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<!DOCTYPE html>
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<p class="caption"><span class="caption-text">Notes</span></p>
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<li class="toctree-l1"><a class="reference internal" href="notes/autograd.html">Autograd mechanics</a><ul>
<li class="toctree-l2"><a class="reference internal" href="notes/autograd.html#excluding-subgraphs-from-backward">Excluding subgraphs from backward</a><ul>
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<p class="caption"><span class="caption-text">Package Reference</span></p>
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<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#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>
</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>
</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>
</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>
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</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#pairwisedistance"><span class="hidden-section">PairwiseDistance</span></a></li>
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</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#nllloss2d"><span class="hidden-section">NLLLoss2d</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#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>
</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#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#multi-gpu-layers">Multi-GPU layers</a><ul>
<li class="toctree-l3"><a class="reference internal" href="nn.html#dataparallel"><span class="hidden-section">DataParallel</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#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>
</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#id13"><span class="hidden-section">conv1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id14"><span class="hidden-section">conv2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id15"><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>
</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-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-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>
</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#id16"><span class="hidden-section">threshold</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id17"><span class="hidden-section">relu</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id18"><span class="hidden-section">hardtanh</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id19"><span class="hidden-section">relu6</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id20"><span class="hidden-section">elu</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#id21"><span class="hidden-section">prelu</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#id22"><span class="hidden-section">logsigmoid</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#id23"><span class="hidden-section">tanhshrink</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id24"><span class="hidden-section">softsign</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id25"><span class="hidden-section">softplus</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id26"><span class="hidden-section">softmin</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id27"><span class="hidden-section">softmax</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id28"><span class="hidden-section">softshrink</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#id29"><span class="hidden-section">tanh</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="nn.html#id30"><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>
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<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#id31"><span class="hidden-section">linear</span></a></li>
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<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#id32"><span class="hidden-section">dropout</span></a></li>
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<li class="toctree-l2"><a class="reference internal" href="nn.html#id33">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>
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<li class="toctree-l2"><a class="reference internal" href="nn.html#id34">Loss functions</a><ul>
<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#kl-div"><span class="hidden-section">kl_div</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#binary-cross-entropy"><span class="hidden-section">binary_cross_entropy</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>
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<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>
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<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>
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<li class="toctree-l3"><a class="reference internal" href="optim.html#per-parameter-options">Per-parameter options</a></li>
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<li class="toctree-l4"><a class="reference internal" href="optim.html#optimizer-step"><code class="docutils literal"><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"><span class="pre">optimizer.step(closure)</span></code></a></li>
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<li class="toctree-l3"><a class="reference internal" href="autograd.html#in-place-correctness-checks">In-place correctness checks</a></li>
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<li class="toctree-l2"><a class="reference internal" href="autograd.html#function"><span class="hidden-section">Function</span></a></li>
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<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>
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<li class="toctree-l1"><a class="reference internal" href="legacy.html">torch.legacy</a></li>
