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<!DOCTYPE html>
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<li class="toctree-l2"><a class="reference internal" href="../nn.html#parameters">Parameters</a></li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#containers">Containers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#module"><span class="hidden-section">Module</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#sequential"><span class="hidden-section">Sequential</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#modulelist"><span class="hidden-section">ModuleList</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#moduledict"><span class="hidden-section">ModuleDict</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#parameterlist"><span class="hidden-section">ParameterList</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#parameterdict"><span class="hidden-section">ParameterDict</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#convolution-layers">Convolution layers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#conv1d"><span class="hidden-section">Conv1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#conv2d"><span class="hidden-section">Conv2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#conv3d"><span class="hidden-section">Conv3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#convtranspose1d"><span class="hidden-section">ConvTranspose1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#convtranspose2d"><span class="hidden-section">ConvTranspose2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#convtranspose3d"><span class="hidden-section">ConvTranspose3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#unfold"><span class="hidden-section">Unfold</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#fold"><span class="hidden-section">Fold</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#pooling-layers">Pooling layers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#maxpool1d"><span class="hidden-section">MaxPool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#maxpool2d"><span class="hidden-section">MaxPool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#maxpool3d"><span class="hidden-section">MaxPool3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#maxunpool1d"><span class="hidden-section">MaxUnpool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#maxunpool2d"><span class="hidden-section">MaxUnpool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#maxunpool3d"><span class="hidden-section">MaxUnpool3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#avgpool1d"><span class="hidden-section">AvgPool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#avgpool2d"><span class="hidden-section">AvgPool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#avgpool3d"><span class="hidden-section">AvgPool3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#fractionalmaxpool2d"><span class="hidden-section">FractionalMaxPool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#lppool1d"><span class="hidden-section">LPPool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#lppool2d"><span class="hidden-section">LPPool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptivemaxpool1d"><span class="hidden-section">AdaptiveMaxPool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptivemaxpool2d"><span class="hidden-section">AdaptiveMaxPool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptivemaxpool3d"><span class="hidden-section">AdaptiveMaxPool3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptiveavgpool1d"><span class="hidden-section">AdaptiveAvgPool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptiveavgpool2d"><span class="hidden-section">AdaptiveAvgPool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptiveavgpool3d"><span class="hidden-section">AdaptiveAvgPool3d</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#padding-layers">Padding layers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#reflectionpad1d"><span class="hidden-section">ReflectionPad1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#reflectionpad2d"><span class="hidden-section">ReflectionPad2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#replicationpad1d"><span class="hidden-section">ReplicationPad1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#replicationpad2d"><span class="hidden-section">ReplicationPad2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#replicationpad3d"><span class="hidden-section">ReplicationPad3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#zeropad2d"><span class="hidden-section">ZeroPad2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#constantpad1d"><span class="hidden-section">ConstantPad1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#constantpad2d"><span class="hidden-section">ConstantPad2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#constantpad3d"><span class="hidden-section">ConstantPad3d</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#non-linear-activations-weighted-sum-nonlinearity">Non-linear activations (weighted sum, nonlinearity)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#elu"><span class="hidden-section">ELU</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#hardshrink"><span class="hidden-section">Hardshrink</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#hardtanh"><span class="hidden-section">Hardtanh</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#leakyrelu"><span class="hidden-section">LeakyReLU</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#logsigmoid"><span class="hidden-section">LogSigmoid</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#prelu"><span class="hidden-section">PReLU</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#relu"><span class="hidden-section">ReLU</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#relu6"><span class="hidden-section">ReLU6</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#rrelu"><span class="hidden-section">RReLU</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#selu"><span class="hidden-section">SELU</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#sigmoid"><span class="hidden-section">Sigmoid</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#softplus"><span class="hidden-section">Softplus</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#softshrink"><span class="hidden-section">Softshrink</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#softsign"><span class="hidden-section">Softsign</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#tanh"><span class="hidden-section">Tanh</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#tanhshrink"><span class="hidden-section">Tanhshrink</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#threshold"><span class="hidden-section">Threshold</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#non-linear-activations-other">Non-linear