script() (in module torch.jit)</a>
</li>
      <li><a href="generated/torch.jit.script_if_tracing.html#torch.jit.script_if_tracing">script_if_tracing() (in module torch.jit)</a>
</li>
      <li><a href="generated/torch.jit.ScriptFunction.html#torch.jit.ScriptFunction">ScriptFunction (class in torch.jit)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule">ScriptModule (class in torch.jit)</a>
</li>
      <li><a href="generated/torch.searchsorted.html#torch.searchsorted">searchsorted() (in module torch)</a>
</li>
      <li><a href="generated/torch.seed.html#torch.seed">seed() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.cuda.seed.html#torch.cuda.seed">(in module torch.cuda)</a>
</li>
        <li><a href="random.html#torch.random.seed">(in module torch.random)</a>
</li>
        <li><a href="generated/torch.Generator.html#torch.Generator.seed">(torch.Generator method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.seed_all.html#torch.cuda.seed_all">seed_all() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.Tensor.select.html#torch.Tensor.select">select() (torch.Tensor method)</a>
</li>
      <li><a href="onnx.html#torch.onnx.select_model_mode_for_export">select_model_mode_for_export() (in module torch.onnx)</a>
</li>
      <li><a href="generated/torch.autograd.profiler.profile.self_cpu_time_total.html#torch.autograd.profiler.profile.self_cpu_time_total">self_cpu_time_total() (torch.autograd.profiler.profile property)</a>
</li>
      <li><a href="generated/torch.nn.SELU.html#torch.nn.SELU">SELU (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.selu.html#torch.nn.functional.selu">selu() (in module torch.nn.functional)</a>
</li>
      <li><a href="distributed.html#torch.distributed.send">send() (in module torch.distributed)</a>
</li>
      <li><a href="generated/torch.nn.Sequential.html#torch.nn.Sequential">Sequential (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.optim.lr_scheduler.SequentialLR.html#torch.optim.lr_scheduler.SequentialLR">SequentialLR (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="data.html#torch.utils.data.SequentialSampler">SequentialSampler (class in torch.utils.data)</a>
</li>
      <li><a href="distributed.html#torch.distributed.Store.set">set() (in module torch.distributed.Store)</a>

      <ul>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_store.EtcdStore.set">(torch.distributed.elastic.rendezvous.etcd_store.EtcdStore method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.set_.html#torch.Tensor.set_">set_() (torch.Tensor method)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.set_backoff_factor">set_backoff_factor() (torch.cuda.amp.GradScaler method)</a>
</li>
      <li><a href="ddp_comm_hooks.html#torch.distributed.GradBucket.set_buffer">set_buffer() (in module torch.distributed.GradBucket)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandler.set_closed">set_closed() (torch.distributed.elastic.rendezvous.RendezvousHandler method)</a>
</li>
      <li><a href="generated/torch.set_default_dtype.html#torch.set_default_dtype">set_default_dtype() (in module torch)</a>
</li>
      <li><a href="generated/torch.set_default_tensor_type.html#torch.set_default_tensor_type">set_default_tensor_type() (in module torch)</a>
</li>
      <li><a href="distributions.html#torch.distributions.distribution.Distribution.set_default_validate_args">set_default_validate_args() (torch.distributions.distribution.Distribution static method)</a>
</li>
      <li><a href="autograd.html#torch.autograd.set_detect_anomaly">set_detect_anomaly (class in torch.autograd)</a>
</li>
      <li><a href="generated/torch.cuda.set_device.html#torch.cuda.set_device">set_device() (in module torch.cuda)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.TensorPipeRpcBackendOptions.set_device_map">set_device_map() (torch.distributed.rpc.TensorPipeRpcBackendOptions method)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.TensorPipeRpcBackendOptions.set_devices">set_devices() (torch.distributed.rpc.TensorPipeRpcBackendOptions method)</a>
</li>
      <li><a href="hub.html#torch.hub.set_dir">set_dir() (in module torch.hub)</a>
</li>
      <li><a href="futures.html#torch.futures.Future.set_exception">set_exception() (torch.futures.Future method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.set_extra_state">set_extra_state() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.set_extra_state">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.set_flush_denormal.html#torch.set_flush_denormal">set_flush_denormal() (in module torch)</a>
</li>
      <li><a href="generated/torch.set_grad_enabled.html#torch.set_grad_enabled">set_grad_enabled (class in torch)</a>

      <ul>
        <li><a href="generated/torch.autograd.set_grad_enabled.html#torch.autograd.set_grad_enabled">(class in torch.autograd)</a>
</li>
      </ul></li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.set_growth_factor">set_growth_factor() (torch.cuda.amp.GradScaler method)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.set_growth_interval">set_growth_interval() (torch.cuda.amp.GradScaler method)</a>
</li>
      <li><a href="generated/torch.autograd.function.FunctionCtx.set_materialize_grads.html#torch.autograd.function.FunctionCtx.set_materialize_grads">set_materialize_grads() (torch.autograd.function.FunctionCtx method)</a>
</li>
      <li><a href="generated/torch.set_num_interop_threads.html#torch.set_num_interop_threads">set_num_interop_threads() (in module torch)</a>
</li>
      <li><a href="generated/torch.set_num_threads.html#torch.set_num_threads">set_num_threads() (in module torch)</a>
</li>
      <li><a href="generated/torch.cuda.set_per_process_memory_fraction.html#torch.cuda.set_per_process_memory_fraction">set_per_process_memory_fraction() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.set_printoptions.html#torch.set_printoptions">set_printoptions() (in module torch)</a>
</li>
      <li><a href="futures.html#torch.futures.Future.set_result">set_result() (torch.futures.Future method)</a>
</li>
      <li><a href="generated/torch.set_rng_state.html#torch.set_rng_state">set_rng_state() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.cuda.set_rng_state.html#torch.cuda.set_rng_state">(in module torch.cuda)</a>
</li>
        <li><a href="random.html#torch.random.set_rng_state">(in module torch.random)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.set_rng_state_all.html#torch.cuda.set_rng_state_all">set_rng_state_all() (in module torch.cuda)</a>
</li>
      <li><a href="multiprocessing.html#torch.multiprocessing.set_sharing_strategy">set_sharing_strategy() (in module torch.multiprocessing)</a>
</li>
      <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.c10d_rendezvous_backend.C10dRendezvousBackend.set_state">set_state() (torch.distributed.elastic.rendezvous.c10d_rendezvous_backend.C10dRendezvousBackend method)</a>

      <ul>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousBackend.set_state">(torch.distributed.elastic.rendezvous.dynamic_rendezvous.RendezvousBackend method)</a>
</li>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_rendezvous_backend.EtcdRendezvousBackend.set_state">(torch.distributed.elastic.rendezvous.etcd_rendezvous_backend.EtcdRendezvousBackend method)</a>
</li>
        <li><a href="generated/torch.Generator.html#torch.Generator.set_state">(torch.Generator method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.cuda.set_stream.html#torch.cuda.set_stream">set_stream() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.set_sync_debug_mode.html#torch.cuda.set_sync_debug_mode">set_sync_debug_mode() (in module torch.cuda)</a>
</li>
      <li><a href="distributed.html#torch.distributed.Store.set_timeout">set_timeout() (in module torch.distributed.Store)</a>
</li>
      <li><a href="generated/torch.set_warn_always.html#torch.set_warn_always">set_warn_always() (in module torch)</a>
</li>
      <li><a href="generated/torch.optim.SGD.html#torch.optim.SGD">SGD (class in torch.optim)</a>
</li>
      <li><a href="generated/torch.sgn.html#torch.sgn">sgn() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.sgn.html#torch.Tensor.sgn">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.sgn_.html#torch.Tensor.sgn_">sgn_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.share_memory">share_memory() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.share_memory">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.BFloat16Storage.share_memory_">share_memory_() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.share_memory_">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.share_memory_">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.share_memory_">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.share_memory_">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.share_memory_">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.share_memory_">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.share_memory_">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.share_memory_">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.share_memory_">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.share_memory_">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.share_memory_">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.share_memory_">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.share_memory_">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.share_memory_">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.share_memory_">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.share_memory_.html#torch.Tensor.share_memory_">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.BFloat16Storage.short">short() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.short">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.short">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.short">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.short">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.short">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.short">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.short">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.short">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.short">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.short">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.short">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.short">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.short">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.short">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.short">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.short.html#torch.Tensor.short">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="storage.html#torch.ShortStorage">ShortStorage (class in torch)</a>
</li>
      <li><a href="__config__.html#torch.__config__.show">show() (in module torch.__config__)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.shutdown">shutdown() (in module torch.distributed.rpc)</a>

