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<li class="toctree-l2"><a class="reference internal" href="generated/torch.conj_physical.html">torch.conj_physical</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.copysign.html">torch.copysign</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cos.html">torch.cos</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cosh.html">torch.cosh</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.deg2rad.html">torch.deg2rad</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.div.html">torch.div</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.divide.html">torch.divide</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.digamma.html">torch.digamma</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.erf.html">torch.erf</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.erfc.html">torch.erfc</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.erfinv.html">torch.erfinv</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.exp.html">torch.exp</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.exp2.html">torch.exp2</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.expm1.html">torch.expm1</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.fake_quantize_per_channel_affine.html">torch.fake_quantize_per_channel_affine</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.fake_quantize_per_tensor_affine.html">torch.fake_quantize_per_tensor_affine</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.fix.html">torch.fix</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.float_power.html">torch.float_power</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.floor.html">torch.floor</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.floor_divide.html">torch.floor_divide</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.fmod.html">torch.fmod</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.frac.html">torch.frac</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.frexp.html">torch.frexp</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.gradient.html">torch.gradient</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.imag.html">torch.imag</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.ldexp.html">torch.ldexp</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.lerp.html">torch.lerp</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.lgamma.html">torch.lgamma</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.log.html">torch.log</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.log10.html">torch.log10</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.log1p.html">torch.log1p</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.log2.html">torch.log2</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logaddexp.html">torch.logaddexp</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logaddexp2.html">torch.logaddexp2</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logical_and.html">torch.logical_and</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logical_not.html">torch.logical_not</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logical_or.html">torch.logical_or</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logical_xor.html">torch.logical_xor</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logit.html">torch.logit</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.hypot.html">torch.hypot</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.i0.html">torch.i0</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.igamma.html">torch.igamma</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.igammac.html">torch.igammac</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mul.html">torch.mul</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.multiply.html">torch.multiply</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mvlgamma.html">torch.mvlgamma</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nan_to_num.html">torch.nan_to_num</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.neg.html">torch.neg</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.negative.html">torch.negative</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nextafter.html">torch.nextafter</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.polygamma.html">torch.polygamma</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.positive.html">torch.positive</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.pow.html">torch.pow</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.quantized_batch_norm.html">torch.quantized_batch_norm</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.quantized_max_pool1d.html">torch.quantized_max_pool1d</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.quantized_max_pool2d.html">torch.quantized_max_pool2d</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.rad2deg.html">torch.rad2deg</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.real.html">torch.real</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.reciprocal.html">torch.reciprocal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.remainder.html">torch.remainder</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.round.html">torch.round</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.rsqrt.html">torch.rsqrt</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sigmoid.html">torch.sigmoid</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sign.html">torch.sign</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sgn.html">torch.sgn</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.signbit.html">torch.signbit</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sin.html">torch.sin</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sinc.html">torch.sinc</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sinh.html">torch.sinh</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.softmax.html">torch.softmax</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sqrt.html">torch.sqrt</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.square.html">torch.square</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sub.html">torch.sub</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.subtract.html">torch.subtract</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.tan.html">torch.tan</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.tanh.html">torch.tanh</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.true_divide.html">torch.true_divide</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.trunc.html">torch.trunc</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xlogy.html">torch.xlogy</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.argmax.html">torch.argmax</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.argmin.html">torch.argmin</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.amax.html">torch.amax</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.amin.html">torch.amin</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.aminmax.html">torch.aminmax</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.all.html">torch.all</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.any.html">torch.any</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.max.html">torch.max</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.min.html">torch.min</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.dist.html">torch.dist</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logsumexp.html">torch.logsumexp</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mean.html">torch.mean</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nanmean.html">torch.nanmean</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.median.html">torch.median</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nanmedian.html">torch.nanmedian</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mode.html">torch.mode</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.norm.html">torch.norm</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nansum.html">torch.nansum</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.prod.html">torch.prod</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.quantile.html">torch.quantile</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nanquantile.html">torch.nanquantile</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.std.html">torch.std</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.std_mean.html">torch.std_mean</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sum.html">torch.sum</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.unique.html">torch.unique</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.unique_consecutive.html">torch.unique_consecutive</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.var.html">torch.var</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.var_mean.html">torch.var_mean</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.count_nonzero.html">torch.count_nonzero</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.allclose.html">torch.allclose</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.argsort.html">torch.argsort</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.eq.html">torch.eq</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.equal.html">torch.equal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.ge.html">torch.ge</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.greater_equal.html">torch.greater_equal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.gt.html">torch.gt</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.greater.html">torch.greater</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.isclose.html">torch.isclose</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.isfinite.html">torch.isfinite</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.isin.html">torch.isin</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.isinf.html">torch.isinf</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.isposinf.html">torch.isposinf</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.isneginf.html">torch.isneginf</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.isnan.html">torch.isnan</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.isreal.html">torch.isreal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.kthvalue.html">torch.kthvalue</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.le.html">torch.le</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.less_equal.html">torch.less_equal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.lt.html">torch.lt</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.less.html">torch.less</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.maximum.html">torch.maximum</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.minimum.html">torch.minimum</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.fmax.html">torch.fmax</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.fmin.html">torch.fmin</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.ne.html">torch.ne</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.not_equal.html">torch.not_equal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sort.html">torch.sort</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.topk.html">torch.topk</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.msort.html">torch.msort</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.stft.html">torch.stft</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.istft.html">torch.istft</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.bartlett_window.html">torch.bartlett_window</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.blackman_window.html">torch.blackman_window</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.hamming_window.html">torch.hamming_window</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.hann_window.html">torch.hann_window</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.kaiser_window.html">torch.kaiser_window</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.atleast_1d.html">torch.atleast_1d</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.atleast_2d.html">torch.atleast_2d</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.atleast_3d.html">torch.atleast_3d</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.bincount.html">torch.bincount</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.block_diag.html">torch.block_diag</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.broadcast_tensors.html">torch.broadcast_tensors</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.broadcast_to.html">torch.broadcast_to</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