<li class="toctree-l1"><a class="reference internal" href="cuda.html">torch.cuda</a><ul>
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<li class="toctree-l1"><a class="reference internal" href="ffi.html">torch.utils.ffi</a></li>
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<p class="caption"><span class="caption-text">torchvision Reference</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="torchvision/torchvision.html">torchvision</a></li>
<li class="toctree-l1"><a class="reference internal" href="torchvision/datasets.html">torchvision.datasets</a><ul>
<li class="toctree-l2"><a class="reference internal" href="torchvision/datasets.html#mnist">MNIST</a></li>
<li class="toctree-l2"><a class="reference internal" href="torchvision/datasets.html#coco">COCO</a><ul>
<li class="toctree-l3"><a class="reference internal" href="torchvision/datasets.html#captions">Captions:</a></li>
<li class="toctree-l3"><a class="reference internal" href="torchvision/datasets.html#detection">Detection:</a></li>
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<li class="toctree-l2"><a class="reference internal" href="torchvision/datasets.html#lsun">LSUN</a></li>
<li class="toctree-l2"><a class="reference internal" href="torchvision/datasets.html#imagefolder">ImageFolder</a></li>
<li class="toctree-l2"><a class="reference internal" href="torchvision/datasets.html#imagenet-12">Imagenet-12</a></li>
<li class="toctree-l2"><a class="reference internal" href="torchvision/datasets.html#cifar">CIFAR</a></li>
<li class="toctree-l2"><a class="reference internal" href="torchvision/datasets.html#stl10">STL10</a></li>
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<li class="toctree-l1"><a class="reference internal" href="torchvision/models.html">torchvision.models</a></li>
<li class="toctree-l1"><a class="reference internal" href="torchvision/transforms.html">torchvision.transforms</a><ul>
<li class="toctree-l2"><a class="reference internal" href="torchvision/transforms.html#transforms-on-pil-image">Transforms on PIL.Image</a></li>
<li class="toctree-l2"><a class="reference internal" href="torchvision/transforms.html#transforms-on-torch-tensor">Transforms on torch.*Tensor</a></li>
<li class="toctree-l2"><a class="reference internal" href="torchvision/transforms.html#conversion-transforms">Conversion Transforms</a></li>
<li class="toctree-l2"><a class="reference internal" href="torchvision/transforms.html#generic-transforms">Generic Transforms</a></li>
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<li class="toctree-l1"><a class="reference internal" href="torchvision/utils.html">torchvision.utils</a></li>
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<h2 id="A">A</h2>
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<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="torch.html#torch.abs">abs() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.abs">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.abs_">abs_() (torch.Tensor method)</a>
</li>
<li><a href="torch.html#torch.acos">acos() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.acos">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.acos_">acos_() (torch.Tensor method)</a>
</li>
<li><a href="optim.html#torch.optim.Adadelta">Adadelta (class in torch.optim)</a>
</li>
<li><a href="optim.html#torch.optim.Adagrad">Adagrad (class in torch.optim)</a>
</li>
<li><a href="optim.html#torch.optim.Adam">Adam (class in torch.optim)</a>
</li>
<li><a href="optim.html#torch.optim.Adamax">Adamax (class in torch.optim)</a>
</li>
<li><a href="nn.html#torch.nn.functional.adaptive_avg_pool1d">adaptive_avg_pool1d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.functional.adaptive_avg_pool2d">adaptive_avg_pool2d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.functional.adaptive_max_pool1d">adaptive_max_pool1d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.functional.adaptive_max_pool2d">adaptive_max_pool2d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.AdaptiveAvgPool1d">AdaptiveAvgPool1d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.AdaptiveAvgPool2d">AdaptiveAvgPool2d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.AdaptiveMaxPool1d">AdaptiveMaxPool1d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.AdaptiveMaxPool2d">AdaptiveMaxPool2d (class in torch.nn)</a>
</li>
<li><a href="torch.html#torch.add">add() (in module torch)</a>, <a href="torch.html#torch.add">[1]</a>, <a href="torch.html#torch.add">[2]</a>
<ul>
<li><a href="tensors.html#torch.Tensor.add">(torch.Tensor method)</a>
</li>
<li><a href="sparse.html#torch.sparse.FloatTensor.add">(torch.sparse.FloatTensor method)</a>
</li>
</ul></li>
<li><a href="sparse.html#torch.sparse.FloatTensor.add_">add_() (torch.sparse.FloatTensor method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.add_">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="nn.html#torch.nn.Module.add_module">add_module() (torch.nn.Module method)</a>
</li>
<li><a href="torch.html#torch.addbmm">addbmm() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addbmm">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.addbmm_">addbmm_() (torch.Tensor method)</a>
</li>
<li><a href="torch.html#torch.addcdiv">addcdiv() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addcdiv">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.addcdiv_">addcdiv_() (torch.Tensor method)</a>
</li>
<li><a href="torch.html#torch.addcmul">addcmul() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addcmul">(torch.Tensor method)</a>
</li>
</ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="tensors.html#torch.Tensor.addcmul_">addcmul_() (torch.Tensor method)</a>
</li>
<li><a href="torch.html#torch.addmm">addmm() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addmm">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.addmm_">addmm_() (torch.Tensor method)</a>
</li>
<li><a href="torch.html#torch.addmv">addmv() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addmv">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.addmv_">addmv_() (torch.Tensor method)</a>