      <ul>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.RendezvousHandler.shutdown">(torch.distributed.elastic.rendezvous.RendezvousHandler method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.Sigmoid.html#torch.nn.Sigmoid">Sigmoid (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.sigmoid.html#torch.sigmoid">sigmoid() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.nn.functional.sigmoid.html#torch.nn.functional.sigmoid">(in module torch.nn.functional)</a>
</li>
        <li><a href="generated/torch.Tensor.sigmoid.html#torch.Tensor.sigmoid">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.sigmoid_.html#torch.Tensor.sigmoid_">sigmoid_() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.SigmoidTransform">SigmoidTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="generated/torch.sign.html#torch.sign">sign() (in module torch)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.transforms.Transform.sign">(torch.distributions.transforms.Transform property)</a>
</li>
        <li><a href="generated/torch.Tensor.sign.html#torch.Tensor.sign">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.sign_.html#torch.Tensor.sign_">sign_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.signbit.html#torch.signbit">signbit() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.signbit.html#torch.Tensor.signbit">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.Measurement.significant_figures">significant_figures() (torch.utils.benchmark.Measurement property)</a>
</li>
      <li><a href="generated/torch.nn.SiLU.html#torch.nn.SiLU">SiLU (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.silu.html#torch.nn.functional.silu">silu() (in module torch.nn.functional)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.SimpleElasticAgent">SimpleElasticAgent (class in torch.distributed.elastic.agent.server)</a>
</li>
      <li><a href="generated/torch.sin.html#torch.sin">sin() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.sin.html#torch.Tensor.sin">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.sin_.html#torch.Tensor.sin_">sin_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.sinc.html#torch.sinc">sinc() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.sinc">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.sinc.html#torch.Tensor.sinc">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.sinc_.html#torch.Tensor.sinc_">sinc_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.sinh.html#torch.sinh">sinh() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.sinh.html#torch.Tensor.sinh">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.sinh_.html#torch.Tensor.sinh_">sinh_() (torch.Tensor method)</a>
</li>
      <li><a href="backends.html#torch.backends.cuda.size">size (torch.backends.cuda attribute)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.size">size() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.size">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.size">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.size">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.size">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.size">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.size">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.size">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.size">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.size">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.size">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.size">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.size">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.size">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.size">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.size">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.size.html#torch.Tensor.size">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.utils.skip_init.html#torch.nn.utils.skip_init">skip_init() (in module torch.nn.utils)</a>
</li>
      <li><a href="pipeline.html#torch.distributed.pipeline.sync.skip.skippable.skippable">skippable() (in module torch.distributed.pipeline.sync.skip.skippable)</a>
</li>
      <li><a href="generated/torch.slogdet.html#torch.slogdet">slogdet() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.slogdet.html#torch.linalg.slogdet">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.slogdet.html#torch.Tensor.slogdet">(torch.Tensor method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.smm.html#torch.smm">smm() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.smm.html#torch.Tensor.smm">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.smooth_l1_loss.html#torch.nn.functional.smooth_l1_loss">smooth_l1_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.SmoothL1Loss.html#torch.nn.SmoothL1Loss">SmoothL1Loss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.quasirandom.SobolEngine.html#torch.quasirandom.SobolEngine">SobolEngine (class in torch.quasirandom)</a>
</li>
      <li><a href="generated/torch.nn.functional.soft_margin_loss.html#torch.nn.functional.soft_margin_loss">soft_margin_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.SoftMarginLoss.html#torch.nn.SoftMarginLoss">SoftMarginLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.Softmax.html#torch.nn.Softmax">Softmax (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.softmax.html#torch.nn.functional.softmax">softmax() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="generated/torch.sparse.softmax.html#torch.sparse.softmax">(in module torch.sparse)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.Softmax2d.html#torch.nn.Softmax2d">Softmax2d (class in torch.nn)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.SoftmaxTransform">SoftmaxTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="generated/torch.nn.Softmin.html#torch.nn.Softmin">Softmin (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.softmin.html#torch.nn.functional.softmin">softmin() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.Softplus.html#torch.nn.Softplus">Softplus (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.softplus.html#torch.nn.functional.softplus">softplus() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.Softshrink.html#torch.nn.Softshrink">Softshrink (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.softshrink.html#torch.nn.functional.softshrink">softshrink() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.Softsign.html#torch.nn.Softsign">Softsign (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.softsign.html#torch.nn.functional.softsign">softsign() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.solve.html#torch.solve">solve() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.solve.html#torch.linalg.solve">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.solve.html#torch.Tensor.solve">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.sort.html#torch.sort">sort() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.sort.html#torch.Tensor.sort">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.sorted_indices">sorted_indices (torch.nn.utils.rnn.PackedSequence attribute)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.sparse_">sparse_() (in module torch.nn.init)</a>
</li>
      <li><a href="generated/torch.sparse_coo_tensor.html#torch.sparse_coo_tensor">sparse_coo_tensor() (in module torch)</a>
</li>
      <li><a href="generated/torch.sparse_csr_tensor.html#torch.sparse_csr_tensor">sparse_csr_tensor() (in module torch)</a>
</li>
      <li><a href="generated/torch.Tensor.sparse_dim.html#torch.Tensor.sparse_dim">sparse_dim() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.sparse_mask.html#torch.Tensor.sparse_mask">sparse_mask() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.sparse_resize_.html#torch.Tensor.sparse_resize_">sparse_resize_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.sparse_resize_and_clear_.html#torch.Tensor.sparse_resize_and_clear_">sparse_resize_and_clear_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.optim.SparseAdam.html#torch.optim.SparseAdam">SparseAdam (class in torch.optim)</a>
</li>
      <li><a href="multiprocessing.html#torch.multiprocessing.spawn">spawn() (in module torch.multiprocessing)</a>
</li>
      <li><a href="multiprocessing.html#torch.multiprocessing.SpawnContext">SpawnContext (class in torch.multiprocessing)</a>
</li>
      <li><a href="generated/torch.nn.utils.spectral_norm.html#torch.nn.utils.spectral_norm">spectral_norm() (in module torch.nn.utils)</a>

      <ul>
        <li><a href="generated/torch.nn.utils.parametrizations.spectral_norm.html#torch.nn.utils.parametrizations.spectral_norm">(in module torch.nn.utils.parametrizations)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.split.html#torch.split">split() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.split.html#torch.Tensor.split">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.sqrt.html#torch.sqrt">sqrt() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.sqrt.html#torch.Tensor.sqrt">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.sqrt_.html#torch.Tensor.sqrt_">sqrt_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.square.html#torch.square">square() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.square.html#torch.Tensor.square">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.square_.html#torch.Tensor.square_">square_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.squeeze.html#torch.squeeze">squeeze() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.squeeze.html#torch.Tensor.squeeze">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.squeeze_.html#torch.Tensor.squeeze_">squeeze_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.sspaddmm.html#torch.sspaddmm">sspaddmm() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.sspaddmm.html#torch.Tensor.sspaddmm">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.constraints.stack">stack (in module torch.distributions.constraints)</a>
</li>
      <li><a href="generated/torch.stack.html#torch.stack">stack() (in module torch)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.stack_trace">stack_trace() (torch.fx.Node property)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.StackTransform">StackTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="elastic/multiprocessing.html#torch.distributed.elastic.multiprocessing.start_processes">start_processes() (in module torch.distributed.elastic.multiprocessing)</a>
</li>
      <li><a href="pipeline.html#torch.distributed.pipeline.sync.skip.skippable.stash">stash (class in torch.distributed.pipeline.sync.skip.skippable)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.state_dict">state_dict() (torch.cuda.amp.GradScaler method)</a>