.broadcast_shapes.html">torch.broadcast_shapes</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.bucketize.html">torch.bucketize</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cartesian_prod.html">torch.cartesian_prod</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cdist.html">torch.cdist</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.clone.html">torch.clone</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.combinations.html">torch.combinations</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.corrcoef.html">torch.corrcoef</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cov.html">torch.cov</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cross.html">torch.cross</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cummax.html">torch.cummax</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cummin.html">torch.cummin</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cumprod.html">torch.cumprod</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cumsum.html">torch.cumsum</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.diag.html">torch.diag</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.diag_embed.html">torch.diag_embed</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.diagflat.html">torch.diagflat</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.diagonal.html">torch.diagonal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.diff.html">torch.diff</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.einsum.html">torch.einsum</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.flatten.html">torch.flatten</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.flip.html">torch.flip</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.fliplr.html">torch.fliplr</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.flipud.html">torch.flipud</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.kron.html">torch.kron</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.rot90.html">torch.rot90</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.gcd.html">torch.gcd</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.histc.html">torch.histc</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.histogram.html">torch.histogram</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.histogramdd.html">torch.histogramdd</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.meshgrid.html">torch.meshgrid</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.lcm.html">torch.lcm</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logcumsumexp.html">torch.logcumsumexp</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.ravel.html">torch.ravel</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.renorm.html">torch.renorm</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.repeat_interleave.html">torch.repeat_interleave</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.roll.html">torch.roll</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.searchsorted.html">torch.searchsorted</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.tensordot.html">torch.tensordot</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.trace.html">torch.trace</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.tril.html">torch.tril</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.tril_indices.html">torch.tril_indices</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.triu.html">torch.triu</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.triu_indices.html">torch.triu_indices</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.unflatten.html">torch.unflatten</a></li>
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</ul>
</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="nn.html">torch.nn</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.LeakyReLU.html">LeakyReLU</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.ReLU6.html">ReLU6</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.RReLU.html">RReLU</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.CELU.html">CELU</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.GELU.html">GELU</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.Sigmoid.html">Sigmoid</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.SiLU.html">SiLU</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.Mish.html">Mish</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.Softplus.html">Softplus</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.Softshrink.html">Softshrink</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.Softsign.html">Softsign</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.Tanh.html">Tanh</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.GLU.html">GLU</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.Softmin.html">Softmin</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.Softmax.html">Softmax</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.Softmax2d.html">Softmax2d</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.LogSoftmax.html">LogSoftmax</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.RNN.html">RNN</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.GRU.html">GRU</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.Bilinear.html">Bilinear</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.utils.parametrizations.spectral_norm.html">torch.nn.utils.parametrizations.spectral_norm</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.nn.utils.rnn.pad_packed_sequence.html">torch.nn.utils.rnn.pad_packed_sequence</a></li>
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<li class="toctree-l1 has-children"><a class="reference internal" href="nn.functional.html">torch.nn.functional</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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</ul>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.seed.html">torch.mps.seed</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.empty_cache.html">torch.mps.empty_cache</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.set_per_process_memory_fraction.html">torch.mps.set_per_process_memory_fraction</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.current_allocated_memory.html">torch.mps.current_allocated_memory</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.driver_allocated_memory.html">torch.mps.driver_allocated_memory</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.recommended_max_memory.html">torch.mps.recommended_max_memory</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.compile_shader.html">torch.mps.compile_shader</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.profiler.start.html">torch.mps.profiler.start</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.profiler.stop.html">torch.mps.profiler.stop</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.profiler.profile.html">torch.mps.profiler.profile</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.profiler.is_capturing_metal.html">torch.mps.profiler.is_capturing_metal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.profiler.is_metal_capture_enabled.html">torch.mps.profiler.is_metal_capture_enabled</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.profiler.metal_capture.html">torch.mps.profiler.metal_capture</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mps.event.Event.html">Event</a></li>
</ul>
</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="xpu.html">torch.xpu</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.StreamContext.html">StreamContext</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.current_device.html">torch.xpu.current_device</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.current_stream.html">torch.xpu.current_stream</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.device.html">device</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.device_count.html">torch.xpu.device_count</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.device_of.html">device_of</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.get_arch_list.html">torch.xpu.get_arch_list</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.get_device_capability.html">torch.xpu.get_device_capability</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.get_device_name.html">torch.xpu.get_device_name</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.get_device_properties.html">torch.xpu.get_device_properties</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.get_gencode_flags.html">torch.xpu.get_gencode_flags</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.get_stream_from_external.html">torch.xpu.get_stream_from_external</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.init.html">torch.xpu.init</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.is_available.html">torch.xpu.is_available</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.is_initialized.html">torch.xpu.is_initialized</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.set_device.html">torch.xpu.set_device</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.set_stream.html">torch.xpu.set_stream</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.stream.html">torch.xpu.stream</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.get_rng_state.html">torch.xpu.get_rng_state</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.get_rng_state_all.html">torch.xpu.get_rng_state_all</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.initial_seed.html">torch.xpu.initial_seed</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.manual_seed.html">torch.xpu.manual_seed</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.manual_seed_all.html">torch.xpu.manual_seed_all</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.seed.html">torch.xpu.seed</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.seed_all.html">torch.xpu.seed_all</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.set_rng_state.html">torch.xpu.set_rng_state</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.set_rng_state_all.html">torch.xpu.set_rng_state_all</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.Event.html">Event</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.Stream.html">Stream</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.empty_cache.html">torch.xpu.empty_cache</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.max_memory_allocated.html">torch.xpu.max_memory_allocated</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.max_memory_reserved.html">torch.xpu.max_memory_reserved</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.mem_get_info.html">torch.xpu.mem_get_info</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.memory_allocated.html">torch.xpu.memory_allocated</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.memory_reserved.html">torch.xpu.memory_reserved</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.memory_stats.html">torch.xpu.memory_stats</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.memory_stats_as_nested_dict.html">torch.xpu.memory_stats_as_nested_dict</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.reset_accumulated_memory_stats.html">torch.xpu.reset_accumulated_memory_stats</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.xpu.reset_peak_memory_stats.html">torch.xpu.reset_peak_memory_stats</a></li>
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</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="mtia.html">torch.mtia</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.StreamContext.html">StreamContext</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.current_stream.html">torch.mtia.current_stream</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.default_stream.html">torch.mtia.default_stream</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.device_count.html">torch.mtia.device_count</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.init.html">torch.mtia.init</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.is_available.html">torch.mtia.is_available</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.is_initialized.html">torch.mtia.is_initialized</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.memory_stats.html">torch.mtia.memory_stats</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.get_device_capability.html">torch.mtia.get_device_capability</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.empty_cache.html">torch.mtia.empty_cache</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.record_memory_history.html">torch.mtia.record_memory_history</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.snapshot.html">torch.mtia.snapshot</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.attach_out_of_memory_observer.html">torch.mtia.attach_out_of_memory_observer</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.set_device.html">torch.mtia.set_device</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.set_stream.html">torch.mtia.set_stream</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.stream.html">torch.mtia.stream</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.synchronize.html">torch.mtia.synchronize</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.device.html">device</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.set_rng_state.html">torch.mtia.set_rng_state</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.get_rng_state.html">torch.mtia.get_rng_state</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.DeferredMtiaCallError.html">torch.mtia.DeferredMtiaCallError</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.Event.html">Event</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.Stream.html">Stream</a></li>