</li>
<li><a href="torch.html#torch.addr">addr() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.addr">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.addr_">addr_() (torch.Tensor method)</a>
</li>
<li><a href="torchvision/models.html#torchvision.models.alexnet">alexnet() (in module torchvision.models)</a>
</li>
<li><a href="nn.html#torch.nn.ModuleList.append">append() (torch.nn.ModuleList method)</a>
<ul>
<li><a href="nn.html#torch.nn.ParameterList.append">(torch.nn.ParameterList method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.apply_">apply_() (torch.Tensor method)</a>
</li>
<li><a href="torch.html#torch.arange">arange() (in module torch)</a>
</li>
<li><a href="optim.html#torch.optim.ASGD">ASGD (class in torch.optim)</a>
</li>
<li><a href="torch.html#torch.asin">asin() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.asin">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.asin_">asin_() (torch.Tensor method)</a>
</li>
<li><a href="torch.html#torch.atan">atan() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.atan">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="torch.html#torch.atan2">atan2() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.atan2">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.atan2_">atan2_() (torch.Tensor method)</a>
</li>
<li><a href="tensors.html#torch.Tensor.atan_">atan_() (torch.Tensor method)</a>
</li>
<li><a href="nn.html#torch.nn.functional.avg_pool1d">avg_pool1d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.functional.avg_pool2d">avg_pool2d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.functional.avg_pool3d">avg_pool3d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.AvgPool1d">AvgPool1d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.AvgPool2d">AvgPool2d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.AvgPool3d">AvgPool3d (class in torch.nn)</a>
</li>
</ul></td>
</tr></table>
<h2 id="B">B</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="autograd.html#torch.autograd.backward">backward() (in module torch.autograd)</a>
<ul>
<li><a href="autograd.html#torch.autograd.Function.backward">(torch.autograd.Function method)</a>
</li>
<li><a href="autograd.html#torch.autograd.Variable.backward">(torch.autograd.Variable method)</a>
</li>
</ul></li>
<li><a href="torch.html#torch.baddbmm">baddbmm() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.baddbmm">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.baddbmm_">baddbmm_() (torch.Tensor method)</a>
</li>
<li><a href="nn.html#torch.nn.functional.batch_norm">batch_norm() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.BatchNorm1d">BatchNorm1d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.BatchNorm2d">BatchNorm2d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.BatchNorm3d">BatchNorm3d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.BCELoss">BCELoss (class in torch.nn)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="torch.html#torch.bernoulli">bernoulli() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.bernoulli">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.bernoulli_">bernoulli_() (torch.Tensor method)</a>
</li>
<li><a href="nn.html#torch.nn.functional.binary_cross_entropy">binary_cross_entropy() (in module torch.nn.functional)</a>
</li>
<li><a href="torch.html#torch.bmm">bmm() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.bmm">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="cuda.html#torch.cuda.comm.broadcast">broadcast() (in module torch.cuda.comm)</a>
</li>
<li><a href="torch.html#torch.btrifact">btrifact() (in module torch)</a>
</li>
<li><a href="torch.html#torch.btrisolve">btrisolve() (in module torch)</a>
</li>
<li><a href="storage.html#torch.FloatStorage.byte">byte() (torch.FloatStorage method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.byte">(torch.Tensor method)</a>
</li>
</ul></li>
</ul></td>
</tr></table>
<h2 id="C">C</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="nn.html#torch.nn.init.calculate_gain">calculate_gain() (in module torch.nn.init)</a>
</li>
<li><a href="torch.html#torch.cat">cat() (in module torch)</a>
</li>
<li><a href="tensors.html#torch.Tensor.cauchy_">cauchy_() (torch.Tensor method)</a>
</li>
<li><a href="torch.html#torch.ceil">ceil() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.ceil">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.ceil_">ceil_() (torch.Tensor method)</a>
</li>
<li><a href="torchvision/transforms.html#torchvision.transforms.CenterCrop">CenterCrop (class in torchvision.transforms)</a>
</li>
<li><a href="storage.html#torch.FloatStorage.char">char() (torch.FloatStorage method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.char">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="nn.html#torch.nn.Module.children">children() (torch.nn.Module method)</a>
</li>
<li><a href="torch.html#torch.chunk">chunk() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.chunk">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="torch.html#torch.clamp">clamp() (in module torch)</a>, <a href="torch.html#torch.clamp">[1]</a>, <a href="torch.html#torch.clamp">[2]</a>
<ul>
<li><a href="tensors.html#torch.Tensor.clamp">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.clamp_">clamp_() (torch.Tensor method)</a>
</li>
<li><a href="nn.html#torch.nn.utils.clip_grad_norm">clip_grad_norm() (in module torch.nn.utils)</a>
</li>
<li><a href="storage.html#torch.FloatStorage.clone">clone() (torch.FloatStorage method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.clone">(torch.Tensor method)</a>
</li>
<li><a href="sparse.html#torch.sparse.FloatTensor.clone">(torch.sparse.FloatTensor method)</a>
</li>
</ul></li>
<li><a href="torchvision/transforms.html#torchvision.transforms.Compose">Compose (class in torchvision.transforms)</a>
</li>
<li><a href="nn.html#torch.nn.init.constant">constant() (in module torch.nn.init)</a>
</li>
<li><a href="tensors.html#torch.Tensor.contiguous">contiguous() (torch.Tensor method)</a>
</li>