      <ul>
        <li><a href="distributed.optim.html#torch.distributed.optim.ZeroRedundancyOptimizer.state_dict">(torch.distributed.optim.ZeroRedundancyOptimizer method)</a>
</li>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.state_dict">(torch.jit.ScriptModule method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.state_dict">(torch.nn.Module method)</a>
</li>
        <li><a href="generated/torch.optim.Adadelta.html#torch.optim.Adadelta.state_dict">(torch.optim.Adadelta method)</a>
</li>
        <li><a href="generated/torch.optim.Adagrad.html#torch.optim.Adagrad.state_dict">(torch.optim.Adagrad method)</a>
</li>
        <li><a href="generated/torch.optim.Adam.html#torch.optim.Adam.state_dict">(torch.optim.Adam method)</a>
</li>
        <li><a href="generated/torch.optim.Adamax.html#torch.optim.Adamax.state_dict">(torch.optim.Adamax method)</a>
</li>
        <li><a href="generated/torch.optim.AdamW.html#torch.optim.AdamW.state_dict">(torch.optim.AdamW method)</a>
</li>
        <li><a href="generated/torch.optim.ASGD.html#torch.optim.ASGD.state_dict">(torch.optim.ASGD method)</a>
</li>
        <li><a href="generated/torch.optim.LBFGS.html#torch.optim.LBFGS.state_dict">(torch.optim.LBFGS method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.ChainedScheduler.html#torch.optim.lr_scheduler.ChainedScheduler.state_dict">(torch.optim.lr_scheduler.ChainedScheduler method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.ConstantLR.html#torch.optim.lr_scheduler.ConstantLR.state_dict">(torch.optim.lr_scheduler.ConstantLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingLR.html#torch.optim.lr_scheduler.CosineAnnealingLR.state_dict">(torch.optim.lr_scheduler.CosineAnnealingLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.html#torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.state_dict">(torch.optim.lr_scheduler.CosineAnnealingWarmRestarts method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CyclicLR.html#torch.optim.lr_scheduler.CyclicLR.state_dict">(torch.optim.lr_scheduler.CyclicLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.ExponentialLR.html#torch.optim.lr_scheduler.ExponentialLR.state_dict">(torch.optim.lr_scheduler.ExponentialLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.LambdaLR.html#torch.optim.lr_scheduler.LambdaLR.state_dict">(torch.optim.lr_scheduler.LambdaLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.LinearLR.html#torch.optim.lr_scheduler.LinearLR.state_dict">(torch.optim.lr_scheduler.LinearLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.MultiplicativeLR.html#torch.optim.lr_scheduler.MultiplicativeLR.state_dict">(torch.optim.lr_scheduler.MultiplicativeLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.MultiStepLR.html#torch.optim.lr_scheduler.MultiStepLR.state_dict">(torch.optim.lr_scheduler.MultiStepLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.OneCycleLR.html#torch.optim.lr_scheduler.OneCycleLR.state_dict">(torch.optim.lr_scheduler.OneCycleLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.SequentialLR.html#torch.optim.lr_scheduler.SequentialLR.state_dict">(torch.optim.lr_scheduler.SequentialLR method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.StepLR.html#torch.optim.lr_scheduler.StepLR.state_dict">(torch.optim.lr_scheduler.StepLR method)</a>
</li>
        <li><a href="generated/torch.optim.NAdam.html#torch.optim.NAdam.state_dict">(torch.optim.NAdam method)</a>
</li>
        <li><a href="generated/torch.optim.Optimizer.state_dict.html#torch.optim.Optimizer.state_dict">(torch.optim.Optimizer method)</a>
</li>
        <li><a href="generated/torch.optim.RAdam.html#torch.optim.RAdam.state_dict">(torch.optim.RAdam method)</a>
</li>
        <li><a href="generated/torch.optim.RMSprop.html#torch.optim.RMSprop.state_dict">(torch.optim.RMSprop method)</a>
</li>
        <li><a href="generated/torch.optim.Rprop.html#torch.optim.Rprop.state_dict">(torch.optim.Rprop method)</a>
</li>
        <li><a href="generated/torch.optim.SGD.html#torch.optim.SGD.state_dict">(torch.optim.SGD method)</a>
</li>
        <li><a href="generated/torch.optim.SparseAdam.html#torch.optim.SparseAdam.state_dict">(torch.optim.SparseAdam method)</a>
</li>
      </ul></li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.CallgrindStats.stats">stats() (torch.utils.benchmark.CallgrindStats method)</a>
</li>
      <li><a href="generated/torch.std.html#torch.std">std() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.std.html#torch.Tensor.std">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.std_mean.html#torch.std_mean">std_mean() (in module torch)</a>
</li>
      <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.stddev">stddev() (torch.distributions.continuous_bernoulli.ContinuousBernoulli property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.stddev">(torch.distributions.distribution.Distribution property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.stddev">(torch.distributions.exponential.Exponential property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gumbel.Gumbel.stddev">(torch.distributions.gumbel.Gumbel property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.stddev">(torch.distributions.laplace.Laplace property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.stddev">(torch.distributions.normal.Normal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.stddev">(torch.distributions.uniform.Uniform property)</a>
</li>
      </ul></li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.step">step() (torch.cuda.amp.GradScaler method)</a>