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</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="mtia.memory.html">torch.mtia.memory</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mtia.memory.memory_stats.html">torch.mtia.memory.memory_stats</a></li>
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</details></li>
<li class="toctree-l1"><a class="reference internal" href="meta.html">Meta device</a></li>
<li class="toctree-l1"><a class="reference internal" href="backends.html">torch.backends</a></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="export.html">torch.export</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="export.programming_model.html">torch.export Programming Model</a></li>
<li class="toctree-l2"><a class="reference internal" href="export.ir_spec.html">torch.export IR Specification</a></li>
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<li class="toctree-l3"><a class="reference internal" href="generated/exportdb/torch.dynamic-shape.html">torch.dynamic-shape</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/exportdb/torch.cond.html">torch.cond</a></li>
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<li class="toctree-l3"><a class="reference internal" href="generated/exportdb/torch.mutation.html">torch.mutation</a></li>
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<li class="toctree-l2"><a class="reference internal" href="cond.html">Control Flow - Cond</a></li>
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<li class="toctree-l2"><a class="reference internal" href="torch.compiler_fake_tensor.html">Fake tensor</a></li>
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<li class="toctree-l1"><a class="reference internal" href="distributed.html">torch.distributed</a></li>
<li class="toctree-l1"><a class="reference internal" href="distributed.tensor.html">torch.distributed.tensor</a></li>
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<li class="toctree-l1 has-children"><a class="reference internal" href="distributed.elastic.html">torch.distributed.elastic</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="elastic/quickstart.html">Quickstart</a></li>
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<li class="toctree-l1"><a class="reference internal" href="fsdp.html">torch.distributed.fsdp</a></li>
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<li class="toctree-l2"><a class="reference internal" href="torch.compiler_get_started.html">Getting Started</a></li>
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<li class="toctree-l2"><a class="reference internal" href="torch.compiler.config.html">torch.compiler.config</a></li>
<li class="toctree-l2"><a class="reference internal" href="torch.compiler_fine_grain_apis.html">TorchDynamo APIs for fine-grained tracing</a></li>
<li class="toctree-l2 has-children"><a class="reference internal" href="torch.compiler_aot_inductor.html">AOTInductor: Ahead-Of-Time Compilation for Torch.Export-ed Models</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l3 has-children"><a class="reference internal" href="logging.html">torch._logging</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l3"><a class="reference internal" href="torch.compiler_aot_inductor_minifier.html">AOTInductor Minifier</a></li>
</ul>
</details></li>
<li class="toctree-l2"><a class="reference internal" href="torch.compiler_inductor_profiling.html">TorchInductor GPU Profiling</a></li>
<li class="toctree-l2"><a class="reference internal" href="torch.compiler_profiling_torch_compile.html">Profiling to understand torch.compile performance</a></li>
<li class="toctree-l2"><a class="reference internal" href="torch.compiler_faq.html">Frequently Asked Questions</a></li>
<li class="toctree-l2"><a class="reference internal" href="torch.compiler_troubleshooting.html">torch.compile Troubleshooting</a></li>
<li class="toctree-l2"><a class="reference internal" href="torch.compiler_performance_dashboard.html">PyTorch 2.0 Performance Dashboard</a></li>
<li class="toctree-l2"><a class="reference internal" href="torch.compiler_dynamo_overview.html">Dynamo Overview</a></li>
<li class="toctree-l2"><a class="reference internal" href="torch.compiler_dynamo_deepdive.html">Dynamo Deep-Dive</a></li>
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<li class="toctree-l2 has-children"><a class="reference internal" href="quantization-support.html">Quantization API Reference</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.quantize.html">quantize</a></li>
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<li class="toctree-l3"><a class="reference internal" href="generated/torch.Tensor.min.html">torch.Tensor.min</a></li>
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<li class="toctree-l3"><a class="reference internal" href="generated/torch.Tensor.q_zero_point.html">torch.Tensor.q_zero_point</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.Tensor.q_per_channel_scales.html">torch.Tensor.q_per_channel_scales</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.Tensor.q_per_channel_zero_points.html">torch.Tensor.q_per_channel_zero_points</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.Tensor.q_per_channel_axis.html">torch.Tensor.q_per_channel_axis</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.Tensor.resize_.html">torch.Tensor.resize_</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.Tensor.sort.html">torch.Tensor.sort</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.Tensor.topk.html">torch.Tensor.topk</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.ObserverBase.html">ObserverBase</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.MinMaxObserver.html">MinMaxObserver</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.MovingAverageMinMaxObserver.html">MovingAverageMinMaxObserver</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.PerChannelMinMaxObserver.html">PerChannelMinMaxObserver</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.MovingAveragePerChannelMinMaxObserver.html">MovingAveragePerChannelMinMaxObserver</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.HistogramObserver.html">HistogramObserver</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.PlaceholderObserver.html">PlaceholderObserver</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.RecordingObserver.html">RecordingObserver</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.NoopObserver.html">NoopObserver</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.get_observer_state_dict.html">get_observer_state_dict</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.load_observer_state_dict.html">load_observer_state_dict</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.default_observer.html">default_observer</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.default_placeholder_observer.html">default_placeholder_observer</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.default_debug_observer.html">default_debug_observer</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.default_weight_observer.html">default_weight_observer</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.default_histogram_observer.html">default_histogram_observer</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.default_per_channel_weight_observer.html">default_per_channel_weight_observer</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.default_dynamic_quant_observer.html">default_dynamic_quant_observer</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.default_float_qparams_observer.html">default_float_qparams_observer</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.AffineQuantizedObserverBase.html">AffineQuantizedObserverBase</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.Granularity.html">Granularity</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.MappingType.html">MappingType</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.PerAxis.html">PerAxis</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.PerBlock.html">PerBlock</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.PerGroup.html">PerGroup</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.PerRow.html">PerRow</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.PerTensor.html">PerTensor</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.PerToken.html">PerToken</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.TorchAODType.html">TorchAODType</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.ZeroPointDomain.html">ZeroPointDomain</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.observer.get_block_size.html">get_block_size</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.FakeQuantizeBase.html">FakeQuantizeBase</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.FakeQuantize.html">FakeQuantize</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.FixedQParamsFakeQuantize.html">FixedQParamsFakeQuantize</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.FusedMovingAvgObsFakeQuantize.html">FusedMovingAvgObsFakeQuantize</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.default_fake_quant.html">default_fake_quant</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.default_weight_fake_quant.html">default_weight_fake_quant</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.default_per_channel_weight_fake_quant.html">default_per_channel_weight_fake_quant</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.default_histogram_fake_quant.html">default_histogram_fake_quant</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.default_fused_act_fake_quant.html">default_fused_act_fake_quant</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.default_fused_wt_fake_quant.html">default_fused_wt_fake_quant</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.default_fused_per_channel_wt_fake_quant.html">default_fused_per_channel_wt_fake_quant</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.disable_fake_quant.html">disable_fake_quant</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.enable_fake_quant.html">enable_fake_quant</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.disable_observer.html">disable_observer</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.fake_quantize.enable_observer.html">enable_observer</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.QConfig.html">QConfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.default_qconfig.html">default_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.default_debug_qconfig.html">default_debug_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.default_per_channel_qconfig.html">default_per_channel_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.default_dynamic_qconfig.html">default_dynamic_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.float16_dynamic_qconfig.html">float16_dynamic_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.float16_static_qconfig.html">float16_static_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.per_channel_dynamic_qconfig.html">per_channel_dynamic_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.float_qparams_weight_only_qconfig.html">float_qparams_weight_only_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.default_qat_qconfig.html">default_qat_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.default_weight_only_qconfig.html">default_weight_only_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.default_activation_only_qconfig.html">default_activation_only_qconfig</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.quantization.qconfig.default_qat_qconfig_v2.html">default_qat_qconfig_v2</