activations (other)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#softmin"><span class="hidden-section">Softmin</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#softmax"><span class="hidden-section">Softmax</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#softmax2d"><span class="hidden-section">Softmax2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#logsoftmax"><span class="hidden-section">LogSoftmax</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptivelogsoftmaxwithloss"><span class="hidden-section">AdaptiveLogSoftmaxWithLoss</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#normalization-layers">Normalization layers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#batchnorm1d"><span class="hidden-section">BatchNorm1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#batchnorm2d"><span class="hidden-section">BatchNorm2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#batchnorm3d"><span class="hidden-section">BatchNorm3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#groupnorm"><span class="hidden-section">GroupNorm</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#instancenorm1d"><span class="hidden-section">InstanceNorm1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#instancenorm2d"><span class="hidden-section">InstanceNorm2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#instancenorm3d"><span class="hidden-section">InstanceNorm3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#layernorm"><span class="hidden-section">LayerNorm</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#localresponsenorm"><span class="hidden-section">LocalResponseNorm</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#recurrent-layers">Recurrent layers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#rnn"><span class="hidden-section">RNN</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#lstm"><span class="hidden-section">LSTM</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#gru"><span class="hidden-section">GRU</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#rnncell"><span class="hidden-section">RNNCell</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#lstmcell"><span class="hidden-section">LSTMCell</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#grucell"><span class="hidden-section">GRUCell</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#linear-layers">Linear layers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#linear"><span class="hidden-section">Linear</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#bilinear"><span class="hidden-section">Bilinear</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#dropout-layers">Dropout layers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#dropout"><span class="hidden-section">Dropout</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#dropout2d"><span class="hidden-section">Dropout2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#dropout3d"><span class="hidden-section">Dropout3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#alphadropout"><span class="hidden-section">AlphaDropout</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#sparse-layers">Sparse layers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#embedding"><span class="hidden-section">Embedding</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#embeddingbag"><span class="hidden-section">EmbeddingBag</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#distance-functions">Distance functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#cosinesimilarity"><span class="hidden-section">CosineSimilarity</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#pairwisedistance"><span class="hidden-section">PairwiseDistance</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#loss-functions">Loss functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#l1loss"><span class="hidden-section">L1Loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#mseloss"><span class="hidden-section">MSELoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#crossentropyloss"><span class="hidden-section">CrossEntropyLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#nllloss"><span class="hidden-section">NLLLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#poissonnllloss"><span class="hidden-section">PoissonNLLLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#kldivloss"><span class="hidden-section">KLDivLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#bceloss"><span class="hidden-section">BCELoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#bcewithlogitsloss"><span class="hidden-section">BCEWithLogitsLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#marginrankingloss"><span class="hidden-section">MarginRankingLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#hingeembeddingloss"><span class="hidden-section">HingeEmbeddingLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#multilabelmarginloss"><span class="hidden-section">MultiLabelMarginLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#smoothl1loss"><span class="hidden-section">SmoothL1Loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#softmarginloss"><span class="hidden-section">SoftMarginLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#multilabelsoftmarginloss"><span class="hidden-section">MultiLabelSoftMarginLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#cosineembeddingloss"><span class="hidden-section">CosineEmbeddingLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#multimarginloss"><span class="hidden-section">MultiMarginLoss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#tripletmarginloss"><span class="hidden-section">TripletMarginLoss</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#vision-layers">Vision layers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#pixelshuffle"><span class="hidden-section">PixelShuffle</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#upsample"><span class="hidden-section">Upsample</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#upsamplingnearest2d"><span class="hidden-section">UpsamplingNearest2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#upsamplingbilinear2d"><span class="hidden-section">UpsamplingBilinear2d</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#dataparallel-layers-multi-gpu-distributed">DataParallel layers (multi-GPU, distributed)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#dataparallel"><span class="hidden-section">DataParallel</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#distributeddataparallel"><span class="hidden-section">DistributedDataParallel</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#utilities">Utilities</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#clip-grad-norm"><span class="hidden-section">clip_grad_norm_</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#clip-grad-value"><span