      <ul>
        <li><a href="rpc.html#torch.distributed.optim.DistributedOptimizer.step">(torch.distributed.optim.DistributedOptimizer method)</a>
</li>
        <li><a href="distributed.optim.html#torch.distributed.optim.ZeroRedundancyOptimizer.step">(torch.distributed.optim.ZeroRedundancyOptimizer method)</a>
</li>
        <li><a href="generated/torch.optim.Adadelta.html#torch.optim.Adadelta.step">(torch.optim.Adadelta method)</a>
</li>
        <li><a href="generated/torch.optim.Adagrad.html#torch.optim.Adagrad.step">(torch.optim.Adagrad method)</a>
</li>
        <li><a href="generated/torch.optim.Adam.html#torch.optim.Adam.step">(torch.optim.Adam method)</a>
</li>
        <li><a href="generated/torch.optim.Adamax.html#torch.optim.Adamax.step">(torch.optim.Adamax method)</a>
</li>
        <li><a href="generated/torch.optim.AdamW.html#torch.optim.AdamW.step">(torch.optim.AdamW method)</a>
</li>
        <li><a href="generated/torch.optim.ASGD.html#torch.optim.ASGD.step">(torch.optim.ASGD method)</a>
</li>
        <li><a href="generated/torch.optim.LBFGS.html#torch.optim.LBFGS.step">(torch.optim.LBFGS method)</a>
</li>
        <li><a href="generated/torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.html#torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.step">(torch.optim.lr_scheduler.CosineAnnealingWarmRestarts method)</a>
</li>
        <li><a href="generated/torch.optim.NAdam.html#torch.optim.NAdam.step">(torch.optim.NAdam method)</a>
</li>
        <li><a href="generated/torch.optim.Optimizer.step.html#torch.optim.Optimizer.step">(torch.optim.Optimizer method)</a>
</li>
        <li><a href="generated/torch.optim.RAdam.html#torch.optim.RAdam.step">(torch.optim.RAdam method)</a>
</li>
        <li><a href="generated/torch.optim.RMSprop.html#torch.optim.RMSprop.step">(torch.optim.RMSprop method)</a>
</li>
        <li><a href="generated/torch.optim.Rprop.html#torch.optim.Rprop.step">(torch.optim.Rprop method)</a>
</li>
        <li><a href="generated/torch.optim.SGD.html#torch.optim.SGD.step">(torch.optim.SGD method)</a>
</li>
        <li><a href="generated/torch.optim.SparseAdam.html#torch.optim.SparseAdam.step">(torch.optim.SparseAdam method)</a>
</li>
        <li><a href="profiler.html#torch.profiler.profile.step">(torch.profiler.profile method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.optim.lr_scheduler.StepLR.html#torch.optim.lr_scheduler.StepLR">StepLR (class in torch.optim.lr_scheduler)</a>
</li>
      <li><a href="generated/torch.stft.html#torch.stft">stft() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.stft.html#torch.Tensor.stft">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.transforms.StickBreakingTransform">StickBreakingTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="generated/torch.Tensor.storage.html#torch.Tensor.storage">storage() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.storage_offset.html#torch.Tensor.storage_offset">storage_offset() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.storage_type.html#torch.Tensor.storage_type">storage_type() (torch.Tensor method)</a>
</li>
      <li><a href="distributed.html#torch.distributed.Store">Store (class in torch.distributed)</a>
</li>
      <li><a href="generated/torch.cuda.Stream.html#torch.cuda.Stream">Stream (class in torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.stream.html#torch.cuda.stream">stream() (in module torch.cuda)</a>
</li>
      <li><a href="generated/torch.cuda.StreamContext.html#torch.cuda.StreamContext">StreamContext (class in torch.cuda)</a>
</li>
      <li><a href="generated/torch.Tensor.stride.html#torch.Tensor.stride">stride() (torch.Tensor method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.studentT.StudentT">StudentT (class in torch.distributions.studentT)</a>
</li>
      <li><a href="generated/torch.sub.html#torch.sub">sub() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.sub.html#torch.Tensor.sub">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.sub_.html#torch.Tensor.sub_">sub_() (torch.Tensor method)</a>
</li>
      <li><a href="elastic/multiprocessing.html#torch.distributed.elastic.multiprocessing.api.SubprocessContext">SubprocessContext (class in torch.distributed.elastic.multiprocessing.api)</a>
</li>
      <li><a href="data.html#torch.utils.data.Subset">Subset (class in torch.utils.data)</a>
</li>
      <li><a href="data.html#torch.utils.data.SubsetRandomSampler">SubsetRandomSampler (class in torch.utils.data)</a>
</li>
      <li><a href="generated/torch.subtract.html#torch.subtract">subtract() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.subtract.html#torch.Tensor.subtract">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.subtract_.html#torch.Tensor.subtract_">subtract_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.sum.html#torch.sum">sum() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.sparse.sum.html#torch.sparse.sum">(in module torch.sparse)</a>
</li>
        <li><a href="generated/torch.Tensor.sum.html#torch.Tensor.sum">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.sum_to_size.html#torch.Tensor.sum_to_size">sum_to_size() (torch.Tensor method)</a>
</li>
      <li><a href="tensorboard.html#torch.utils.tensorboard.writer.SummaryWriter">SummaryWriter (class in torch.utils.tensorboard.writer)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.support">support (torch.distributions.bernoulli.Bernoulli attribute)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.beta.Beta.support">(torch.distributions.beta.Beta attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.support">(torch.distributions.cauchy.Cauchy attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.support">(torch.distributions.continuous_bernoulli.ContinuousBernoulli attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet.support">(torch.distributions.dirichlet.Dirichlet attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.support">(torch.distributions.exponential.Exponential attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.fishersnedecor.FisherSnedecor.support">(torch.distributions.fishersnedecor.FisherSnedecor attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gamma.Gamma.support">(torch.distributions.gamma.Gamma attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.geometric.Geometric.support">(torch.distributions.geometric.Geometric attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gumbel.Gumbel.support">(torch.distributions.gumbel.Gumbel attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.support">(torch.distributions.half_cauchy.HalfCauchy attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.support">(torch.distributions.half_normal.HalfNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.kumaraswamy.Kumaraswamy.support">(torch.distributions.kumaraswamy.Kumaraswamy attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.support">(torch.distributions.laplace.Laplace attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lkj_cholesky.LKJCholesky.support">(torch.distributions.lkj_cholesky.LKJCholesky attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.log_normal.LogNormal.support">(torch.distributions.log_normal.LogNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.support">(torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.support">(torch.distributions.multivariate_normal.MultivariateNormal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.support">(torch.distributions.negative_binomial.NegativeBinomial attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.support">(torch.distributions.normal.Normal attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.support">(torch.distributions.one_hot_categorical.OneHotCategorical attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.poisson.Poisson.support">(torch.distributions.poisson.Poisson attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli.support">(torch.distributions.relaxed_bernoulli.LogitRelaxedBernoulli attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.RelaxedBernoulli.support">(torch.distributions.relaxed_bernoulli.RelaxedBernoulli attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.relaxed_categorical.RelaxedOneHotCategorical.support">(torch.distributions.relaxed_categorical.RelaxedOneHotCategorical attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.studentT.StudentT.support">(torch.distributions.studentT.StudentT attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.von_mises.VonMises.support">(torch.distributions.von_mises.VonMises attribute)</a>
</li>
        <li><a href="distributions.html#torch.distributions.weibull.Weibull.support">(torch.distributions.weibull.Weibull attribute)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.binomial.Binomial.support">support() (torch.distributions.binomial.Binomial property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.support">(torch.distributions.categorical.Categorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.support">(torch.distributions.distribution.Distribution property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.independent.Independent.support">(torch.distributions.independent.Independent property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.support">(torch.distributions.mixture_same_family.MixtureSameFamily property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.support">(torch.distributions.multinomial.Multinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.pareto.Pareto.support">(torch.distributions.pareto.Pareto property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution.support">(torch.distributions.transformed_distribution.TransformedDistribution property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.support">(torch.distributions.uniform.Uniform property)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.svd.html#torch.svd">svd() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.linalg.svd.html#torch.linalg.svd">(in module torch.linalg)</a>
</li>
        <li><a href="generated/torch.Tensor.svd.html#torch.Tensor.svd">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.svd_lowrank.html#torch.svd_lowrank">svd_lowrank() (in module torch)</a>
</li>
      <li><a href="generated/torch.linalg.svdvals.html#torch.linalg.svdvals">svdvals() (in module torch.linalg)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.swap_module">swap_module() (in module torch.quantization)</a>
</li>
      <li><a href="generated/torch.swapaxes.html#torch.swapaxes">swapaxes() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.swapaxes.html#torch.Tensor.swapaxes">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.swapdims.html#torch.swapdims">swapdims() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.swapdims.html#torch.Tensor.swapdims">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.symbolic_trace">symbolic_trace() (in module torch.fx)</a>
</li>
      <li><a href="generated/torch.symeig.html#torch.symeig">symeig() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.symeig.html#torch.Tensor.symeig">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.SyncBatchNorm.html#torch.nn.SyncBatchNorm">SyncBatchNorm (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.cuda.synchronize.html#torch.cuda.synchronize">synchronize() (in module torch.cuda)</a>

      <ul>
        <li><a href="generated/torch.cuda.Event.html#torch.cuda.Event.synchronize">(torch.cuda.Event method)</a>
</li>
        <li><a href="generated/torch.cuda.Stream.html#torch.cuda.Stream.synchronize">(torch.cuda.Stream method)</a>
</li>
      </ul></li>
  </ul></td>
</tr></table>