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.ConvReLU1d.html">ConvReLU1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.ConvReLU2d.html">ConvReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.ConvReLU3d.html">ConvReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.LinearReLU.html">LinearReLU</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.ConvBn1d.html">ConvBn1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.ConvBn2d.html">ConvBn2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.ConvBn3d.html">ConvBn3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.ConvBnReLU1d.html">ConvBnReLU1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.ConvBnReLU2d.html">ConvBnReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.ConvBnReLU3d.html">ConvBnReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.BNReLU2d.html">BNReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.BNReLU3d.html">BNReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.LinearReLU.html">LinearReLU</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.ConvBn1d.html">ConvBn1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.ConvBnReLU1d.html">ConvBnReLU1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.ConvBn2d.html">ConvBn2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.ConvBnReLU2d.html">ConvBnReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.ConvReLU2d.html">ConvReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.ConvBn3d.html">ConvBn3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.ConvBnReLU3d.html">ConvBnReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.ConvReLU3d.html">ConvReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.update_bn_stats.html">update_bn_stats</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.qat.freeze_bn_stats.html">freeze_bn_stats</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.quantized.BNReLU2d.html">BNReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.quantized.BNReLU3d.html">BNReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.quantized.ConvReLU1d.html">ConvReLU1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.quantized.ConvReLU2d.html">ConvReLU2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.quantized.ConvReLU3d.html">ConvReLU3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.quantized.LinearReLU.html">LinearReLU</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.intrinsic.quantized.dynamic.LinearReLU.html">LinearReLU</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.qat.Conv2d.html">Conv2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.qat.Conv3d.html">Conv3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.qat.Linear.html">Linear</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.qat.dynamic.Linear.html">Linear</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.ReLU6.html">ReLU6</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.Hardswish.html">Hardswish</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.ELU.html">ELU</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.LeakyReLU.html">LeakyReLU</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.Sigmoid.html">Sigmoid</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.BatchNorm2d.html">BatchNorm2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.BatchNorm3d.html">BatchNorm3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.Conv1d.html">Conv1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.Conv2d.html">Conv2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.Conv3d.html">Conv3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.ConvTranspose1d.html">ConvTranspose1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.ConvTranspose2d.html">ConvTranspose2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.ConvTranspose3d.html">ConvTranspose3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.Embedding.html">Embedding</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.EmbeddingBag.html">EmbeddingBag</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.FloatFunctional.html">FloatFunctional</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.FXFloatFunctional.html">FXFloatFunctional</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.QFunctional.html">QFunctional</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.Linear.html">Linear</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.LayerNorm.html">LayerNorm</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.GroupNorm.html">GroupNorm</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.InstanceNorm1d.html">InstanceNorm1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.InstanceNorm2d.html">InstanceNorm2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.InstanceNorm3d.html">InstanceNorm3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.avg_pool2d.html">avg_pool2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.avg_pool3d.html">avg_pool3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.adaptive_avg_pool2d.html">adaptive_avg_pool2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.adaptive_avg_pool3d.html">adaptive_avg_pool3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.conv1d.html">conv1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.conv2d.html">conv2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.conv3d.html">conv3d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.interpolate.html">interpolate</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.linear.html">linear</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.max_pool1d.html">max_pool1d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.max_pool2d.html">max_pool2d</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.celu.html">celu</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.leaky_relu.html">leaky_relu</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.hardtanh.html">hardtanh</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.hardswish.html">hardswish</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.threshold.html">threshold</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.elu.html">elu</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.hardsigmoid.html">hardsigmoid</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.clamp.html">clamp</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.upsample.html">upsample</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.upsample_bilinear.html">upsample_bilinear</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.functional.upsample_nearest.html">upsample_nearest</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantizable.LSTM.html">LSTM</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantizable.MultiheadAttention.html">MultiheadAttention</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.dynamic.Linear.html">Linear</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.dynamic.LSTM.html">LSTM</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.dynamic.GRU.html">GRU</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.dynamic.RNNCell.html">RNNCell</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.dynamic.LSTMCell.html">LSTMCell</a></li>
<li class="toctree-l3"><a class="reference internal" href="generated/torch.ao.nn.quantized.dynamic.GRUCell.html">GRUCell</a></li>
</ul>
</details></li>
<li class="toctree-l2"><a class="reference internal" href="quantization-backend-configuration.html">Quantization Backend Configuration</a></li>
<li class="toctree-l2"><a class="reference internal" href="quantization-accuracy-debugging.html">Quantization Accuracy Debugging</a></li>

</ul>
</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="rpc.html">Distributed RPC Framework</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="rpc/rref.html">Remote Reference Protocol</a></li>
<li class="toctree-l2"><a class="reference internal" href="rpc/distributed_autograd.html">Distributed Autograd Design</a></li>
</ul>
</details></li>
<li class="toctree-l1"><a class="reference internal" href="random.html">torch.random</a></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="masked.html">torch.masked</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.absolute.html">torch.absolute</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.acos.html">torch.acos</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.asin.html">torch.asin</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.arcsin.html">torch.arcsin</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.arcsinh.html">torch.arcsinh</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.atan.html">torch.atan</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.arctan.html">torch.arctan</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.atanh.html">torch.atanh</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.arctanh.html">torch.arctanh</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.ceil.html">torch.ceil</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.clip.html">torch.clip</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.cos.html">torch.cos</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.cosh.html">torch.cosh</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.erf.html">torch.erf</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.erfc.html">torch.erfc</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.erfinv.html">torch.erfinv</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.exp.html">torch.exp</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.exp2.html">torch.exp2</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.expm1.html">torch.expm1</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.fix.html">torch.fix</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.floor.html">torch.floor</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.frac.html">torch.frac</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.log.html">torch.log</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.log10.html">torch.log10</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.log1p.html">torch.log1p</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.log2.html">torch.log2</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logit.html">torch.logit</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.i0.html">torch.i0</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.isnan.html">torch.isnan</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nan_to_num.html">torch.nan_to_num</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.neg.html">torch.neg</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.negative.html">torch.negative</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.positive.html">torch.positive</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.pow.html">torch.pow</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.rad2deg.html">torch.rad2deg</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.reciprocal.html">torch.reciprocal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.round.html">torch.round</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.rsqrt.html">torch.rsqrt</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sigmoid.html">torch.sigmoid</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sign.html">torch.sign</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sgn.html">torch.sgn</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.signbit.html">torch.signbit</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sin.html">torch.sin</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sinc.html">torch.sinc</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sinh.html">torch.sinh</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sqrt.html">torch.sqrt</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.square.html">torch.square</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.tan.html">torch.tan</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.tanh.html">torch.tanh</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.trunc.html">torch.trunc</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.angle.html">torch.angle</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.positive.html">torch.positive</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.signbit.html">torch.signbit</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.isnan.html">torch.isnan</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.add.html">torch.add</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.atan2.html">torch.atan2</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.bitwise_right_shift.html">torch.bitwise_right_shift</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