class="hidden-section">clip_grad_value_</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#parameters-to-vector"><span class="hidden-section">parameters_to_vector</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#vector-to-parameters"><span class="hidden-section">vector_to_parameters</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#weight-norm"><span class="hidden-section">weight_norm</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#remove-weight-norm"><span class="hidden-section">remove_weight_norm</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#spectral-norm"><span class="hidden-section">spectral_norm</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#remove-spectral-norm"><span class="hidden-section">remove_spectral_norm</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#packedsequence"><span class="hidden-section">PackedSequence</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#pack-padded-sequence"><span class="hidden-section">pack_padded_sequence</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#pad-packed-sequence"><span class="hidden-section">pad_packed_sequence</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#pad-sequence"><span class="hidden-section">pad_sequence</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#pack-sequence"><span class="hidden-section">pack_sequence</span></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../nn.html#torch-nn-functional">torch.nn.functional</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#convolution-functions">Convolution functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id20"><span class="hidden-section">conv1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id21"><span class="hidden-section">conv2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id22"><span class="hidden-section">conv3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#conv-transpose1d"><span class="hidden-section">conv_transpose1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#conv-transpose2d"><span class="hidden-section">conv_transpose2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#conv-transpose3d"><span class="hidden-section">conv_transpose3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id23"><span class="hidden-section">unfold</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id24"><span class="hidden-section">fold</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#pooling-functions">Pooling functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#avg-pool1d"><span class="hidden-section">avg_pool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#avg-pool2d"><span class="hidden-section">avg_pool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#avg-pool3d"><span class="hidden-section">avg_pool3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#max-pool1d"><span class="hidden-section">max_pool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#max-pool2d"><span class="hidden-section">max_pool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#max-pool3d"><span class="hidden-section">max_pool3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#max-unpool1d"><span class="hidden-section">max_unpool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#max-unpool2d"><span class="hidden-section">max_unpool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#max-unpool3d"><span class="hidden-section">max_unpool3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#lp-pool1d"><span class="hidden-section">lp_pool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#lp-pool2d"><span class="hidden-section">lp_pool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptive-max-pool1d"><span class="hidden-section">adaptive_max_pool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptive-max-pool2d"><span class="hidden-section">adaptive_max_pool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptive-max-pool3d"><span class="hidden-section">adaptive_max_pool3d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptive-avg-pool1d"><span class="hidden-section">adaptive_avg_pool1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptive-avg-pool2d"><span class="hidden-section">adaptive_avg_pool2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#adaptive-avg-pool3d"><span class="hidden-section">adaptive_avg_pool3d</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#non-linear-activation-functions">Non-linear activation functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id25"><span class="hidden-section">threshold</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id26"><span class="hidden-section">relu</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id27"><span class="hidden-section">hardtanh</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id28"><span class="hidden-section">relu6</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id29"><span class="hidden-section">elu</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id30"><span class="hidden-section">selu</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#leaky-relu"><span class="hidden-section">leaky_relu</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id31"><span class="hidden-section">prelu</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id32"><span class="hidden-section">rrelu</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#glu"><span class="hidden-section">glu</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id33"><span class="hidden-section">logsigmoid</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id34"><span class="hidden-section">hardshrink</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id35"><span class="hidden-section">tanhshrink</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id36"><span class="hidden-section">softsign</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id37"><span class="hidden-section">softplus</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id38"><span class="hidden-section">softmin</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id39"><span class="hidden-section">softmax</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id40"><span class="hidden-section">softshrink</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#gumbel-softmax"><span class="hidden-section">gumbel_softmax</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#log-softmax"><span class="hidden-section">log_softmax</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id41"><span class="hidden-section">tanh</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id42"><span class="hidden-section">sigmoid</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#normalization-functions">Normalization functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#batch-norm"><span class="hidden-section">batch_norm</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#instance-norm"><span class="hidden-section">instance_norm</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#layer-norm"><span