<h2 id="T">T</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="tensors.html#torch.Tensor.T">T (torch.Tensor attribute)</a>
</li>
      <li><a href="generated/torch.t.html#torch.t">t() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.t.html#torch.Tensor.t">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.t_.html#torch.Tensor.t_">t_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.take.html#torch.take">take() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.take.html#torch.Tensor.take">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.take_along_dim.html#torch.take_along_dim">take_along_dim() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.take_along_dim.html#torch.Tensor.take_along_dim">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.tan.html#torch.tan">tan() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.tan.html#torch.Tensor.tan">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.tan_.html#torch.Tensor.tan_">tan_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.Tanh.html#torch.nn.Tanh">Tanh (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.tanh.html#torch.tanh">tanh() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.nn.functional.tanh.html#torch.nn.functional.tanh">(in module torch.nn.functional)</a>
</li>
        <li><a href="generated/torch.Tensor.tanh.html#torch.Tensor.tanh">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.tanh_.html#torch.Tensor.tanh_">tanh_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.nn.Tanhshrink.html#torch.nn.Tanhshrink">Tanhshrink (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.tanhshrink.html#torch.nn.functional.tanhshrink">tanhshrink() (in module torch.nn.functional)</a>
</li>
      <li><a href="distributions.html#torch.distributions.transforms.TanhTransform">TanhTransform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="distributed.html#torch.distributed.TCPStore">TCPStore (class in torch.distributed)</a>
</li>
      <li><a href="distributions.html#torch.distributions.relaxed_bernoulli.RelaxedBernoulli.temperature">temperature() (torch.distributions.relaxed_bernoulli.RelaxedBernoulli property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.relaxed_categorical.RelaxedOneHotCategorical.temperature">(torch.distributions.relaxed_categorical.RelaxedOneHotCategorical property)</a>
</li>
      </ul></li>
      <li><a href="tensors.html#torch.Tensor">Tensor (class in torch)</a>
</li>
      <li><a href="generated/torch.tensor.html#torch.tensor">tensor() (in module torch)</a>
</li>
      <li><a href="generated/torch.tensor_split.html#torch.tensor_split">tensor_split() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.tensor_split.html#torch.Tensor.tensor_split">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="profiler.html#torch.profiler.tensorboard_trace_handler">tensorboard_trace_handler() (in module torch.profiler)</a>
</li>
      <li><a href="data.html#torch.utils.data.TensorDataset">TensorDataset (class in torch.utils.data)</a>
</li>
      <li><a href="generated/torch.tensordot.html#torch.tensordot">tensordot() (in module torch)</a>
</li>
      <li><a href="generated/torch.linalg.tensorinv.html#torch.linalg.tensorinv">tensorinv() (in module torch.linalg)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.TensorPipeRpcBackendOptions">TensorPipeRpcBackendOptions (class in torch.distributed.rpc)</a>
</li>
      <li><a href="generated/torch.linalg.tensorsolve.html#torch.linalg.tensorsolve">tensorsolve() (in module torch.linalg)</a>
</li>
      <li><a href="futures.html#torch.futures.Future.then">then() (torch.futures.Future method)</a>
</li>
      <li><a href="generated/torch.nn.Threshold.html#torch.nn.Threshold">Threshold (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.threshold.html#torch.nn.functional.threshold">threshold() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.threshold_.html#torch.nn.functional.threshold_">threshold_() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.tile.html#torch.tile">tile() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.tile.html#torch.Tensor.tile">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.Timer.timeit">timeit() (torch.utils.benchmark.Timer method)</a>
</li>
      <li><a href="benchmark_utils.html#torch.utils.benchmark.Timer">Timer (class in torch.utils.benchmark)</a>
</li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.TimerClient">TimerClient (class in torch.distributed.elastic.timer)</a>
</li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.TimerRequest">TimerRequest (class in torch.distributed.elastic.timer)</a>
</li>
      <li><a href="elastic/timer.html#torch.distributed.elastic.timer.TimerServer">TimerServer (class in torch.distributed.elastic.timer)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.to">to() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.to">(torch.nn.Module method)</a>
</li>
        <li><a href="generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.to">(torch.nn.utils.rnn.PackedSequence method)</a>
</li>
        <li><a href="generated/torch.Tensor.to.html#torch.Tensor.to">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Tracer.to_bool">to_bool() (torch.fx.Tracer method)</a>
</li>
      <li><a href="generated/torch.Tensor.to_dense.html#torch.Tensor.to_dense">to_dense() (torch.Tensor method)</a>
</li>
      <li><a href="dlpack.html#torch.utils.dlpack.to_dlpack">to_dlpack() (in module torch.utils.dlpack)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.to_empty">to_empty() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.to_empty">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.GraphModule.to_folder">to_folder() (torch.fx.GraphModule method)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.RRef.to_here">to_here() (torch.distributed.rpc.RRef method)</a>
</li>
      <li><a href="generated/torch.Tensor.to_mkldnn.html#torch.Tensor.to_mkldnn">to_mkldnn() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.to_sparse.html#torch.Tensor.to_sparse">to_sparse() (torch.Tensor method)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.tolist">tolist() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.tolist">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.tolist">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.tolist">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.tolist">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.tolist">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.tolist">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.tolist">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.tolist">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.tolist">(torch.IntStorage method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.tolist">(torch.LongStorage method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.tolist">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.tolist">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.tolist">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.tolist">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.tolist">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.tolist.html#torch.Tensor.tolist">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.topk.html#torch.topk">topk() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.topk.html#torch.Tensor.topk">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li>
    torch.__config__

      <ul>
        <li><a href="__config__.html#module-torch.__config__">module</a>
</li>
      </ul></li>
      <li>
    torch.autograd

      <ul>
        <li><a href="autograd.html#module-torch.autograd">module</a>
</li>
      </ul></li>
      <li>
    torch.cuda

      <ul>
        <li><a href="cuda.html#module-torch.cuda">module</a>
</li>
      </ul></li>
      <li>
    torch.cuda.amp

      <ul>
        <li><a href="amp.html#module-torch.cuda.amp">module</a>
</li>
      </ul></li>
      <li><a href="tensor_attributes.html#torch.torch.device">torch.device (class in torch)</a>
</li>
      <li>
    torch.distributed

      <ul>
        <li><a href="distributed.html#module-torch.distributed">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.autograd

      <ul>
        <li><a href="rpc.html#module-torch.distributed.autograd">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.elastic.agent

      <ul>
        <li><a href="elastic/agent.html#module-torch.distributed.elastic.agent">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.elastic.agent.server

      <ul>
        <li><a href="elastic/agent.html#module-torch.distributed.elastic.agent.server">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.elastic.events

      <ul>
        <li><a href="elastic/events.html#module-torch.distributed.elastic.events">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.elastic.metrics

      <ul>
        <li><a href="elastic/metrics.html#module-torch.distributed.elastic.metrics">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.elastic.multiprocessing

      <ul>
        <li><a href="elastic/multiprocessing.html#module-torch.distributed.elastic.multiprocessing">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.elastic.multiprocessing.errors

      <ul>
        <li><a href="elastic/errors.html#module-torch.distributed.elastic.multiprocessing.errors">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.elastic.rendezvous

      <ul>
        <li><a href="elastic/rendezvous.html#module-torch.distributed.elastic.rendezvous">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.elastic.rendezvous.registry

      <ul>
        <li><a href="elastic/rendezvous.html#module-torch.distributed.elastic.rendezvous.registry">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.elastic.timer

      <ul>
        <li><a href="elastic/timer.html#module-torch.distributed.elastic.timer">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.launch

      <ul>
        <li><a href="distributed.html#module-torch.distributed.launch">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.optim

      <ul>
        <li><a href="rpc.html#module-torch.distributed.optim">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.rpc

      <ul>
        <li><a href="rpc.html#module-torch.distributed.rpc">module</a>
</li>
      </ul></li>
      <li>
    torch.distributed.run

      <ul>
        <li><a href="elastic/run.html#module-torch.distributed.run">module</a>
</li>
      </ul></li>
      <li>
    torch.distributions

      <ul>
        <li><a href="distributions.html#module-torch.distributions">module</a>
</li>
      </ul></li>
      <li>
    torch.distributions.constraint_registry

      <ul>
        <li><a href="distributions.html#module-torch.distributions.constraint_registry">module</a>
</li>
      </ul></li>
      <li>
    torch.distributions.constraints

      <ul>
        <li><a href="distributions.html#module-torch.distributions.constraints">module</a>
</li>
      </ul></li>
      <li>
    torch.distributions.kl

      <ul>
        <li><a href="distributions.html#module-torch.distributions.kl">module</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li>
    torch.distributions.transforms

      <ul>
        <li><a href="distributions.html#module-torch.distributions.transforms">module</a>
</li>
      </ul></li>
      <li><a href="tensor_attributes.html#torch.torch.dtype">torch.dtype (class in torch)</a>
</li>
      <li><a href="type_info.html#torch.torch.finfo">torch.finfo (class in torch)</a>
</li>
      <li>
    torch.futures

      <ul>
        <li><a href="futures.html#module-torch.futures">module</a>
</li>
      </ul></li>
      <li>
    torch.fx

      <ul>
        <li><a href="fx.html#module-torch.fx">module</a>
</li>
      </ul></li>
      <li>
    torch.hub

      <ul>
        <li><a href="hub.html#module-torch.hub">module</a>
</li>
      </ul></li>
      <li><a href="type_info.html#torch.torch.iinfo">torch.iinfo (class in torch)</a>
</li>
      <li>
    torch.jit

      <ul>
        <li><a href="jit.html#module-torch.jit">module</a>
</li>
      </ul></li>
      <li>
    torch.jit.supported_ops

      <ul>
        <li><a href="jit_builtin_functions.html#module-torch.jit.supported_ops">module</a>
</li>
      </ul></li>
      <li>
    torch.jit.unsupported_tensor_ops

      <ul>
        <li><a href="jit_unsupported.html#module-torch.jit.unsupported_tensor_ops">module</a>
</li>
      </ul></li>
      <li><a href="tensor_attributes.html#torch.torch.layout">torch.layout (class in torch)</a>
</li>
      <li>
    torch.linalg

      <ul>
        <li><a href="linalg.html#module-torch.linalg">module</a>
</li>
      </ul></li>
      <li><a href="tensor_attributes.html#torch.torch.memory_format">torch.memory_format (class in torch)</a>
</li>
      <li>
    torch.multiprocessing

      <ul>
        <li><a href="multiprocessing.html#module-torch.multiprocessing">module</a>
</li>
      </ul></li>
      <li>
    torch.nn.intrinsic

      <ul>
        <li><a href="torch.nn.intrinsic.html#module-torch.nn.intrinsic">module</a>
</li>
      </ul></li>
      <li>
    torch.nn.intrinsic.qat

      <ul>
        <li><a href="torch.nn.intrinsic.qat.html#module-torch.nn.intrinsic.qat">module</a>
</li>
      </ul></li>
      <li>
    torch.nn.intrinsic.quantized