.div.html">torch.div</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.fmod.html">torch.fmod</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.logaddexp2.html">torch.logaddexp2</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.mul.html">torch.mul</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.multiply.html">torch.multiply</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.nextafter.html">torch.nextafter</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.remainder.html">torch.remainder</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sub.html">torch.sub</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.subtract.html">torch.subtract</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.true_divide.html">torch.true_divide</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.eq.html">torch.eq</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.ne.html">torch.ne</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.le.html">torch.le</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.ge.html">torch.ge</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.greater.html">torch.greater</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.greater_equal.html">torch.greater_equal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.gt.html">torch.gt</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.less_equal.html">torch.less_equal</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.lt.html">torch.lt</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.less.html">torch.less</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.maximum.html">torch.maximum</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.minimum.html">torch.minimum</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.fmin.html">torch.fmin</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.logaddexp.html">torch.logaddexp</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.logaddexp2.html">torch.logaddexp2</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.equal.html">torch.equal</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.minimum.html">torch.minimum</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.sum.html">torch.sum</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.argmax.html">torch.argmax</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.cat.html">torch.cat</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.chunk.html">torch.chunk</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.column_stack.html">torch.column_stack</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.dsplit.html">torch.dsplit</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.flatten.html">torch.flatten</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.hsplit.html">torch.hsplit</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.hstack.html">torch.hstack</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.kron.html">torch.kron</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.meshgrid.html">torch.meshgrid</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.narrow.html">torch.narrow</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.ravel.html">torch.ravel</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.select.html">torch.select</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.split.html">torch.split</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.stack.html">torch.stack</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.t.html">torch.t</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.transpose.html">torch.transpose</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.vsplit.html">torch.vsplit</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.vstack.html">torch.vstack</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.expand.html">torch.Tensor.expand</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.expand_as.html">torch.Tensor.expand_as</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.reshape.html">torch.Tensor.reshape</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.reshape_as.html">torch.Tensor.reshape_as</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.unfold.html">torch.Tensor.unfold</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.view.html">torch.Tensor.view</a></li>
</ul>
</details></li>
<li class="toctree-l1"><a class="reference internal" href="nested.html">torch.nested</a></li>
<li class="toctree-l1"><a class="reference internal" href="size.html">torch.Size</a></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="sparse.html">torch.sparse</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.is_sparse.html">torch.Tensor.is_sparse</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.is_sparse_csr.html">torch.Tensor.is_sparse_csr</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.sparse_dim.html">torch.Tensor.sparse_dim</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.sparse_mask.html">torch.Tensor.sparse_mask</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.to_sparse.html">torch.Tensor.to_sparse</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.to_sparse_coo.html">torch.Tensor.to_sparse_coo</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.to_sparse_csr.html">torch.Tensor.to_sparse_csr</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.to_sparse_csc.html">torch.Tensor.to_sparse_csc</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.to_sparse_bsr.html">torch.Tensor.to_sparse_bsr</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.to_sparse_bsc.html">torch.Tensor.to_sparse_bsc</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.to_dense.html">torch.Tensor.to_dense</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.values.html">torch.Tensor.values</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.coalesce.html">torch.Tensor.coalesce</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.sparse_resize_.html">torch.Tensor.sparse_resize_</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.sparse_resize_and_clear_.html">torch.Tensor.sparse_resize_and_clear_</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.is_coalesced.html">torch.Tensor.is_coalesced</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.indices.html">torch.Tensor.indices</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.crow_indices.html">torch.Tensor.crow_indices</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.col_indices.html">torch.Tensor.col_indices</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.row_indices.html">torch.Tensor.row_indices</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.Tensor.ccol_indices.html">torch.Tensor.ccol_indices</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sparse_coo_tensor.html">torch.sparse_coo_tensor</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sparse_csr_tensor.html">torch.sparse_csr_tensor</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sparse_csc_tensor.html">torch.sparse_csc_tensor</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sparse_bsr_tensor.html">torch.sparse_bsr_tensor</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sparse_bsc_tensor.html">torch.sparse_bsc_tensor</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sparse_compressed_tensor.html">torch.sparse_compressed_tensor</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sparse.sum.html">torch.sparse.sum</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sparse.addmm.html">torch.sparse.addmm</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sparse.sampled_addmm.html">torch.sparse.sampled_addmm</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/torch.sparse.mm.html">torch.sparse.mm</a></li>
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  <div class="section" id="torch-hub">
<h1>torch.hub<a class="headerlink" href="#torch-hub" title="Permalink to this heading">#</a></h1>
<p class="date-info-last-verified" style="color: #6c6c6d; font-size: small;">Created On: Oct 29, 2018 | Last Updated: Jan 23, 2023</p>
<p>Pytorch Hub is a pre-trained model repository designed to facilitate research reproducibility.</p>
<div class="section" id="publishing-models">
<h2>Publishing models<a class="headerlink" href="#publishing-models" title="Permalink to this heading">#</a></h2>
<p>Pytorch Hub supports publishing pre-trained models(model definitions and pre-trained weights)
to a GitHub repository by adding a simple <code class="docutils literal notranslate"><span class="pre">hubconf.py</span></code> file;</p>
<p><code class="docutils literal notranslate"><span class="pre">hubconf.py</span></code> can have multiple entrypoints. Each entrypoint is defined as a python function
(example: a pre-trained model you want to publish).</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">entrypoint_name</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
    <span class="c1"># args &amp; kwargs are optional, for models which take positional/keyword arguments.</span>
    <span class="o">...</span>
</pre></div>
</div>
<div class="section" id="how-to-implement-an-entrypoint">
<h3>How to implement an entrypoint?<a class="headerlink" href="#how-to-implement-an-entrypoint" title="Permalink to this heading">#</a></h3>
<p>Here is a code snippet specifies an entrypoint for <code class="docutils literal notranslate"><span class="pre">resnet18</span></code> model if we expand
the implementation in <code class="docutils literal notranslate"><span class="pre">pytorch/vision/hubconf.py</span></code>.
In most case importing the right function in <code class="docutils literal notranslate"><span class="pre">hubconf.py</span></code> is sufficient. Here we
just want to use the expanded version as an example to show how it works.
You can see the full script in
<a class="reference external" href="https://github.com/pytorch/vision/blob/master/hubconf.py">pytorch/vision repo</a></p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">dependencies</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;torch&#39;</span><span class="p">]</span>
<span class="kn">from</span> <span class="nn">torchvision.models.resnet</span> <span class="kn">import</span> <span class="n">resnet18</span> <span class="k">as</span> <span class="n">_resnet18</span>

<span class="c1"># resnet18 is the name of entrypoint</span>
<span class="k">def</span> <span class="nf">resnet18</span><span class="p">(</span><span class="n">pretrained</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="w">    </span><span class="sd">&quot;&quot;&quot; # This docstring shows up in hub.help()</span>
<span class="sd">    Resnet18 model</span>
<span class="sd">    pretrained (bool): kwargs, load pretrained weights into the model</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># Call the model, load pretrained weights</span>
    <span class="n">model</span> <span class="o">=</span> <span class="n">_resnet18</span><span class="p">(</span><span class="n">pretrained</span><span class="o">=</span><span class="n">pretrained</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">model</span>
</pre></div>
</div>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">dependencies</span></code> variable is a <strong>list</strong> of package names required to <strong>load</strong> the model. Note this might
be slightly different from dependencies required for training a model.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">args</span></code> and <code class="docutils literal notranslate"><span class="pre">kwargs</span></code> are passed along to the real callable function.</p></li>
<li><p>Docstring of the function works as a help message. It explains what does the model do and what
are the allowed positional/keyword arguments. It’s highly recommended to add a few examples here.</p></li>
<li><p>Entrypoint function can either return a model(nn.module), or auxiliary tools to make the user workflow smoother, e.g. tokenizers.</p></li>
<li><p>Callables prefixed with underscore are considered as helper functions which won’t show up in <a class="reference internal" href="#torch.hub.list" title="torch.hub.list"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.list()</span></code></a>.</p></li>
<li><p>Pretrained weights can either be stored locally in the GitHub repo, or loadable by
<a class="reference internal" href="#torch.hub.load_state_dict_from_url" title="torch.hub.load_state_dict_from_url"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.load_state_dict_from_url()</span></code></a>. If less than 2GB, it’s recommended to attach it to a <a class="reference external" href="https://help.github.com/en/articles/distributing-large-binaries">project release</a>
and use the url from the release.