class="hidden-section">layer_norm</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#local-response-norm"><span class="hidden-section">local_response_norm</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#normalize"><span class="hidden-section">normalize</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#linear-functions">Linear functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id43"><span class="hidden-section">linear</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id44"><span class="hidden-section">bilinear</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#dropout-functions">Dropout functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id45"><span class="hidden-section">dropout</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#alpha-dropout"><span class="hidden-section">alpha_dropout</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id46"><span class="hidden-section">dropout2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id47"><span class="hidden-section">dropout3d</span></a></li>
</ul>
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<li class="toctree-l2"><a class="reference internal" href="../nn.html#sparse-functions">Sparse functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id48"><span class="hidden-section">embedding</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#embedding-bag"><span class="hidden-section">embedding_bag</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#id49">Distance functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#pairwise-distance"><span class="hidden-section">pairwise_distance</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#cosine-similarity"><span class="hidden-section">cosine_similarity</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#id50">Loss functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#binary-cross-entropy"><span class="hidden-section">binary_cross_entropy</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#poisson-nll-loss"><span class="hidden-section">poisson_nll_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#cosine-embedding-loss"><span class="hidden-section">cosine_embedding_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#cross-entropy"><span class="hidden-section">cross_entropy</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#hinge-embedding-loss"><span class="hidden-section">hinge_embedding_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#kl-div"><span class="hidden-section">kl_div</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#l1-loss"><span class="hidden-section">l1_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#mse-loss"><span class="hidden-section">mse_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#margin-ranking-loss"><span class="hidden-section">margin_ranking_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#multilabel-margin-loss"><span class="hidden-section">multilabel_margin_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#multilabel-soft-margin-loss"><span class="hidden-section">multilabel_soft_margin_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#multi-margin-loss"><span class="hidden-section">multi_margin_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#nll-loss"><span class="hidden-section">nll_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#binary-cross-entropy-with-logits"><span class="hidden-section">binary_cross_entropy_with_logits</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#smooth-l1-loss"><span class="hidden-section">smooth_l1_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#soft-margin-loss"><span class="hidden-section">soft_margin_loss</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#triplet-margin-loss"><span class="hidden-section">triplet_margin_loss</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#vision-functions">Vision functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#pixel-shuffle"><span class="hidden-section">pixel_shuffle</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#pad"><span class="hidden-section">pad</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#interpolate"><span class="hidden-section">interpolate</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id51"><span class="hidden-section">upsample</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#upsample-nearest"><span class="hidden-section">upsample_nearest</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#upsample-bilinear"><span class="hidden-section">upsample_bilinear</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#grid-sample"><span class="hidden-section">grid_sample</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#affine-grid"><span class="hidden-section">affine_grid</span></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#dataparallel-functions-multi-gpu-distributed">DataParallel functions (multi-GPU, distributed)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#data-parallel"><span class="hidden-section">data_parallel</span></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../nn.html#torch-nn-init">torch.nn.init</a></li>
<li class="toctree-l1"><a class="reference internal" href="../optim.html">torch.optim</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../optim.html#how-to-use-an-optimizer">How to use an optimizer</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../optim.html#constructing-it">Constructing it</a></li>
<li class="toctree-l3"><a class="reference internal" href="../optim.html#per-parameter-options">Per-parameter options</a></li>
<li class="toctree-l3"><a class="reference internal" href="../optim.html#taking-an-optimization-step">Taking an optimization step</a><ul>
<li class="toctree-l4"><a class="reference internal" href="../optim.html#optimizer-step"><code class="docutils literal notranslate"><span class="pre">optimizer.step()</span></code></a></li>
<li class="toctree-l4"><a class="reference internal" href="../optim.html#optimizer-step-closure"><code class="docutils literal notranslate"><span class="pre">optimizer.step(closure)</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../optim.html#algorithms">Algorithms</a></li>
<li class="toctree-l2"><a class="reference internal" href="../optim.html#how-to-adjust-learning-rate">How to adjust Learning Rate</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../autograd.html">torch.autograd</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../autograd.html#locally-disabling-gradient-computation">Locally disabling gradient computation</a></li>
<li class="toctree-l2"><a class="reference internal" href="../autograd.html#in-place-operations-on-tensors">In-place operations on Tensors</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../autograd.html#in-place-correctness-checks">In-place correctness checks</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../autograd.html#variable-deprecated">Variable (deprecated)</a></li>