      <ul>
        <li><a href="torch.nn.intrinsic.quantized.html#module-torch.nn.intrinsic.quantized">module</a>
</li>
      </ul></li>
      <li>
    torch.nn.qat

      <ul>
        <li><a href="torch.nn.qat.html#module-torch.nn.qat">module</a>
</li>
      </ul></li>
      <li>
    torch.nn.quantized

      <ul>
        <li><a href="torch.nn.quantized.html#module-torch.nn.quantized">module</a>
</li>
      </ul></li>
      <li>
    torch.nn.quantized.dynamic

      <ul>
        <li><a href="torch.nn.quantized.dynamic.html#module-torch.nn.quantized.dynamic">module</a>
</li>
      </ul></li>
      <li>
    torch.nn.quantized.functional

      <ul>
        <li><a href="torch.nn.quantized.html#module-torch.nn.quantized.functional">module</a>
</li>
      </ul></li>
      <li>
    torch.onnx

      <ul>
        <li><a href="onnx.html#module-torch.onnx">module</a>
</li>
      </ul></li>
      <li>
    torch.optim

      <ul>
        <li><a href="optim.html#module-torch.optim">module</a>
</li>
      </ul></li>
      <li>
    torch.profiler

      <ul>
        <li><a href="profiler.html#module-torch.profiler">module</a>
</li>
      </ul></li>
      <li>
    torch.quantization

      <ul>
        <li><a href="torch.quantization.html#module-torch.quantization">module</a>
</li>
      </ul></li>
      <li>
    torch.random

      <ul>
        <li><a href="random.html#module-torch.random">module</a>
</li>
      </ul></li>
      <li>
    torch.testing

      <ul>
        <li><a href="testing.html#module-torch.testing">module</a>
</li>
      </ul></li>
      <li>
    torch.utils.benchmark

      <ul>
        <li><a href="benchmark_utils.html#module-torch.utils.benchmark">module</a>
</li>
      </ul></li>
      <li>
    torch.utils.data

      <ul>
        <li><a href="data.html#module-torch.utils.data">module</a>
</li>
      </ul></li>
      <li>
    torch.utils.model_zoo

      <ul>
        <li><a href="model_zoo.html#module-torch.utils.model_zoo">module</a>
</li>
      </ul></li>
      <li><a href="generated/torch.autograd.profiler.profile.total_average.html#torch.autograd.profiler.profile.total_average">total_average() (torch.autograd.profiler.profile method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.total_count">total_count (torch.distributions.multinomial.Multinomial attribute)</a>
</li>
      <li><a href="generated/torch.trace.html#torch.trace">trace() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.jit.trace.html#torch.jit.trace">(in module torch.jit)</a>
</li>
        <li><a href="fx.html#torch.fx.Tracer.trace">(torch.fx.Tracer method)</a>
</li>
        <li><a href="generated/torch.Tensor.trace.html#torch.Tensor.trace">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.jit.trace_module.html#torch.jit.trace_module">trace_module() (in module torch.jit)</a>
</li>
      <li><a href="fx.html#torch.fx.Tracer">Tracer (class in torch.fx)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.train">train() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.train">(torch.nn.Module method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.transforms.Transform">Transform (class in torch.distributions.transforms)</a>
</li>
      <li><a href="fx.html#torch.fx.Transformer.transform">transform() (torch.fx.Transformer method)</a>

      <ul>
        <li><a href="benchmark_utils.html#torch.utils.benchmark.FunctionCounts.transform">(torch.utils.benchmark.FunctionCounts method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.transformed_distribution.TransformedDistribution">TransformedDistribution (class in torch.distributions.transformed_distribution)</a>
</li>
      <li><a href="fx.html#torch.fx.Transformer">Transformer (class in torch.fx)</a>

      <ul>
        <li><a href="generated/torch.nn.Transformer.html#torch.nn.Transformer">(class in torch.nn)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.TransformerDecoder.html#torch.nn.TransformerDecoder">TransformerDecoder (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.TransformerDecoderLayer.html#torch.nn.TransformerDecoderLayer">TransformerDecoderLayer (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.TransformerEncoder.html#torch.nn.TransformerEncoder">TransformerEncoder (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.TransformerEncoderLayer.html#torch.nn.TransformerEncoderLayer">TransformerEncoderLayer (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.transpose.html#torch.transpose">transpose() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.transpose.html#torch.Tensor.transpose">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.transpose_.html#torch.Tensor.transpose_">transpose_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.trapezoid.html#torch.trapezoid">trapezoid() (in module torch)</a>
</li>
      <li><a href="generated/torch.trapz.html#torch.trapz">trapz() (in module torch)</a>
</li>
      <li><a href="generated/torch.triangular_solve.html#torch.triangular_solve">triangular_solve() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.triangular_solve.html#torch.Tensor.triangular_solve">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.tril.html#torch.tril">tril() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.tril.html#torch.Tensor.tril">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.tril_.html#torch.Tensor.tril_">tril_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.tril_indices.html#torch.tril_indices">tril_indices() (in module torch)</a>
</li>
      <li><a href="generated/torch.nn.functional.triplet_margin_loss.html#torch.nn.functional.triplet_margin_loss">triplet_margin_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.functional.triplet_margin_with_distance_loss.html#torch.nn.functional.triplet_margin_with_distance_loss">triplet_margin_with_distance_loss() (in module torch.nn.functional)</a>
</li>
      <li><a href="generated/torch.nn.TripletMarginLoss.html#torch.nn.TripletMarginLoss">TripletMarginLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.TripletMarginWithDistanceLoss.html#torch.nn.TripletMarginWithDistanceLoss">TripletMarginWithDistanceLoss (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.triu.html#torch.triu">triu() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.triu.html#torch.Tensor.triu">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.triu_.html#torch.Tensor.triu_">triu_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.triu_indices.html#torch.triu_indices">triu_indices() (in module torch)</a>
</li>
      <li><a href="generated/torch.true_divide.html#torch.true_divide">true_divide() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.true_divide.html#torch.Tensor.true_divide">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.true_divide_.html#torch.Tensor.true_divide_">true_divide_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.trunc.html#torch.trunc">trunc() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.trunc.html#torch.Tensor.trunc">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.trunc_.html#torch.Tensor.trunc_">trunc_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.jit.Attribute.html#torch.jit.Attribute.type">type (torch.jit.Attribute attribute)</a>
</li>
      <li><a href="storage.html#torch.BFloat16Storage.type">type() (torch.BFloat16Storage method)</a>

      <ul>
        <li><a href="storage.html#torch.BoolStorage.type">(torch.BoolStorage method)</a>
</li>
        <li><a href="storage.html#torch.ByteStorage.type">(torch.ByteStorage method)</a>
</li>
        <li><a href="storage.html#torch.CharStorage.type">(torch.CharStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexDoubleStorage.type">(torch.ComplexDoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.ComplexFloatStorage.type">(torch.ComplexFloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.DoubleStorage.type">(torch.DoubleStorage method)</a>
</li>
        <li><a href="storage.html#torch.FloatStorage.type">(torch.FloatStorage method)</a>
</li>
        <li><a href="storage.html#torch.HalfStorage.type">(torch.HalfStorage method)</a>
</li>
        <li><a href="storage.html#torch.IntStorage.type">(torch.IntStorage method)</a>
</li>
        <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.type">(torch.jit.ScriptModule method)</a>
</li>
        <li><a href="storage.html#torch.LongStorage.type">(torch.LongStorage method)</a>
</li>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.type">(torch.nn.Module method)</a>
</li>
        <li><a href="storage.html#torch.QInt32Storage.type">(torch.QInt32Storage method)</a>
</li>
        <li><a href="storage.html#torch.QInt8Storage.type">(torch.QInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt4x2Storage.type">(torch.QUInt4x2Storage method)</a>
</li>
        <li><a href="storage.html#torch.QUInt8Storage.type">(torch.QUInt8Storage method)</a>
</li>
        <li><a href="storage.html#torch.ShortStorage.type">(torch.ShortStorage method)</a>
</li>
        <li><a href="generated/torch.Tensor.type.html#torch.Tensor.type">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.type_as.html#torch.Tensor.type_as">type_as() (torch.Tensor method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="U">U</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.unbind.html#torch.unbind">unbind() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.unbind.html#torch.Tensor.unbind">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.Unflatten.html#torch.nn.Unflatten">Unflatten (class in torch.nn)</a>
</li>
      <li><a href="named_tensor.html#torch.Tensor.unflatten">unflatten() (torch.Tensor method)</a>
</li>
      <li><a href="fx.html#torch.fx.Graph.unflatten_outs">unflatten_outs() (torch.fx.Graph method)</a>
</li>
      <li><a href="generated/torch.nn.Unfold.html#torch.nn.Unfold">Unfold (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.unfold.html#torch.nn.functional.unfold">unfold() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="generated/torch.Tensor.unfold.html#torch.Tensor.unfold">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="distributions.html#torch.distributions.uniform.Uniform">Uniform (class in torch.distributions.uniform)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.uniform_">uniform_() (in module torch.nn.init)</a>