In the example above <code class="docutils literal notranslate"><span class="pre">torchvision.models.resnet.resnet18</span></code> handles <code class="docutils literal notranslate"><span class="pre">pretrained</span></code>, alternatively you can put the following logic in the entrypoint definition.</p></li>
</ul>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">if</span> <span class="n">pretrained</span><span class="p">:</span>
    <span class="c1"># For checkpoint saved in local GitHub repo, e.g. &lt;RELATIVE_PATH_TO_CHECKPOINT&gt;=weights/save.pth</span>
    <span class="n">dirname</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">dirname</span><span class="p">(</span><span class="vm">__file__</span><span class="p">)</span>
    <span class="n">checkpoint</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">dirname</span><span class="p">,</span> <span class="o">&lt;</span><span class="n">RELATIVE_PATH_TO_CHECKPOINT</span><span class="o">&gt;</span><span class="p">)</span>
    <span class="n">state_dict</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">)</span>
    <span class="n">model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">state_dict</span><span class="p">)</span>

    <span class="c1"># For checkpoint saved elsewhere</span>
    <span class="n">checkpoint</span> <span class="o">=</span> <span class="s1">&#39;https://download.pytorch.org/models/resnet18-5c106cde.pth&#39;</span>
    <span class="n">model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">load_state_dict_from_url</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">,</span> <span class="n">progress</span><span class="o">=</span><span class="kc">False</span><span class="p">))</span>
</pre></div>
</div>
</div>
<div class="section" id="important-notice">
<h3>Important Notice<a class="headerlink" href="#important-notice" title="Permalink to this heading">#</a></h3>
<ul class="simple">
<li><p>The published models should be at least in a branch/tag. It can’t be a random commit.</p></li>
</ul>
</div>
</div>
<div class="section" id="loading-models-from-hub">
<h2>Loading models from Hub<a class="headerlink" href="#loading-models-from-hub" title="Permalink to this heading">#</a></h2>
<p>Pytorch Hub provides convenient APIs to explore all available models in hub
through <a class="reference internal" href="#torch.hub.list" title="torch.hub.list"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.list()</span></code></a>, show docstring and examples through
<a class="reference internal" href="#torch.hub.help" title="torch.hub.help"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.help()</span></code></a> and load the pre-trained models using
<a class="reference internal" href="#torch.hub.load" title="torch.hub.load"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.load()</span></code></a>.</p>
<span class="target" id="module-torch.hub"></span><dl class="py function">
<dt class="sig sig-object py" id="torch.hub.list">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">list</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">github</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_reload</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_validation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trust_repo</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/pytorch/pytorch/blob/d36b09ca5879caac9296e8cf1f41307a91563d0b/torch/hub.py#L422"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.list" title="Permalink to this definition">#</a></dt>
<dd><p>List all callable entrypoints available in the repo specified by <code class="docutils literal notranslate"><span class="pre">github</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>github</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a>) – a string with format “repo_owner/repo_name[:ref]” with an optional
ref (tag or branch). If <code class="docutils literal notranslate"><span class="pre">ref</span></code> is not specified, the default branch is assumed to be <code class="docutils literal notranslate"><span class="pre">main</span></code> if
it exists, and otherwise <code class="docutils literal notranslate"><span class="pre">master</span></code>.
Example: ‘pytorch/vision:0.10’</p></li>
<li><p><strong>force_reload</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – whether to discard the existing cache and force a fresh download.
Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>skip_validation</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – if <code class="docutils literal notranslate"><span class="pre">False</span></code>, torchhub will check that the branch or commit
specified by the <code class="docutils literal notranslate"><span class="pre">github</span></code> argument properly belongs to the repo owner. This will make
requests to the GitHub API; you can specify a non-default GitHub token by setting the
<code class="docutils literal notranslate"><span class="pre">GITHUB_TOKEN</span></code> environment variable. Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>trust_repo</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a><em> or </em><em>None</em>) – <p><code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code>, <code class="docutils literal notranslate"><span class="pre">False</span></code> or <code class="docutils literal notranslate"><span class="pre">None</span></code>.
This parameter was introduced in v1.12 and helps ensuring that users
only run code from repos that they trust.</p>
<ul>
<li><p>If <code class="docutils literal notranslate"><span class="pre">False</span></code>, a prompt will ask the user whether the repo should
be trusted.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">True</span></code>, the repo will be added to the trusted list and loaded
without requiring explicit confirmation.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code>, the repo will be checked against the list of
trusted repos in the cache. If it is not present in that list, the
behaviour will fall back onto the <code class="docutils literal notranslate"><span class="pre">trust_repo=False</span></code> option.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">None</span></code>: this will raise a warning, inviting the user to set
<code class="docutils literal notranslate"><span class="pre">trust_repo</span></code> to either <code class="docutils literal notranslate"><span class="pre">False</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code> or <code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code>. This
is only present for backward compatibility and will be removed in
v2.0.</p></li>
</ul>
<p>Default is <code class="docutils literal notranslate"><span class="pre">None</span></code> and will eventually change to <code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code> in v2.0.</p>
</p></li>
<li><p><strong>verbose</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – If <code class="docutils literal notranslate"><span class="pre">False</span></code>, mute messages about hitting
local caches. Note that the message about first download cannot be
muted. Default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>The available callables entrypoint</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)">list</a></p>
</dd>
</dl>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">entrypoints</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">list</span><span class="p">(</span><span class="s2">&quot;pytorch/vision&quot;</span><span class="p">,</span> <span class="n">force_reload</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.help">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">help</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">github</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_reload</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_validation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trust_repo</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/pytorch/pytorch/blob/d36b09ca5879caac9296e8cf1f41307a91563d0b/torch/hub.py#L494"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.help" title="Permalink to this definition">#</a></dt>
<dd><p>Show the docstring of entrypoint <code class="docutils literal notranslate"><span class="pre">model</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>github</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a>) – a string with format &lt;repo_owner/repo_name[:ref]&gt; with an optional
ref (a tag or a branch). If <code class="docutils literal notranslate"><span class="pre">ref</span></code> is not specified, the default branch is assumed
to be <code class="docutils literal notranslate"><span class="pre">main</span></code> if it exists, and otherwise <code class="docutils literal notranslate"><span class="pre">master</span></code>.
Example: ‘pytorch/vision:0.10’</p></li>
<li><p><strong>model</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a>) – a string of entrypoint name defined in repo’s <code class="docutils literal notranslate"><span class="pre">hubconf.py</span></code></p></li>
<li><p><strong>force_reload</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – whether to discard the existing cache and force a fresh download.
Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>skip_validation</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – if <code class="docutils literal notranslate"><span class="pre">False</span></code>, torchhub will check that the ref
specified by the <code class="docutils literal notranslate"><span class="pre">github</span></code> argument properly belongs to the repo owner. This will make
requests to the GitHub API; you can specify a non-default GitHub token by setting the
<code class="docutils literal notranslate"><span class="pre">GITHUB_TOKEN</span></code> environment variable. Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>trust_repo</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a><em> or </em><em>None</em>) – <p><code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code>, <code class="docutils literal notranslate"><span class="pre">False</span></code> or <code class="docutils literal notranslate"><span class="pre">None</span></code>.
This parameter was introduced in v1.12 and helps ensuring that users
only run code from repos that they trust.</p>
<ul>
<li><p>If <code class="docutils literal notranslate"><span class="pre">False</span></code>, a prompt will ask the user whether the repo should
be trusted.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">True</span></code>, the repo will be added to the trusted list and loaded
without requiring explicit confirmation.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code>, the repo will be checked against the list of
trusted repos in the cache. If it is not present in that list, the
behaviour will fall back onto the <code class="docutils literal notranslate"><span class="pre">trust_repo=False</span></code> option.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">None</span></code>: this will raise a warning, inviting the user to set
<code class="docutils literal notranslate"><span class="pre">trust_repo</span></code> to either <code class="docutils literal notranslate"><span class="pre">False</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code> or <code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code>. This
is only present for backward compatibility and will be removed in
v2.0.</p></li>
</ul>
<p>Default is <code class="docutils literal notranslate"><span class="pre">None</span></code> and will eventually change to <code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code> in v2.0.</p>
</p></li>
</ul>
</dd>
</dl>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">help</span><span class="p">(</span><span class="s2">&quot;pytorch/vision&quot;</span><span class="p">,</span> <span class="s2">&quot;resnet18&quot;</span><span class="p">,</span> <span class="n">force_reload</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
</pre></div>
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.load">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">repo_or_dir</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'github'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trust_repo</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_reload</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_validation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/pytorch/pytorch/blob/d36b09ca5879caac9296e8cf1f41307a91563d0b/torch/hub.py#L549"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.load" title="Permalink to this definition">#</a></dt>
<dd><p>Load a model from a github repo or a local directory.</p>
<p>Note: Loading a model is the typical use case, but this can also be used to
for loading other objects such as tokenizers, loss functions, etc.</p>
<p>If <code class="docutils literal notranslate"><span class="pre">source</span></code> is ‘github’, <code class="docutils literal notranslate"><span class="pre">repo_or_dir</span></code> is expected to be
of the form <code class="docutils literal notranslate"><span class="pre">repo_owner/repo_name[:ref]</span></code> with an optional
ref (a tag or a branch).</p>
<p>If <code class="docutils literal notranslate"><span class="pre">source</span></code> is ‘local’, <code class="docutils literal notranslate"><span class="pre">repo_or_dir</span></code> is expected to be a
path to a local directory.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>repo_or_dir</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a>) – If <code class="docutils literal notranslate"><span class="pre">source</span></code> is ‘github’,
this should correspond to a github repo with format <code class="docutils literal notranslate"><span class="pre">repo_owner/repo_name[:ref]</span></code> with
an optional ref (tag or branch), for example ‘pytorch/vision:0.10’. If <code class="docutils literal notranslate"><span class="pre">ref</span></code> is not specified,
the default branch is assumed to be <code class="docutils literal notranslate"><span class="pre">main</span></code> if it exists, and otherwise <code class="docutils literal notranslate"><span class="pre">master</span></code>.