<li class="toctree-l2"><a class="reference internal" href="../autograd.html#tensor-autograd-functions">Tensor autograd functions</a></li>
<li class="toctree-l2"><a class="reference internal" href="../autograd.html#function"><span class="hidden-section">Function</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../autograd.html#numerical-gradient-checking">Numerical gradient checking</a></li>
<li class="toctree-l2"><a class="reference internal" href="../autograd.html#profiler">Profiler</a></li>
<li class="toctree-l2"><a class="reference internal" href="../autograd.html#anomaly-detection">Anomaly detection</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../distributions.html">torch.distributions</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#score-function">Score function</a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#pathwise-derivative">Pathwise derivative</a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#distribution"><span class="hidden-section">Distribution</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#exponentialfamily"><span class="hidden-section">ExponentialFamily</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#bernoulli"><span class="hidden-section">Bernoulli</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#beta"><span class="hidden-section">Beta</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#binomial"><span class="hidden-section">Binomial</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#categorical"><span class="hidden-section">Categorical</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#cauchy"><span class="hidden-section">Cauchy</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#chi2"><span class="hidden-section">Chi2</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#dirichlet"><span class="hidden-section">Dirichlet</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#exponential"><span class="hidden-section">Exponential</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#fishersnedecor"><span class="hidden-section">FisherSnedecor</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#gamma"><span class="hidden-section">Gamma</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#geometric"><span class="hidden-section">Geometric</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#gumbel"><span class="hidden-section">Gumbel</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#halfcauchy"><span class="hidden-section">HalfCauchy</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#halfnormal"><span class="hidden-section">HalfNormal</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#independent"><span class="hidden-section">Independent</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#laplace"><span class="hidden-section">Laplace</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#lognormal"><span class="hidden-section">LogNormal</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#multinomial"><span class="hidden-section">Multinomial</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#multivariatenormal"><span class="hidden-section">MultivariateNormal</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#normal"><span class="hidden-section">Normal</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#onehotcategorical"><span class="hidden-section">OneHotCategorical</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#pareto"><span class="hidden-section">Pareto</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#poisson"><span class="hidden-section">Poisson</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#relaxedbernoulli"><span class="hidden-section">RelaxedBernoulli</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#relaxedonehotcategorical"><span class="hidden-section">RelaxedOneHotCategorical</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#studentt"><span class="hidden-section">StudentT</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#transformeddistribution"><span class="hidden-section">TransformedDistribution</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#uniform"><span class="hidden-section">Uniform</span></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#module-torch.distributions.kl"><cite>KL Divergence</cite></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#module-torch.distributions.transforms"><cite>Transforms</cite></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#module-torch.distributions.constraints"><cite>Constraints</cite></a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributions.html#module-torch.distributions.constraint_registry"><cite>Constraint Registry</cite></a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../multiprocessing.html">torch.multiprocessing</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../multiprocessing.html#strategy-management">Strategy management</a></li>
<li class="toctree-l2"><a class="reference internal" href="../multiprocessing.html#sharing-cuda-tensors">Sharing CUDA tensors</a></li>
<li class="toctree-l2"><a class="reference internal" href="../multiprocessing.html#sharing-strategies">Sharing strategies</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../multiprocessing.html#file-descriptor-file-descriptor">File descriptor - <code class="docutils literal notranslate"><span class="pre">file_descriptor</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="../multiprocessing.html#file-system-file-system">File system - <code class="docutils literal notranslate"><span class="pre">file_system</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../distributed.html">torch.distributed</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../distributed.html#basics">Basics</a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributed.html#initialization">Initialization</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../distributed.html#tcp-initialization">TCP initialization</a></li>
<li class="toctree-l3"><a class="reference internal" href="../distributed.html#shared-file-system-initialization">Shared file-system initialization</a></li>
<li class="toctree-l3"><a class="reference internal" href="../distributed.html#environment-variable-initialization">Environment variable initialization</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../distributed.html#groups">Groups</a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributed.html#point-to-point-communication">Point-to-point communication</a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributed.html#collective-functions">Collective functions</a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributed.html#multi-gpu-collective-functions">Multi-GPU collective functions</a></li>
<li class="toctree-l2"><a class="reference internal" href="../distributed.html#launch-utility">Launch utility</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../bottleneck.html">torch.utils.bottleneck</a></li>