      <ul>
        <li><a href="generated/torch.Tensor.uniform_.html#torch.Tensor.uniform_">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.parameter.UninitializedBuffer.html#torch.nn.parameter.UninitializedBuffer">UninitializedBuffer (class in torch.nn.parameter)</a>
</li>
      <li><a href="generated/torch.nn.parameter.UninitializedParameter.html#torch.nn.parameter.UninitializedParameter">UninitializedParameter (class in torch.nn.parameter)</a>
</li>
      <li><a href="generated/torch.unique.html#torch.unique">unique() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.unique.html#torch.Tensor.unique">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.unique_consecutive.html#torch.unique_consecutive">unique_consecutive() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.unique_consecutive.html#torch.Tensor.unique_consecutive">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.unscale_">unscale_() (torch.cuda.amp.GradScaler method)</a>
</li>
      <li><a href="generated/torch.nn.utils.rnn.PackedSequence.html#torch.nn.utils.rnn.PackedSequence.unsorted_indices">unsorted_indices (torch.nn.utils.rnn.PackedSequence attribute)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.unsqueeze.html#torch.unsqueeze">unsqueeze() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.unsqueeze.html#torch.Tensor.unsqueeze">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.Tensor.unsqueeze_.html#torch.Tensor.unsqueeze_">unsqueeze_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.jit.unused.html#torch.jit.unused">unused() (in module torch.jit)</a>
</li>
      <li><a href="amp.html#torch.cuda.amp.GradScaler.update">update() (torch.cuda.amp.GradScaler method)</a>

      <ul>
        <li><a href="generated/torch.nn.ModuleDict.html#torch.nn.ModuleDict.update">(torch.nn.ModuleDict method)</a>
</li>
        <li><a href="generated/torch.nn.ParameterDict.html#torch.nn.ParameterDict.update">(torch.nn.ParameterDict method)</a>
</li>
      </ul></li>
      <li><a href="fx.html#torch.fx.Node.update_arg">update_arg() (torch.fx.Node method)</a>
</li>
      <li><a href="fx.html#torch.fx.Node.update_kwarg">update_kwarg() (torch.fx.Node method)</a>
</li>
      <li><a href="generated/torch.nn.Upsample.html#torch.nn.Upsample">Upsample (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.functional.upsample.html#torch.nn.functional.upsample">upsample() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.upsample">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.upsample_bilinear.html#torch.nn.functional.upsample_bilinear">upsample_bilinear() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.upsample_bilinear">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.functional.upsample_nearest.html#torch.nn.functional.upsample_nearest">upsample_nearest() (in module torch.nn.functional)</a>

      <ul>
        <li><a href="torch.nn.quantized.html#torch.nn.quantized.functional.upsample_nearest">(in module torch.nn.quantized.functional)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.nn.UpsamplingBilinear2d.html#torch.nn.UpsamplingBilinear2d">UpsamplingBilinear2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.nn.UpsamplingNearest2d.html#torch.nn.UpsamplingNearest2d">UpsamplingNearest2d (class in torch.nn)</a>
</li>
      <li><a href="generated/torch.use_deterministic_algorithms.html#torch.use_deterministic_algorithms">use_deterministic_algorithms() (in module torch)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="V">V</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.jit.Attribute.html#torch.jit.Attribute.value">value (torch.jit.Attribute attribute)</a>
</li>
      <li><a href="futures.html#torch.futures.Future.value">value() (torch.futures.Future method)</a>
</li>
      <li><a href="generated/torch.nn.ModuleDict.html#torch.nn.ModuleDict.values">values() (torch.nn.ModuleDict method)</a>

      <ul>
        <li><a href="generated/torch.nn.ParameterDict.html#torch.nn.ParameterDict.values">(torch.nn.ParameterDict method)</a>
</li>
        <li><a href="generated/torch.Tensor.values.html#torch.Tensor.values">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.vander.html#torch.vander">vander() (in module torch)</a>
</li>
      <li><a href="generated/torch.var.html#torch.var">var() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.var.html#torch.Tensor.var">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.var_mean.html#torch.var_mean">var_mean() (in module torch)</a>
</li>
      <li><a href="distributions.html#torch.distributions.bernoulli.Bernoulli.variance">variance() (torch.distributions.bernoulli.Bernoulli property)</a>

      <ul>
        <li><a href="distributions.html#torch.distributions.beta.Beta.variance">(torch.distributions.beta.Beta property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.binomial.Binomial.variance">(torch.distributions.binomial.Binomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.categorical.Categorical.variance">(torch.distributions.categorical.Categorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.cauchy.Cauchy.variance">(torch.distributions.cauchy.Cauchy property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.continuous_bernoulli.ContinuousBernoulli.variance">(torch.distributions.continuous_bernoulli.ContinuousBernoulli property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.dirichlet.Dirichlet.variance">(torch.distributions.dirichlet.Dirichlet property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.distribution.Distribution.variance">(torch.distributions.distribution.Distribution property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.exponential.Exponential.variance">(torch.distributions.exponential.Exponential property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.fishersnedecor.FisherSnedecor.variance">(torch.distributions.fishersnedecor.FisherSnedecor property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gamma.Gamma.variance">(torch.distributions.gamma.Gamma property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.geometric.Geometric.variance">(torch.distributions.geometric.Geometric property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.gumbel.Gumbel.variance">(torch.distributions.gumbel.Gumbel property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_cauchy.HalfCauchy.variance">(torch.distributions.half_cauchy.HalfCauchy property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.half_normal.HalfNormal.variance">(torch.distributions.half_normal.HalfNormal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.independent.Independent.variance">(torch.distributions.independent.Independent property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.kumaraswamy.Kumaraswamy.variance">(torch.distributions.kumaraswamy.Kumaraswamy property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.laplace.Laplace.variance">(torch.distributions.laplace.Laplace property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.log_normal.LogNormal.variance">(torch.distributions.log_normal.LogNormal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal.variance">(torch.distributions.lowrank_multivariate_normal.LowRankMultivariateNormal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.mixture_same_family.MixtureSameFamily.variance">(torch.distributions.mixture_same_family.MixtureSameFamily property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multinomial.Multinomial.variance">(torch.distributions.multinomial.Multinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.multivariate_normal.MultivariateNormal.variance">(torch.distributions.multivariate_normal.MultivariateNormal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.negative_binomial.NegativeBinomial.variance">(torch.distributions.negative_binomial.NegativeBinomial property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.normal.Normal.variance">(torch.distributions.normal.Normal property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.one_hot_categorical.OneHotCategorical.variance">(torch.distributions.one_hot_categorical.OneHotCategorical property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.pareto.Pareto.variance">(torch.distributions.pareto.Pareto property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.poisson.Poisson.variance">(torch.distributions.poisson.Poisson property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.studentT.StudentT.variance">(torch.distributions.studentT.StudentT property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.uniform.Uniform.variance">(torch.distributions.uniform.Uniform property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.von_mises.VonMises.variance">(torch.distributions.von_mises.VonMises property)</a>
</li>
        <li><a href="distributions.html#torch.distributions.weibull.Weibull.variance">(torch.distributions.weibull.Weibull property)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.vdot.html#torch.vdot">vdot() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.vdot.html#torch.Tensor.vdot">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.linalg.vector_norm.html#torch.linalg.vector_norm">vector_norm() (in module torch.linalg)</a>
</li>
      <li><a href="generated/torch.nn.utils.vector_to_parameters.html#torch.nn.utils.vector_to_parameters">vector_to_parameters() (in module torch.nn.utils)</a>
</li>
      <li><a href="cpp_extension.html#torch.utils.cpp_extension.verify_ninja_availability">verify_ninja_availability() (in module torch.utils.cpp_extension)</a>
</li>
      <li><a href="pipeline.html#torch.distributed.pipeline.sync.skip.skippable.verify_skippables">verify_skippables() (in module torch.distributed.pipeline.sync.skip.skippable)</a>
</li>
      <li><a href="backends.html#torch.backends.cudnn.version">version() (in module torch.backends.cudnn)</a>
</li>
      <li><a href="generated/torch.autograd.functional.vhp.html#torch.autograd.functional.vhp">vhp() (in module torch.autograd.functional)</a>
</li>
      <li><a href="generated/torch.Tensor.view.html#torch.Tensor.view">view() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.Tensor.view_as.html#torch.Tensor.view_as">view_as() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.view_as_complex.html#torch.view_as_complex">view_as_complex() (in module torch)</a>
</li>
      <li><a href="generated/torch.view_as_real.html#torch.view_as_real">view_as_real() (in module torch)</a>
</li>
      <li><a href="generated/torch.autograd.functional.vjp.html#torch.autograd.functional.vjp">vjp() (in module torch.autograd.functional)</a>
</li>
      <li><a href="distributions.html#torch.distributions.von_mises.VonMises">VonMises (class in torch.distributions.von_mises)</a>
</li>
      <li><a href="generated/torch.vsplit.html#torch.vsplit">vsplit() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.vsplit.html#torch.Tensor.vsplit">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="generated/torch.vstack.html#torch.vstack">vstack() (in module torch)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="W">W</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="distributed.html#torch.distributed.Store.wait">wait() (in module torch.distributed.Store)</a>

      <ul>
        <li><a href="generated/torch.jit.wait.html#torch.jit.wait">(in module torch.jit)</a>
</li>
        <li><a href="generated/torch.cuda.Event.html#torch.cuda.Event.wait">(torch.cuda.Event method)</a>
</li>
        <li><a href="elastic/rendezvous.html#torch.distributed.elastic.rendezvous.etcd_store.EtcdStore.wait">(torch.distributed.elastic.rendezvous.etcd_store.EtcdStore method)</a>
</li>
        <li><a href="futures.html#torch.futures.Future.wait">(torch.futures.Future method)</a>
</li>
      </ul></li>
      <li><a href="futures.html#torch.futures.wait_all">wait_all() (in module torch.futures)</a>
</li>
      <li><a href="generated/torch.cuda.Stream.html#torch.cuda.Stream.wait_event">wait_event() (torch.cuda.Stream method)</a>
</li>
      <li><a href="generated/torch.cuda.Stream.html#torch.cuda.Stream.wait_stream">wait_stream() (torch.cuda.Stream method)</a>
</li>
      <li><a href="distributions.html#torch.distributions.weibull.Weibull">Weibull (class in torch.distributions.weibull)</a>
</li>
      <li><a href="generated/torch.nn.utils.weight_norm.html#torch.nn.utils.weight_norm">weight_norm() (in module torch.nn.utils)</a>
</li>
      <li><a href="data.html#torch.utils.data.WeightedRandomSampler">WeightedRandomSampler (class in torch.utils.data)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.where.html#torch.where">where() (in module torch)</a>

      <ul>
        <li><a href="generated/torch.Tensor.where.html#torch.Tensor.where">(torch.Tensor method)</a>
</li>
      </ul></li>
      <li><a href="torch.quantization.html#torch.quantization.ObserverBase.with_args">with_args() (torch.quantization.ObserverBase class method)</a>
</li>
      <li><a href="torch.quantization.html#torch.quantization.ObserverBase.with_callable_args">with_callable_args() (torch.quantization.ObserverBase class method)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.Worker">Worker (class in torch.distributed.elastic.agent.server)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.WorkerGroup">WorkerGroup (class in torch.distributed.elastic.agent.server)</a>
</li>
      <li><a href="rpc.html#torch.distributed.rpc.WorkerInfo">WorkerInfo (class in torch.distributed.rpc)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.WorkerSpec">WorkerSpec (class in torch.distributed.elastic.agent.server)</a>
</li>
      <li><a href="elastic/agent.html#torch.distributed.elastic.agent.server.WorkerState">WorkerState (class in torch.distributed.elastic.agent.server)</a>
</li>
      <li><a href="fx.html#torch.fx.wrap">wrap() (in module torch.fx)</a>
</li>
      <li><a href="torch.overrides.html#torch.overrides.wrap_torch_function">wrap_torch_function() (in module torch.overrides)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="X">X</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="nn.init.html#torch.nn.init.xavier_normal_">xavier_normal_() (in module torch.nn.init)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.xavier_uniform_">xavier_uniform_() (in module torch.nn.init)</a>
</li>
      <li><a href="special.html#torch.special.xlog1py">xlog1py() (in module torch.special)</a>
</li>
      <li><a href="generated/torch.xlogy.html#torch.xlogy">xlogy() (in module torch)</a>

      <ul>
        <li><a href="special.html#torch.special.xlogy">(in module torch.special)</a>
</li>
        <li><a href="generated/torch.Tensor.xlogy.html#torch.Tensor.xlogy">(torch.Tensor method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.Tensor.xlogy_.html#torch.Tensor.xlogy_">xlogy_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.xpu">xpu() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.xpu">(torch.nn.Module method)</a>
</li>
      </ul></li>
  </ul></td>
</tr></table>

<h2 id="Z">Z</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.Tensor.zero_.html#torch.Tensor.zero_">zero_() (torch.Tensor method)</a>
</li>
      <li><a href="generated/torch.jit.ScriptModule.html#torch.jit.ScriptModule.zero_grad">zero_grad() (torch.jit.ScriptModule method)</a>

      <ul>
        <li><a href="generated/torch.nn.Module.html#torch.nn.Module.zero_grad">(torch.nn.Module method)</a>
</li>
        <li><a href="generated/torch.optim.Adadelta.html#torch.optim.Adadelta.zero_grad">(torch.optim.Adadelta method)</a>
</li>
        <li><a href="generated/torch.optim.Adagrad.html#torch.optim.Adagrad.zero_grad">(torch.optim.Adagrad method)</a>
</li>
        <li><a href="generated/torch.optim.Adam.html#torch.optim.Adam.zero_grad">(torch.optim.Adam method)</a>
</li>
        <li><a href="generated/torch.optim.Adamax.html#torch.optim.Adamax.zero_grad">(torch.optim.Adamax method)</a>
</li>
        <li><a href="generated/torch.optim.AdamW.html#torch.optim.AdamW.zero_grad">(torch.optim.AdamW method)</a>
</li>
        <li><a href="generated/torch.optim.ASGD.html#torch.optim.ASGD.zero_grad">(torch.optim.ASGD method)</a>
</li>
        <li><a href="generated/torch.optim.LBFGS.html#torch.optim.LBFGS.zero_grad">(torch.optim.LBFGS method)</a>
</li>
        <li><a href="generated/torch.optim.NAdam.html#torch.optim.NAdam.zero_grad">(torch.optim.NAdam method)</a>
</li>
        <li><a href="generated/torch.optim.Optimizer.zero_grad.html#torch.optim.Optimizer.zero_grad">(torch.optim.Optimizer method)</a>
</li>
        <li><a href="generated/torch.optim.RAdam.html#torch.optim.RAdam.zero_grad">(torch.optim.RAdam method)</a>
</li>
        <li><a href="generated/torch.optim.RMSprop.html#torch.optim.RMSprop.zero_grad">(torch.optim.RMSprop method)</a>
</li>
        <li><a href="generated/torch.optim.Rprop.html#torch.optim.Rprop.zero_grad">(torch.optim.Rprop method)</a>
</li>
        <li><a href="generated/torch.optim.SGD.html#torch.optim.SGD.zero_grad">(torch.optim.SGD method)</a>
</li>
        <li><a href="generated/torch.optim.SparseAdam.html#torch.optim.SparseAdam.zero_grad">(torch.optim.SparseAdam method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="generated/torch.nn.ZeroPad2d.html#torch.nn.ZeroPad2d">ZeroPad2d (class in torch.nn)</a>
</li>
      <li><a href="distributed.optim.html#torch.distributed.optim.ZeroRedundancyOptimizer">ZeroRedundancyOptimizer (class in torch.distributed.optim)</a>
</li>
      <li><a href="generated/torch.zeros.html#torch.zeros">zeros() (in module torch)</a>
</li>
      <li><a href="nn.init.html#torch.nn.init.zeros_">zeros_() (in module torch.nn.init)</a>
</li>
      <li><a href="generated/torch.zeros_like.html#torch.zeros_like">zeros_like() (in module torch)</a>
</li>
      <li><a href="special.html#torch.special.zeta">zeta() (in module torch.special)</a>
</li>
  </ul></td>
</tr></table>


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