<li><a href="nn.html#torch.nn.Conv1d">Conv1d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.functional.conv1d">conv1d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.Conv2d">Conv2d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.functional.conv2d">conv2d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.Conv3d">Conv3d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.functional.conv3d">conv3d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.functional.conv_transpose1d">conv_transpose1d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.functional.conv_transpose2d">conv_transpose2d() (in module torch.nn.functional)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="nn.html#torch.nn.functional.conv_transpose3d">conv_transpose3d() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.ConvTranspose1d">ConvTranspose1d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.ConvTranspose2d">ConvTranspose2d (class in torch.nn)</a>
</li>
<li><a href="nn.html#torch.nn.ConvTranspose3d">ConvTranspose3d (class in torch.nn)</a>
</li>
<li><a href="storage.html#torch.FloatStorage.copy_">copy_() (torch.FloatStorage method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.copy_">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="torch.html#torch.cos">cos() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.cos">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.cos_">cos_() (torch.Tensor method)</a>
</li>
<li><a href="torch.html#torch.cosh">cosh() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.cosh">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="tensors.html#torch.Tensor.cosh_">cosh_() (torch.Tensor method)</a>
</li>
<li><a href="nn.html#torch.nn.CosineEmbeddingLoss">CosineEmbeddingLoss (class in torch.nn)</a>
</li>
<li><a href="storage.html#torch.FloatStorage.cpu">cpu() (torch.FloatStorage method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.cpu">(torch.Tensor method)</a>
</li>
<li><a href="nn.html#torch.nn.Module.cpu">(torch.nn.Module method)</a>
</li>
</ul></li>
<li><a href="ffi.html#torch.utils.ffi.create_extension">create_extension() (in module torch.utils.ffi)</a>
</li>
<li><a href="torch.html#torch.cross">cross() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.cross">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="nn.html#torch.nn.functional.cross_entropy">cross_entropy() (in module torch.nn.functional)</a>
</li>
<li><a href="nn.html#torch.nn.CrossEntropyLoss">CrossEntropyLoss (class in torch.nn)</a>
</li>
<li><a href="storage.html#torch.FloatStorage.cuda">cuda() (torch.FloatStorage method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.cuda">(torch.Tensor method)</a>
</li>
<li><a href="nn.html#torch.nn.Module.cuda">(torch.nn.Module method)</a>
</li>
</ul></li>
<li><a href="torch.html#torch.cumprod">cumprod() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.cumprod">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="torch.html#torch.cumsum">cumsum() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.cumsum">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="cuda.html#torch.cuda.current_blas_handle">current_blas_handle() (in module torch.cuda)</a>
</li>
<li><a href="cuda.html#torch.cuda.current_device">current_device() (in module torch.cuda)</a>
</li>
<li><a href="cuda.html#torch.cuda.current_stream">current_stream() (in module torch.cuda)</a>
</li>
</ul></td>
</tr></table>
<h2 id="D">D</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="storage.html#torch.FloatStorage.data_ptr">data_ptr() (torch.FloatStorage method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.data_ptr">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="data.html#torch.utils.data.DataLoader">DataLoader (class in torch.utils.data)</a>
</li>
<li><a href="nn.html#torch.nn.DataParallel">DataParallel (class in torch.nn)</a>
</li>
<li><a href="data.html#torch.utils.data.Dataset">Dataset (class in torch.utils.data)</a>
</li>
<li><a href="torch.html#torch.default_generator">default_generator (in module torch)</a>
</li>
<li><a href="autograd.html#torch.autograd.Variable.detach">detach() (torch.autograd.Variable method)</a>
</li>
<li><a href="autograd.html#torch.autograd.Variable.detach_">detach_() (torch.autograd.Variable method)</a>
</li>
<li><a href="cuda.html#torch.cuda.device">device (class in torch.cuda)</a>
</li>
<li><a href="cuda.html#torch.cuda.device_count">device_count() (in module torch.cuda)</a>
</li>
<li><a href="cuda.html#torch.cuda.device_of">device_of (class in torch.cuda)</a>
</li>
<li><a href="torch.html#torch.diag">diag() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.diag">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="sparse.html#torch.sparse.FloatTensor.dim">dim() (torch.sparse.FloatTensor method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.dim">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="nn.html#torch.nn.init.dirac">dirac() (in module torch.nn.init)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="torch.html#torch.dist">dist() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.dist">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="torch.html#torch.div">div() (in module torch)</a>, <a href="torch.html#torch.div">[1]</a>, <a href="torch.html#torch.div">[2]</a>
<ul>
<li><a href="tensors.html#torch.Tensor.div">(torch.Tensor method)</a>
</li>
<li><a href="sparse.html#torch.sparse.FloatTensor.div">(torch.sparse.FloatTensor method)</a>
</li>
</ul></li>
<li><a href="sparse.html#torch.sparse.FloatTensor.div_">div_() (torch.sparse.FloatTensor method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.div_">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="torch.html#torch.dot">dot() (in module torch)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.dot">(torch.Tensor method)</a>
</li>
</ul></li>
<li><a href="storage.html#torch.FloatStorage.double">double() (torch.FloatStorage method)</a>
<ul>
<li><a href="tensors.html#torch.Tensor.double">(torch.Tensor method)</a>
</li>
<li><a href="nn.html#torch.nn.Module.double">(torch.nn.Module method)</a>
</li>