<li class="toctree-l1"><a class="reference internal" href="../checkpoint.html">torch.utils.checkpoint</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../data.html">torch.utils.data</a></li>
<li class="toctree-l1"><a class="reference internal" href="../dlpack.html">torch.utils.dlpack</a></li>
<li class="toctree-l1"><a class="reference internal" href="../ffi.html">torch.utils.ffi</a></li>
<li class="toctree-l1"><a class="reference internal" href="../model_zoo.html">torch.utils.model_zoo</a></li>
<li class="toctree-l1"><a class="reference internal" href="../onnx.html">torch.onnx</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../onnx.html#example-end-to-end-alexnet-from-pytorch-to-caffe2">Example: End-to-end AlexNet from PyTorch to Caffe2</a></li>
<li class="toctree-l2"><a class="reference internal" href="../onnx.html#limitations">Limitations</a></li>
<li class="toctree-l2"><a class="reference internal" href="../onnx.html#supported-operators">Supported operators</a></li>
<li class="toctree-l2"><a class="reference internal" href="../onnx.html#functions">Functions</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../legacy.html">torch.legacy</a></li>
</ul>
<p class="caption"><span class="caption-text">torchvision Reference</span></p>
<ul class="current">
<li class="toctree-l1 current"><a class="reference internal" href="index.html">torchvision</a><ul class="current">
<li class="toctree-l2"><a class="reference internal" href="datasets.html">torchvision.datasets</a><ul>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#mnist">MNIST</a></li>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#fashion-mnist">Fashion-MNIST</a></li>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#emnist">EMNIST</a></li>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#coco">COCO</a><ul>
<li class="toctree-l4"><a class="reference internal" href="datasets.html#captions">Captions</a></li>
<li class="toctree-l4"><a class="reference internal" href="datasets.html#detection">Detection</a></li>
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<li class="toctree-l3"><a class="reference internal" href="datasets.html#lsun">LSUN</a></li>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#imagefolder">ImageFolder</a></li>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#datasetfolder">DatasetFolder</a></li>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#imagenet-12">Imagenet-12</a></li>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#cifar">CIFAR</a></li>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#stl10">STL10</a></li>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#svhn">SVHN</a></li>
<li class="toctree-l3"><a class="reference internal" href="datasets.html#phototour">PhotoTour</a></li>
</ul>
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<li class="toctree-l2"><a class="reference internal" href="models.html">torchvision.models</a><ul>
<li class="toctree-l3"><a class="reference internal" href="models.html#id1">Alexnet</a></li>
<li class="toctree-l3"><a class="reference internal" href="models.html#id2">VGG</a></li>
<li class="toctree-l3"><a class="reference internal" href="models.html#id3">ResNet</a></li>
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<li class="toctree-l2 current"><a class="current reference internal" href="#">torchvision.transforms</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#transforms-on-pil-image">Transforms on PIL Image</a></li>
<li class="toctree-l3"><a class="reference internal" href="#transforms-on-torch-tensor">Transforms on torch.*Tensor</a></li>
<li class="toctree-l3"><a class="reference internal" href="#conversion-transforms">Conversion Transforms</a></li>
<li class="toctree-l3"><a class="reference internal" href="#generic-transforms">Generic Transforms</a></li>
<li class="toctree-l3"><a class="reference internal" href="#module-torchvision.transforms.functional">Functional Transforms</a></li>
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<div class="section" id="torchvision-transforms">
<h1>torchvision.transforms<a class="headerlink" href="#torchvision-transforms" title="Permalink to this headline">¶</a></h1>
<p>Transforms are common image transforms. They can be chained together using <a class="reference internal" href="#torchvision.transforms.Compose" title="torchvision.transforms.Compose"><code class="xref py py-class docutils literal notranslate"><span class="pre">Compose</span></code></a></p>
<dl class="class">
<dt id="torchvision.transforms.Compose">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">Compose</code><span class="sig-paren">(</span><em>transforms</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.Compose" title="Permalink to this definition">¶</a></dt>
<dd><p>Composes several transforms together.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>transforms</strong> (list of <code class="docutils literal notranslate"><span class="pre">Transform</span></code> objects) – list of transforms to compose.</td>
</tr>
</tbody>
</table>
<p class="rubric">Example</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span>
<span class="gp">>>> </span> <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="mi">10</span><span class="p">),</span>
<span class="gp">>>> </span> <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
<span class="gp">>>> </span><span class="p">])</span>
</pre></div>
</div>
</dd></dl>
<div class="section" id="transforms-on-pil-image">
<h2>Transforms on PIL Image<a class="headerlink" href="#transforms-on-pil-image" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="torchvision.transforms.CenterCrop">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">CenterCrop</code><span class="sig-paren">(</span><em>size</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.CenterCrop" title="Permalink to this definition">¶</a></dt>
<dd><p>Crops the given PIL Image at the center.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>size</strong> (<em>sequence</em><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – Desired output size of the crop. If size is an
int instead of sequence like (h, w), a square crop (size, size) is
made.</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="class">
<dt id="torchvision.transforms.ColorJitter">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">ColorJitter</code><span class="sig-paren">(</span><em>brightness=0</em>, <em>contrast=0</em>, <em>saturation=0</em>, <em>hue=0</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.ColorJitter" title="Permalink to this definition">¶</a></dt>
<dd><p>Randomly change the brightness, contrast and saturation of an image.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>brightness</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.7)"><em>float</em></a>) – How much to jitter brightness. brightness_factor
is chosen uniformly from [max(0, 1 - brightness), 1 + brightness].</li>