If <code class="docutils literal notranslate"><span class="pre">source</span></code> is ‘local’  then it should be a path to a local directory.</p></li>
<li><p><strong>model</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a>) – the name of a callable (entrypoint) defined in the
repo/dir’s <code class="docutils literal notranslate"><span class="pre">hubconf.py</span></code>.</p></li>
<li><p><strong>*args</strong> (<em>optional</em>) – the corresponding args for callable <code class="docutils literal notranslate"><span class="pre">model</span></code>.</p></li>
<li><p><strong>source</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a><em>, </em><em>optional</em>) – ‘github’ or ‘local’. Specifies how
<code class="docutils literal notranslate"><span class="pre">repo_or_dir</span></code> is to be interpreted. Default is ‘github’.</p></li>
<li><p><strong>trust_repo</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a><em> or </em><em>None</em>) – <p><code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code>, <code class="docutils literal notranslate"><span class="pre">False</span></code> or <code class="docutils literal notranslate"><span class="pre">None</span></code>.
This parameter was introduced in v1.12 and helps ensuring that users
only run code from repos that they trust.</p>
<ul>
<li><p>If <code class="docutils literal notranslate"><span class="pre">False</span></code>, a prompt will ask the user whether the repo should
be trusted.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">True</span></code>, the repo will be added to the trusted list and loaded
without requiring explicit confirmation.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code>, the repo will be checked against the list of
trusted repos in the cache. If it is not present in that list, the
behaviour will fall back onto the <code class="docutils literal notranslate"><span class="pre">trust_repo=False</span></code> option.</p></li>
<li><p>If <code class="docutils literal notranslate"><span class="pre">None</span></code>: this will raise a warning, inviting the user to set
<code class="docutils literal notranslate"><span class="pre">trust_repo</span></code> to either <code class="docutils literal notranslate"><span class="pre">False</span></code>, <code class="docutils literal notranslate"><span class="pre">True</span></code> or <code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code>. This
is only present for backward compatibility and will be removed in
v2.0.</p></li>
</ul>
<p>Default is <code class="docutils literal notranslate"><span class="pre">None</span></code> and will eventually change to <code class="docutils literal notranslate"><span class="pre">&quot;check&quot;</span></code> in v2.0.</p>
</p></li>
<li><p><strong>force_reload</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – whether to force a fresh download of
the github repo unconditionally. Does not have any effect if
<code class="docutils literal notranslate"><span class="pre">source</span> <span class="pre">=</span> <span class="pre">'local'</span></code>. Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>verbose</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – If <code class="docutils literal notranslate"><span class="pre">False</span></code>, mute messages about hitting
local caches. Note that the message about first download cannot be
muted. Does not have any effect if <code class="docutils literal notranslate"><span class="pre">source</span> <span class="pre">=</span> <span class="pre">'local'</span></code>.
Default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
<li><p><strong>skip_validation</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – if <code class="docutils literal notranslate"><span class="pre">False</span></code>, torchhub will check that the branch or commit
specified by the <code class="docutils literal notranslate"><span class="pre">github</span></code> argument properly belongs to the repo owner. This will make
requests to the GitHub API; you can specify a non-default GitHub token by setting the
<code class="docutils literal notranslate"><span class="pre">GITHUB_TOKEN</span></code> environment variable. Default is <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p></li>
<li><p><strong>**kwargs</strong> (<em>optional</em>) – the corresponding kwargs for callable <code class="docutils literal notranslate"><span class="pre">model</span></code>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>The output of the <code class="docutils literal notranslate"><span class="pre">model</span></code> callable when called with the given
<code class="docutils literal notranslate"><span class="pre">*args</span></code> and <code class="docutils literal notranslate"><span class="pre">**kwargs</span></code>.</p>
</dd>
</dl>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="c1"># from a github repo</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">repo</span> <span class="o">=</span> <span class="s2">&quot;pytorch/vision&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">model</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">load</span><span class="p">(</span>
<span class="gp">... </span>    <span class="n">repo</span><span class="p">,</span> <span class="s2">&quot;resnet50&quot;</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="s2">&quot;ResNet50_Weights.IMAGENET1K_V1&quot;</span>
<span class="gp">... </span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># from a local directory</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">path</span> <span class="o">=</span> <span class="s2">&quot;/some/local/path/pytorch/vision&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">model</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="s2">&quot;resnet50&quot;</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="s2">&quot;ResNet50_Weights.DEFAULT&quot;</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.download_url_to_file">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">download_url_to_file</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">url</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dst</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hash_prefix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">progress</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/pytorch/pytorch/blob/d36b09ca5879caac9296e8cf1f41307a91563d0b/torch/hub.py#L685"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.download_url_to_file" title="Permalink to this definition">#</a></dt>
<dd><p>Download object at the given URL to a local path.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>url</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a>) – URL of the object to download</p></li>
<li><p><strong>dst</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a>) – Full path where object will be saved, e.g. <code class="docutils literal notranslate"><span class="pre">/tmp/temporary_file</span></code></p></li>
<li><p><strong>hash_prefix</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a><em>, </em><em>optional</em>) – If not None, the SHA256 downloaded file should start with <code class="docutils literal notranslate"><span class="pre">hash_prefix</span></code>.
Default: None</p></li>
<li><p><strong>progress</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – whether or not to display a progress bar to stderr
Default: True</p></li>
</ul>
</dd>
</dl>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">download_url_to_file</span><span class="p">(</span>
<span class="gp">... </span>    <span class="s2">&quot;https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth&quot;</span><span class="p">,</span>
<span class="gp">... </span>    <span class="s2">&quot;/tmp/temporary_file&quot;</span><span class="p">,</span>
<span class="gp">... </span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.load_state_dict_from_url">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">load_state_dict_from_url</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">url</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">map_location</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">progress</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_hash</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weights_only</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/pytorch/pytorch/blob/d36b09ca5879caac9296e8cf1f41307a91563d0b/torch/hub.py#L807"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.load_state_dict_from_url" title="Permalink to this definition">#</a></dt>
<dd><p>Loads the Torch serialized object at the given URL.</p>
<p>If downloaded file is a zip file, it will be automatically
decompressed.</p>
<p>If the object is already present in <cite>model_dir</cite>, it’s deserialized and
returned.
The default value of <code class="docutils literal notranslate"><span class="pre">model_dir</span></code> is <code class="docutils literal notranslate"><span class="pre">&lt;hub_dir&gt;/checkpoints</span></code> where
<code class="docutils literal notranslate"><span class="pre">hub_dir</span></code> is the directory returned by <a class="reference internal" href="#torch.hub.get_dir" title="torch.hub.get_dir"><code class="xref py py-func docutils literal notranslate"><span class="pre">get_dir()</span></code></a>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>url</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a>) – URL of the object to download</p></li>
<li><p><strong>model_dir</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a><em>, </em><em>optional</em>) – directory in which to save the object</p></li>
<li><p><strong>map_location</strong> (<em>optional</em>) – a function or a dict specifying how to remap storage locations (see torch.load)</p></li>
<li><p><strong>progress</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – whether or not to display a progress bar to stderr.