<li><strong>contrast</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.7)"><em>float</em></a>) – How much to jitter contrast. contrast_factor
is chosen uniformly from [max(0, 1 - contrast), 1 + contrast].</li>
<li><strong>saturation</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.7)"><em>float</em></a>) – How much to jitter saturation. saturation_factor
is chosen uniformly from [max(0, 1 - saturation), 1 + saturation].</li>
<li><strong>hue</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.7)"><em>float</em></a>) – How much to jitter hue. hue_factor is chosen uniformly from
[-hue, hue]. Should be >=0 and <= 0.5.</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="class">
<dt id="torchvision.transforms.FiveCrop">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">FiveCrop</code><span class="sig-paren">(</span><em>size</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.FiveCrop" title="Permalink to this definition">¶</a></dt>
<dd><p>Crop the given PIL Image into four corners and the central crop</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">This transform returns a tuple of images and there may be a mismatch in the number of
inputs and targets your Dataset returns. See below for an example of how to deal with
this.</p>
</div>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>size</strong> (<em>sequence</em><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – Desired output size of the crop. If size is an <code class="docutils literal notranslate"><span class="pre">int</span></code>
instead of sequence like (h, w), a square crop of size (size, size) is made.</td>
</tr>
</tbody>
</table>
<p class="rubric">Example</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">transform</span> <span class="o">=</span> <span class="n">Compose</span><span class="p">([</span>
<span class="gp">>>> </span> <span class="n">FiveCrop</span><span class="p">(</span><span class="n">size</span><span class="p">),</span> <span class="c1"># this is a list of PIL Images</span>
<span class="gp">>>> </span> <span class="n">Lambda</span><span class="p">(</span><span class="k">lambda</span> <span class="n">crops</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">stack</span><span class="p">([</span><span class="n">ToTensor</span><span class="p">()(</span><span class="n">crop</span><span class="p">)</span> <span class="k">for</span> <span class="n">crop</span> <span class="ow">in</span> <span class="n">crops</span><span class="p">]))</span> <span class="c1"># returns a 4D tensor</span>
<span class="gp">>>> </span><span class="p">])</span>
<span class="gp">>>> </span><span class="c1">#In your test loop you can do the following:</span>
<span class="gp">>>> </span><span class="nb">input</span><span class="p">,</span> <span class="n">target</span> <span class="o">=</span> <span class="n">batch</span> <span class="c1"># input is a 5d tensor, target is 2d</span>
<span class="gp">>>> </span><span class="n">bs</span><span class="p">,</span> <span class="n">ncrops</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">h</span><span class="p">,</span> <span class="n">w</span> <span class="o">=</span> <span class="nb">input</span><span class="o">.</span><span class="n">size</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">result</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="nb">input</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">h</span><span class="p">,</span> <span class="n">w</span><span class="p">))</span> <span class="c1"># fuse batch size and ncrops</span>
<span class="gp">>>> </span><span class="n">result_avg</span> <span class="o">=</span> <span class="n">result</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">bs</span><span class="p">,</span> <span class="n">ncrops</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="c1"># avg over crops</span>
</pre></div>
</div>
</dd></dl>
<dl class="class">
<dt id="torchvision.transforms.Grayscale">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">Grayscale</code><span class="sig-paren">(</span><em>num_output_channels=1</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.Grayscale" title="Permalink to this definition">¶</a></dt>
<dd><p>Convert image to grayscale.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>num_output_channels</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – (1 or 3) number of channels desired for output image</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">Grayscale version of the input.
- If num_output_channels == 1 : returned image is single channel
- If num_output_channels == 3 : returned image is 3 channel with r == g == b</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">PIL Image</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="class">
<dt id="torchvision.transforms.LinearTransformation">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">LinearTransformation</code><span class="sig-paren">(</span><em>transformation_matrix</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.LinearTransformation" title="Permalink to this definition">¶</a></dt>
<dd><p>Transform a tensor image with a square transformation matrix computed
offline.</p>
<p>Given transformation_matrix, will flatten the torch.*Tensor, compute the dot
product with the transformation matrix and reshape the tensor to its
original shape.</p>
<dl class="docutils">
<dt>Applications:</dt>
<dd><ul class="first last simple">
<li><dl class="first docutils">
<dt>whitening: zero-center the data, compute the data covariance matrix</dt>
<dd>[D x D] with np.dot(X.T, X), perform SVD on this matrix and
pass it as transformation_matrix.</dd>
</dl>
</li>
</ul>
</dd>
</dl>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>transformation_matrix</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – tensor [D x D], D = C x H x W</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="class">
<dt id="torchvision.transforms.Pad">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">Pad</code><span class="sig-paren">(</span><em>padding</em>, <em>fill=0</em>, <em>padding_mode='constant'</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.Pad" title="Permalink to this definition">¶</a></dt>
<dd><p>Pad the given PIL Image on all sides with the given “pad” value.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>padding</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.7)"><em>tuple</em></a>) – Padding on each border. If a single int is provided this
is used to pad all borders. If tuple of length 2 is provided this is the padding
on left/right and top/bottom respectively. If a tuple of length 4 is provided
this is the padding for the left, top, right and bottom borders
respectively.</li>
<li><strong>fill</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.7)"><em>tuple</em></a>) – Pixel fill value for constant fill. Default is 0. If a tuple of
length 3, it is used to fill R, G, B channels respectively.