Default: True</p></li>
<li><p><strong>check_hash</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – If True, the filename part of the URL should follow the naming convention
<code class="docutils literal notranslate"><span class="pre">filename-&lt;sha256&gt;.ext</span></code> where <code class="docutils literal notranslate"><span class="pre">&lt;sha256&gt;</span></code> is the first eight or more
digits of the SHA256 hash of the contents of the file. The hash is used to
ensure unique names and to verify the contents of the file.
Default: False</p></li>
<li><p><strong>file_name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a><em>, </em><em>optional</em>) – name for the downloaded file. Filename from <code class="docutils literal notranslate"><span class="pre">url</span></code> will be used if not set.</p></li>
<li><p><strong>weights_only</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><em>bool</em></a><em>, </em><em>optional</em>) – If True, only weights will be loaded and no complex pickled objects.
Recommended for untrusted sources. See <a class="reference internal" href="generated/torch.load.html#torch.load" title="torch.load"><code class="xref py py-func docutils literal notranslate"><span class="pre">load()</span></code></a> for more details.</p></li>
</ul>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.13)">dict</a>[<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)">str</a>, <a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.13)"><em>Any</em></a>]</p>
</dd>
</dl>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">state_dict</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">load_state_dict_from_url</span><span class="p">(</span>
<span class="gp">... </span>    <span class="s2">&quot;https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth&quot;</span>
<span class="gp">... </span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>

<div class="section" id="running-a-loaded-model">
<h3>Running a loaded model:<a class="headerlink" href="#running-a-loaded-model" title="Permalink to this heading">#</a></h3>
<p>Note that <code class="docutils literal notranslate"><span class="pre">*args</span></code> and <code class="docutils literal notranslate"><span class="pre">**kwargs</span></code> in <a class="reference internal" href="#torch.hub.load" title="torch.hub.load"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.hub.load()</span></code></a> are used to
<strong>instantiate</strong> a model. After you have loaded a model, how can you find out
what you can do with the model?
A suggested workflow is</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">dir(model)</span></code> to see all available methods of the model.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">help(model.foo)</span></code> to check what arguments <code class="docutils literal notranslate"><span class="pre">model.foo</span></code> takes to run</p></li>
</ul>
<p>To help users explore without referring to documentation back and forth, we strongly
recommend repo owners make function help messages clear and succinct. It’s also helpful
to include a minimal working example.</p>
</div>
<div class="section" id="where-are-my-downloaded-models-saved">
<h3>Where are my downloaded models saved?<a class="headerlink" href="#where-are-my-downloaded-models-saved" title="Permalink to this heading">#</a></h3>
<p>The locations are used in the order of</p>
<ul class="simple">
<li><p>Calling <code class="docutils literal notranslate"><span class="pre">hub.set_dir(&lt;PATH_TO_HUB_DIR&gt;)</span></code></p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">$TORCH_HOME/hub</span></code>, if environment variable <code class="docutils literal notranslate"><span class="pre">TORCH_HOME</span></code> is set.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">$XDG_CACHE_HOME/torch/hub</span></code>, if environment variable <code class="docutils literal notranslate"><span class="pre">XDG_CACHE_HOME</span></code> is set.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">~/.cache/torch/hub</span></code></p></li>
</ul>
<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.get_dir">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">get_dir</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference external" href="https://github.com/pytorch/pytorch/blob/d36b09ca5879caac9296e8cf1f41307a91563d0b/torch/hub.py#L392"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.get_dir" title="Permalink to this definition">#</a></dt>
<dd><p>Get the Torch Hub cache directory used for storing downloaded models &amp; weights.</p>
<p>If <a class="reference internal" href="#torch.hub.set_dir" title="torch.hub.set_dir"><code class="xref py py-func docutils literal notranslate"><span class="pre">set_dir()</span></code></a> is not called, default path is <code class="docutils literal notranslate"><span class="pre">$TORCH_HOME/hub</span></code> where
environment variable <code class="docutils literal notranslate"><span class="pre">$TORCH_HOME</span></code> defaults to <code class="docutils literal notranslate"><span class="pre">$XDG_CACHE_HOME/torch</span></code>.
<code class="docutils literal notranslate"><span class="pre">$XDG_CACHE_HOME</span></code> follows the X Design Group specification of the Linux
filesystem layout, with a default value <code class="docutils literal notranslate"><span class="pre">~/.cache</span></code> if the environment
variable is not set.</p>
<dl class="field-list simple">
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)">str</a></p>
</dd>
</dl>
</dd></dl>

<dl class="py function">
<dt class="sig sig-object py" id="torch.hub.set_dir">
<span class="sig-prename descclassname"><span class="pre">torch.hub.</span></span><span class="sig-name descname"><span class="pre">set_dir</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/pytorch/pytorch/blob/d36b09ca5879caac9296e8cf1f41307a91563d0b/torch/hub.py#L411"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.hub.set_dir" title="Permalink to this definition">#</a></dt>
<dd><p>Optionally set the Torch Hub directory used to save downloaded models &amp; weights.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>d</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><em>str</em></a>) – path to a local folder to save downloaded models &amp; weights.</p>
</dd>
</dl>
</dd></dl>

</div>
<div class="section" id="caching-logic">
<h3>Caching logic<a class="headerlink" href="#caching-logic" title="Permalink to this heading">#</a></h3>
<p>By default, we don’t clean up files after loading it. Hub uses the cache by default if it already exists in the
directory returned by <a class="reference internal" href="#torch.hub.get_dir" title="torch.hub.get_dir"><code class="xref py py-func docutils literal notranslate"><span class="pre">get_dir()</span></code></a>.</p>
<p>Users can force a reload by calling <code class="docutils literal notranslate"><span class="pre">hub.load(...,</span> <span class="pre">force_reload=True)</span></code>. This will delete
the existing GitHub folder and downloaded weights, reinitialize a fresh download. This is useful
when updates are published to the same branch, users can keep up with the latest release.</p>
</div>
<div class="section" id="known-limitations">
<h3>Known limitations:<a class="headerlink" href="#known-limitations" title="Permalink to this heading">#</a></h3>
<p>Torch hub works by importing the package as if it was installed. There are some side effects
introduced by importing in Python. For example, you can see new items in Python caches
<code class="docutils literal notranslate"><span class="pre">sys.modules</span></code> and <code class="docutils literal notranslate"><span class="pre">sys.path_importer_cache</span></code> which is normal Python behavior.
This also means that you may have import errors when importing different models
from different repos, if the repos have the same sub-package names (typically, a
<code class="docutils literal notranslate"><span class="pre">model</span></code> subpackage). A workaround for these kinds of import errors is to
remove the offending sub-package from the <code class="docutils literal notranslate"><span class="pre">sys.modules</span></code> dict; more details can
be found in <a class="reference external" href="https://github.com/pytorch/hub/issues/243#issuecomment-942403391">this GitHub issue</a>.</p>
<p>A known limitation that is worth mentioning here: users <strong>CANNOT</strong> load two different branches of
the same repo in the <strong>same python process</strong>. It’s just like installing two packages with the
same name in Python, which is not good. Cache might join the party and give you surprises if you
actually try that. Of course it’s totally fine to load them in separate processes.</p>
</div>
</div>
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