This value is only used when the padding_mode is constant</li>
<li><strong>padding_mode</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – <p>Type of padding. Should be: constant, edge, reflect or symmetric.
Default is constant.</p>
<ul>
<li>constant: pads with a constant value, this value is specified with fill</li>
<li>edge: pads with the last value at the edge of the image</li>
<li>reflect: pads with reflection of image without repeating the last value on the edge<blockquote>
<div>For example, padding [1, 2, 3, 4] with 2 elements on both sides in reflect mode
will result in [3, 2, 1, 2, 3, 4, 3, 2]</div></blockquote>
</li>
<li>symmetric: pads with reflection of image repeating the last value on the edge<blockquote>
<div>For example, padding [1, 2, 3, 4] with 2 elements on both sides in symmetric mode
will result in [2, 1, 1, 2, 3, 4, 4, 3]</div></blockquote>
</li>
</ul>
</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="class">
<dt id="torchvision.transforms.RandomAffine">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">RandomAffine</code><span class="sig-paren">(</span><em>degrees</em>, <em>translate=None</em>, <em>scale=None</em>, <em>shear=None</em>, <em>resample=False</em>, <em>fillcolor=0</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.RandomAffine" title="Permalink to this definition">¶</a></dt>
<dd><p>Random affine transformation of the image keeping center invariant</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>degrees</strong> (<em>sequence</em><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.7)"><em>float</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – Range of degrees to select from.
If degrees is a number instead of sequence like (min, max), the range of degrees
will be (-degrees, +degrees). Set to 0 to desactivate rotations.</li>
<li><strong>translate</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.7)"><em>tuple</em></a><em>, </em><em>optional</em>) – tuple of maximum absolute fraction for horizontal
and vertical translations. For example translate=(a, b), then horizontal shift
is randomly sampled in the range -img_width * a < dx < img_width * a and vertical shift is
randomly sampled in the range -img_height * b < dy < img_height * b. Will not translate by default.</li>
<li><strong>scale</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.7)"><em>tuple</em></a><em>, </em><em>optional</em>) – scaling factor interval, e.g (a, b), then scale is
randomly sampled from the range a <= scale <= b. Will keep original scale by default.</li>
<li><strong>shear</strong> (<em>sequence</em><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.7)"><em>float</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a><em>, </em><em>optional</em>) – Range of degrees to select from.
If degrees is a number instead of sequence like (min, max), the range of degrees
will be (-degrees, +degrees). Will not apply shear by default</li>
<li><strong>resample</strong> (<em>{PIL.Image.NEAREST</em><em>, </em><em>PIL.Image.BILINEAR</em><em>, </em><em>PIL.Image.BICUBIC}</em><em>, </em><em>optional</em>) – An optional resampling filter. See <a class="reference external" href="https://pillow.readthedocs.io/en/latest/handbook/concepts.html#filters">filters</a> for more information.
If omitted, or if the image has mode “1” or “P”, it is set to PIL.Image.NEAREST.</li>
<li><strong>fillcolor</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – Optional fill color for the area outside the transform in the output image. (Pillow>=5.0.0)</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="class">
<dt id="torchvision.transforms.RandomApply">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">RandomApply</code><span class="sig-paren">(</span><em>transforms</em>, <em>p=0.5</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.RandomApply" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply randomly a list of transformations with a given probability</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>transforms</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.7)"><em>list</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.7)"><em>tuple</em></a>) – list of transformations</li>
<li><strong>p</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.7)"><em>float</em></a>) – probability</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="class">
<dt id="torchvision.transforms.RandomChoice">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">RandomChoice</code><span class="sig-paren">(</span><em>transforms</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.RandomChoice" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply single transformation randomly picked from a list</p>
</dd></dl>
<dl class="class">
<dt id="torchvision.transforms.RandomCrop">
<em class="property">class </em><code class="descclassname">torchvision.transforms.</code><code class="descname">RandomCrop</code><span class="sig-paren">(</span><em>size</em>, <em>padding=None</em>, <em>pad_if_needed=False</em>, <em>fill=0</em>, <em>padding_mode='constant'</em><span class="sig-paren">)</span><a class="headerlink" href="#torchvision.transforms.RandomCrop" title="Permalink to this definition">¶</a></dt>
<dd><p>Crop the given PIL Image at a random location.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />