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              <div class="version">
                <a href="https://pytorch.org/docs/versions.html"> 0.2.0_1 &#x25BC</a>
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              <p class="caption"><span class="caption-text">Notes</span></p>
<ul>
<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>
<li class="toctree-l3"><a class="reference internal" href="../notes/autograd.html#requires-grad"><code class="docutils literal"><span class="pre">requires_grad</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="../notes/autograd.html#volatile"><code class="docutils literal"><span class="pre">volatile</span></code></a></li>
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<li class="toctree-l2"><a class="reference internal" href="../notes/autograd.html#how-autograd-encodes-the-history">How autograd encodes the history</a></li>
<li class="toctree-l2"><a class="reference internal" href="../notes/autograd.html#in-place-operations-on-variables">In-place operations on Variables</a></li>
<li class="toctree-l2"><a class="reference internal" href="../notes/autograd.html#in-place-correctness-checks">In-place correctness checks</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../notes/broadcasting.html">Broadcasting semantics</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../notes/broadcasting.html#general-semantics">General semantics</a></li>
<li class="toctree-l2"><a class="reference internal" href="../notes/broadcasting.html#in-place-semantics">In-place semantics</a></li>
<li class="toctree-l2"><a class="reference internal" href="../notes/broadcasting.html#backwards-compatibility">Backwards compatibility</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../notes/cuda.html">CUDA semantics</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../notes/cuda.html#best-practices">Best practices</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../notes/cuda.html#use-pinned-memory-buffers">Use pinned memory buffers</a></li>
<li class="toctree-l3"><a class="reference internal" href="../notes/cuda.html#use-nn-dataparallel-instead-of-multiprocessing">Use nn.DataParallel instead of multiprocessing</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../notes/extending.html">Extending PyTorch</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../notes/extending.html#extending-torch-autograd">Extending <code class="docutils literal"><span class="pre">torch.autograd</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="../notes/extending.html#extending-torch-nn">Extending <code class="docutils literal"><span class="pre">torch.nn</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="../notes/extending.html#adding-a-module">Adding a <code class="docutils literal"><span class="pre">Module</span></code></a></li>
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<li class="toctree-l2"><a class="reference internal" href="../notes/extending.html#writing-custom-c-extensions">Writing custom C extensions</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../notes/multiprocessing.html">Multiprocessing best practices</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../notes/multiprocessing.html#sharing-cuda-tensors">Sharing CUDA tensors</a></li>
<li class="toctree-l2"><a class="reference internal" href="../notes/multiprocessing.html#best-practices-and-tips">Best practices and tips</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../notes/multiprocessing.html#avoiding-and-fighting-deadlocks">Avoiding and fighting deadlocks</a></li>
<li class="toctree-l3"><a class="reference internal" href="../notes/multiprocessing.html#reuse-buffers-passed-through-a-queue">Reuse buffers passed through a Queue</a></li>
<li class="toctree-l3"><a class="reference internal" href="../notes/multiprocessing.html#asynchronous-multiprocess-training-e-g-hogwild">Asynchronous multiprocess training (e.g. Hogwild)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="../notes/multiprocessing.html#hogwild">Hogwild</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../notes/serialization.html">Serialization semantics</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../notes/serialization.html#best-practices">Best practices</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../notes/serialization.html#recommended-approach-for-saving-a-model">Recommended approach for saving a model</a></li>
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<p class="caption"><span class="caption-text">Package Reference</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="../torch.html">torch</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../torch.html#tensors">Tensors</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../torch.html#creation-ops">Creation Ops</a></li>
<li class="toctree-l3"><a class="reference internal" href="../torch.html#indexing-slicing-joining-mutating-ops">Indexing, Slicing, Joining, Mutating Ops</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../torch.html#random-sampling">Random sampling</a></li>
<li class="toctree-l2"><a class="reference internal" href="../torch.html#serialization">Serialization</a></li>
<li class="toctree-l2"><a class="reference internal" href="../torch.html#parallelism">Parallelism</a></li>
<li class="toctree-l2"><a class="reference internal" href="../torch.html#math-operations">Math operations</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../torch.html#pointwise-ops">Pointwise Ops</a></li>
<li class="toctree-l3"><a class="reference internal" href="../torch.html#reduction-ops">Reduction Ops</a></li>
<li class="toctree-l3"><a class="reference internal" href="../torch.html#comparison-ops">Comparison Ops</a></li>
<li class="toctree-l3"><a class="reference internal" href="../torch.html#other-operations">Other Operations</a></li>
<li class="toctree-l3"><a class="reference internal" href="../torch.html#blas-and-lapack-operations">BLAS and LAPACK Operations</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../tensors.html">torch.Tensor</a></li>
<li class="toctree-l1"><a class="reference internal" href="../sparse.html">torch.sparse</a></li>
<li class="toctree-l1"><a class="reference internal" href="../storage.html">torch.Storage</a></li>
<li class="toctree-l1"><a class="reference internal" href="../nn.html">torch.nn</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../nn.html#parameters">Parameters</a></li>
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<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>
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<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#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#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>
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<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#reflectionpad2d"><span class="hidden-section">ReflectionPad2d</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#constantpad2d"><span class="hidden-section">ConstantPad2d</span></a></li>
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<li class="toctree-l2"><a class="reference internal" href="../nn.html#non-linear-activations">Non-linear Activations</a><ul>
<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#elu"><span class="hidden-section">ELU</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#prelu"><span class="hidden-section">PReLU</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#threshold"><span class="hidden-section">Threshold</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#sigmoid"><span class="hidden-section">Sigmoid</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#logsigmoid"><span class="hidden-section">LogSigmoid</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#tanhshrink"><span class="hidden-section">Tanhshrink</span></a></li>
<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#logsoftmax"><span class="hidden-section">LogSoftmax</span></a></li>
</ul>
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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>
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<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>
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<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>
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<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>
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<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>
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<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>
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<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#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#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>
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<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>
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<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#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#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>
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</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#id16"><span class="hidden-section">conv1d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id17"><span class="hidden-section">conv2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id18"><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>
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</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#id19"><span class="hidden-section">threshold</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id20"><span class="hidden-section">relu</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id21"><span class="hidden-section">hardtanh</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id22"><span class="hidden-section">relu6</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id23"><span class="hidden-section">elu</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id24"><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#id25"><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#id26"><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#id27"><span class="hidden-section">tanhshrink</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id28"><span class="hidden-section">softsign</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id29"><span class="hidden-section">softplus</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id30"><span class="hidden-section">softmin</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id31"><span class="hidden-section">softmax</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id32"><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#id33"><span class="hidden-section">tanh</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id34"><span class="hidden-section">sigmoid</span></a></li>
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<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#normalize"><span class="hidden-section">normalize</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#id35"><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#id36"><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#id37"><span class="hidden-section">dropout2d</span></a></li>
<li class="toctree-l3"><a class="reference internal" href="../nn.html#id38"><span class="hidden-section">dropout3d</span></a></li>
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<li class="toctree-l2"><a class="reference internal" href="../nn.html#id39">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#id40">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>
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<li class="toctree-l3"><a class="reference internal" href="../nn.html#id42"><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>
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<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-l2"><a class="reference internal" href="../autograd.html#variable">Variable</a><ul>
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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>
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<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>
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<li class="toctree-l2"><a class="reference internal" href="../torchvision/datasets.html#cifar">CIFAR</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../torchvision/datasets.html#svhn">SVHN</a></li>
<li class="toctree-l2"><a class="reference internal" href="../torchvision/datasets.html#phototour">PhotoTour</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../torchvision/transforms.html#transforms-on-torch-tensor">Transforms on torch.*Tensor</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../torchvision/transforms.html#generic-transforms">Generic Transforms</a></li>
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  <h1>Source code for torch</h1><div class="highlight"><pre>
<span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">The torch package contains data structures for multi-dimensional</span>
<span class="sd">tensors and mathematical operations over these are defined.</span>
<span class="sd">Additionally, it provides many utilities for efficient serializing of</span>
<span class="sd">Tensors and arbitrary types, and other useful utilities.</span>

<span class="sd">It has a CUDA counterpart, that enables you to run your tensor computations</span>
<span class="sd">on an NVIDIA GPU with compute capability &gt;= 3.0.</span>
<span class="sd">&quot;&quot;&quot;</span>

<span class="kn">import</span> <span class="nn">sys</span>
<span class="kn">from</span> <span class="nn">._utils</span> <span class="k">import</span> <span class="n">_import_dotted_name</span>
<span class="kn">from</span> <span class="nn">.version</span> <span class="k">import</span> <span class="n">__version__</span>

<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span>
    <span class="s1">&#39;typename&#39;</span><span class="p">,</span> <span class="s1">&#39;is_tensor&#39;</span><span class="p">,</span> <span class="s1">&#39;is_storage&#39;</span><span class="p">,</span> <span class="s1">&#39;set_default_tensor_type&#39;</span><span class="p">,</span>
    <span class="s1">&#39;set_rng_state&#39;</span><span class="p">,</span> <span class="s1">&#39;get_rng_state&#39;</span><span class="p">,</span> <span class="s1">&#39;manual_seed&#39;</span><span class="p">,</span> <span class="s1">&#39;initial_seed&#39;</span><span class="p">,</span>
    <span class="s1">&#39;save&#39;</span><span class="p">,</span> <span class="s1">&#39;load&#39;</span><span class="p">,</span> <span class="s1">&#39;set_printoptions&#39;</span><span class="p">,</span> <span class="s1">&#39;chunk&#39;</span><span class="p">,</span> <span class="s1">&#39;split&#39;</span><span class="p">,</span> <span class="s1">&#39;stack&#39;</span><span class="p">,</span> <span class="s1">&#39;matmul&#39;</span><span class="p">,</span>
    <span class="s1">&#39;DoubleStorage&#39;</span><span class="p">,</span> <span class="s1">&#39;FloatStorage&#39;</span><span class="p">,</span> <span class="s1">&#39;LongStorage&#39;</span><span class="p">,</span> <span class="s1">&#39;IntStorage&#39;</span><span class="p">,</span>
    <span class="s1">&#39;ShortStorage&#39;</span><span class="p">,</span> <span class="s1">&#39;CharStorage&#39;</span><span class="p">,</span> <span class="s1">&#39;ByteStorage&#39;</span><span class="p">,</span>
    <span class="s1">&#39;DoubleTensor&#39;</span><span class="p">,</span> <span class="s1">&#39;FloatTensor&#39;</span><span class="p">,</span> <span class="s1">&#39;LongTensor&#39;</span><span class="p">,</span> <span class="s1">&#39;IntTensor&#39;</span><span class="p">,</span>
    <span class="s1">&#39;ShortTensor&#39;</span><span class="p">,</span> <span class="s1">&#39;CharTensor&#39;</span><span class="p">,</span> <span class="s1">&#39;ByteTensor&#39;</span><span class="p">,</span>
<span class="p">]</span>

<span class="c1">################################################################################</span>
<span class="c1"># Load the extension module</span>
<span class="c1">################################################################################</span>

<span class="c1"># Loading the extension with RTLD_GLOBAL option allows to not link extension</span>
<span class="c1"># modules against the _C shared object. Their missing THP symbols will be</span>
<span class="c1"># automatically filled by the dynamic loader.</span>
<span class="kn">import</span> <span class="nn">os</span> <span class="k">as</span> <span class="nn">_dl_flags</span>

<span class="c1"># if we have numpy, it *must* be imported before the call to setdlopenflags()</span>
<span class="c1"># or there is risk that later c modules will segfault when importing numpy</span>
<span class="k">try</span><span class="p">:</span>
    <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="k">except</span><span class="p">:</span>
    <span class="k">pass</span>

<span class="c1"># first check if the os package has the required flags</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">_dl_flags</span><span class="p">,</span> <span class="s1">&#39;RTLD_GLOBAL&#39;</span><span class="p">)</span> <span class="ow">or</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">_dl_flags</span><span class="p">,</span> <span class="s1">&#39;RTLD_NOW&#39;</span><span class="p">):</span>
    <span class="k">try</span><span class="p">:</span>
        <span class="c1"># next try if DLFCN exists</span>
        <span class="kn">import</span> <span class="nn">DLFCN</span> <span class="k">as</span> <span class="nn">_dl_flags</span>
    <span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
        <span class="c1"># as a last attempt, use compile-time constants</span>
        <span class="kn">import</span> <span class="nn">torch._dl</span> <span class="k">as</span> <span class="nn">_dl_flags</span>

<span class="n">old_flags</span> <span class="o">=</span> <span class="n">sys</span><span class="o">.</span><span class="n">getdlopenflags</span><span class="p">()</span>
<span class="n">sys</span><span class="o">.</span><span class="n">setdlopenflags</span><span class="p">(</span><span class="n">_dl_flags</span><span class="o">.</span><span class="n">RTLD_GLOBAL</span> <span class="o">|</span> <span class="n">_dl_flags</span><span class="o">.</span><span class="n">RTLD_NOW</span><span class="p">)</span>

<span class="kn">from</span> <span class="nn">torch._C</span> <span class="k">import</span> <span class="o">*</span>

<span class="n">__all__</span> <span class="o">+=</span> <span class="p">[</span><span class="n">name</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">dir</span><span class="p">(</span><span class="n">_C</span><span class="p">)</span>
            <span class="k">if</span> <span class="n">name</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">!=</span> <span class="s1">&#39;_&#39;</span> <span class="ow">and</span>
            <span class="ow">not</span> <span class="n">name</span><span class="o">.</span><span class="n">endswith</span><span class="p">(</span><span class="s1">&#39;Base&#39;</span><span class="p">)]</span>

<span class="n">sys</span><span class="o">.</span><span class="n">setdlopenflags</span><span class="p">(</span><span class="n">old_flags</span><span class="p">)</span>
<span class="k">del</span> <span class="n">_dl_flags</span>
<span class="k">del</span> <span class="n">old_flags</span>

<span class="c1">################################################################################</span>
<span class="c1"># Define basic utilities</span>
<span class="c1">################################################################################</span>


<span class="k">def</span> <span class="nf">typename</span><span class="p">(</span><span class="n">o</span><span class="p">):</span>
    <span class="n">module</span> <span class="o">=</span> <span class="s1">&#39;&#39;</span>
    <span class="n">class_name</span> <span class="o">=</span> <span class="s1">&#39;&#39;</span>
    <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">o</span><span class="p">,</span> <span class="s1">&#39;__module__&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="n">o</span><span class="o">.</span><span class="vm">__module__</span> <span class="o">!=</span> <span class="s1">&#39;builtins&#39;</span> \
            <span class="ow">and</span> <span class="n">o</span><span class="o">.</span><span class="vm">__module__</span> <span class="o">!=</span> <span class="s1">&#39;__builtin__&#39;</span> <span class="ow">and</span> <span class="n">o</span><span class="o">.</span><span class="vm">__module__</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">module</span> <span class="o">=</span> <span class="n">o</span><span class="o">.</span><span class="vm">__module__</span> <span class="o">+</span> <span class="s1">&#39;.&#39;</span>

    <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">o</span><span class="p">,</span> <span class="s1">&#39;__qualname__&#39;</span><span class="p">):</span>
        <span class="n">class_name</span> <span class="o">=</span> <span class="n">o</span><span class="o">.</span><span class="vm">__qualname__</span>
    <span class="k">elif</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">o</span><span class="p">,</span> <span class="s1">&#39;__name__&#39;</span><span class="p">):</span>
        <span class="n">class_name</span> <span class="o">=</span> <span class="n">o</span><span class="o">.</span><span class="vm">__name__</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">class_name</span> <span class="o">=</span> <span class="n">o</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>

    <span class="k">return</span> <span class="n">module</span> <span class="o">+</span> <span class="n">class_name</span>


<div class="viewcode-block" id="is_tensor"><a class="viewcode-back" href="../torch.html#torch.is_tensor">[docs]</a><span class="k">def</span> <span class="nf">is_tensor</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns True if `obj` is a pytorch tensor.</span>

<span class="sd">    Args:</span>
<span class="sd">        obj (Object): Object to test</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">return</span> <span class="nb">type</span><span class="p">(</span><span class="n">obj</span><span class="p">)</span> <span class="ow">in</span> <span class="n">_tensor_classes</span></div>


<div class="viewcode-block" id="is_storage"><a class="viewcode-back" href="../torch.html#torch.is_storage">[docs]</a><span class="k">def</span> <span class="nf">is_storage</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns True if `obj` is a pytorch storage object.</span>

<span class="sd">    Args:</span>
<span class="sd">        obj (Object): Object to test</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">return</span> <span class="nb">type</span><span class="p">(</span><span class="n">obj</span><span class="p">)</span> <span class="ow">in</span> <span class="n">_storage_classes</span></div>


<div class="viewcode-block" id="set_default_tensor_type"><a class="viewcode-back" href="../torch.html#torch.set_default_tensor_type">[docs]</a><span class="k">def</span> <span class="nf">set_default_tensor_type</span><span class="p">(</span><span class="n">t</span><span class="p">):</span>
    <span class="k">global</span> <span class="n">Tensor</span>
    <span class="k">global</span> <span class="n">Storage</span>
    <span class="n">Tensor</span> <span class="o">=</span> <span class="n">_import_dotted_name</span><span class="p">(</span><span class="n">t</span><span class="p">)</span>
    <span class="n">Storage</span> <span class="o">=</span> <span class="n">_import_dotted_name</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;Tensor&#39;</span><span class="p">,</span> <span class="s1">&#39;Storage&#39;</span><span class="p">))</span>
    <span class="n">_C</span><span class="o">.</span><span class="n">_set_default_tensor_type</span><span class="p">(</span><span class="n">Tensor</span><span class="p">)</span></div>


<div class="viewcode-block" id="set_rng_state"><a class="viewcode-back" href="../torch.html#torch.set_rng_state">[docs]</a><span class="k">def</span> <span class="nf">set_rng_state</span><span class="p">(</span><span class="n">new_state</span><span class="p">):</span>
    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Sets the random number generator state.</span>

<span class="sd">    Args:</span>
<span class="sd">        new_state (torch.ByteTensor): The desired state</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">default_generator</span><span class="o">.</span><span class="n">set_state</span><span class="p">(</span><span class="n">new_state</span><span class="p">)</span></div>


<div class="viewcode-block" id="get_rng_state"><a class="viewcode-back" href="../torch.html#torch.get_rng_state">[docs]</a><span class="k">def</span> <span class="nf">get_rng_state</span><span class="p">():</span>
    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns the random number generator state as a ByteTensor.&quot;&quot;&quot;</span>
    <span class="k">return</span> <span class="n">default_generator</span><span class="o">.</span><span class="n">get_state</span><span class="p">()</span></div>


<div class="viewcode-block" id="manual_seed"><a class="viewcode-back" href="../torch.html#torch.manual_seed">[docs]</a><span class="k">def</span> <span class="nf">manual_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">):</span>
    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Sets the seed for generating random numbers. And returns a</span>
<span class="sd">    `torch._C.Generator` object.</span>

<span class="sd">    Args:</span>
<span class="sd">        seed (int or long): The desired seed.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">is_available</span><span class="p">()</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">_in_bad_fork</span><span class="p">:</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">manual_seed_all</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>

    <span class="k">return</span> <span class="n">default_generator</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span></div>


<div class="viewcode-block" id="initial_seed"><a class="viewcode-back" href="../torch.html#torch.initial_seed">[docs]</a><span class="k">def</span> <span class="nf">initial_seed</span><span class="p">():</span>
    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns the initial seed for generating random numbers as a</span>
<span class="sd">    python `long`.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">return</span> <span class="n">default_generator</span><span class="o">.</span><span class="n">initial_seed</span><span class="p">()</span></div>


<span class="kn">from</span> <span class="nn">.serialization</span> <span class="k">import</span> <span class="n">save</span><span class="p">,</span> <span class="n">load</span>
<span class="kn">from</span> <span class="nn">._tensor_str</span> <span class="k">import</span> <span class="n">set_printoptions</span>

<span class="c1">################################################################################</span>
<span class="c1"># Define Storage and Tensor classes</span>
<span class="c1">################################################################################</span>

<span class="kn">from</span> <span class="nn">.storage</span> <span class="k">import</span> <span class="n">_StorageBase</span>
<span class="kn">from</span> <span class="nn">.tensor</span> <span class="k">import</span> <span class="n">_TensorBase</span>


<span class="k">class</span> <span class="nc">DoubleStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">DoubleStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
    <span class="k">pass</span>


<div class="viewcode-block" id="FloatStorage"><a class="viewcode-back" href="../storage.html#torch.FloatStorage">[docs]</a><span class="k">class</span> <span class="nc">FloatStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">FloatStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
    <span class="k">pass</span></div>


<span class="k">class</span> <span class="nc">HalfStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">HalfStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
    <span class="k">pass</span>


<span class="k">class</span> <span class="nc">LongStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">LongStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
    <span class="k">pass</span>


<span class="k">class</span> <span class="nc">IntStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">IntStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
    <span class="k">pass</span>


<span class="k">class</span> <span class="nc">ShortStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">ShortStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
    <span class="k">pass</span>


<span class="k">class</span> <span class="nc">CharStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">CharStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
    <span class="k">pass</span>


<span class="k">class</span> <span class="nc">ByteStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">ByteStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
    <span class="k">pass</span>


<span class="k">class</span> <span class="nc">DoubleTensor</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">DoubleTensorBase</span><span class="p">,</span> <span class="n">_TensorBase</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">is_signed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="kc">True</span>

    <span class="nd">@classmethod</span>
    <span class="k">def</span> <span class="nf">storage_type</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">DoubleStorage</span>


<span class="k">class</span> <span class="nc">FloatTensor</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">FloatTensorBase</span><span class="p">,</span> <span class="n">_TensorBase</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">is_signed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="kc">True</span>

    <span class="nd">@classmethod</span>
    <span class="k">def</span> <span class="nf">storage_type</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">FloatStorage</span>


<span class="k">class</span> <span class="nc">HalfTensor</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">HalfTensorBase</span><span class="p">,</span> <span class="n">_TensorBase</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">is_signed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="kc">True</span>

    <span class="nd">@classmethod</span>
    <span class="k">def</span> <span class="nf">storage_type</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">HalfStorage</span>


<span class="k">class</span> <span class="nc">LongTensor</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">LongTensorBase</span><span class="p">,</span> <span class="n">_TensorBase</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">is_signed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="kc">True</span>

    <span class="nd">@classmethod</span>
    <span class="k">def</span> <span class="nf">storage_type</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">LongStorage</span>


<span class="k">class</span> <span class="nc">IntTensor</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">IntTensorBase</span><span class="p">,</span> <span class="n">_TensorBase</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">is_signed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="kc">True</span>

    <span class="nd">@classmethod</span>
    <span class="k">def</span> <span class="nf">storage_type</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">IntStorage</span>


<span class="k">class</span> <span class="nc">ShortTensor</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">ShortTensorBase</span><span class="p">,</span> <span class="n">_TensorBase</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">is_signed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="kc">True</span>

    <span class="nd">@classmethod</span>
    <span class="k">def</span> <span class="nf">storage_type</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">ShortStorage</span>


<span class="k">class</span> <span class="nc">CharTensor</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">CharTensorBase</span><span class="p">,</span> <span class="n">_TensorBase</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">is_signed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="c1"># TODO</span>
        <span class="k">return</span> <span class="kc">False</span>

    <span class="nd">@classmethod</span>
    <span class="k">def</span> <span class="nf">storage_type</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">CharStorage</span>


<span class="k">class</span> <span class="nc">ByteTensor</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">ByteTensorBase</span><span class="p">,</span> <span class="n">_TensorBase</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">is_signed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="kc">False</span>

    <span class="nd">@classmethod</span>
    <span class="k">def</span> <span class="nf">storage_type</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">ByteStorage</span>


<span class="n">_storage_classes</span> <span class="o">=</span> <span class="p">{</span>
    <span class="n">DoubleStorage</span><span class="p">,</span> <span class="n">FloatStorage</span><span class="p">,</span> <span class="n">LongStorage</span><span class="p">,</span> <span class="n">IntStorage</span><span class="p">,</span> <span class="n">ShortStorage</span><span class="p">,</span>
    <span class="n">CharStorage</span><span class="p">,</span> <span class="n">ByteStorage</span><span class="p">,</span> <span class="n">HalfStorage</span>
<span class="p">}</span>

<span class="n">_tensor_classes</span> <span class="o">=</span> <span class="p">{</span>
    <span class="n">DoubleTensor</span><span class="p">,</span> <span class="n">FloatTensor</span><span class="p">,</span> <span class="n">LongTensor</span><span class="p">,</span> <span class="n">IntTensor</span><span class="p">,</span> <span class="n">ShortTensor</span><span class="p">,</span>
    <span class="n">CharTensor</span><span class="p">,</span> <span class="n">ByteTensor</span><span class="p">,</span> <span class="n">HalfTensor</span>
<span class="p">}</span>


<span class="n">set_default_tensor_type</span><span class="p">(</span><span class="s1">&#39;torch.FloatTensor&#39;</span><span class="p">)</span>

<span class="c1">################################################################################</span>
<span class="c1"># Import interface functions defined in Python</span>
<span class="c1">################################################################################</span>

<span class="kn">from</span> <span class="nn">.functional</span> <span class="k">import</span> <span class="o">*</span>


<span class="c1">################################################################################</span>
<span class="c1"># Initialize extension</span>
<span class="c1">################################################################################</span>

<span class="k">def</span> <span class="nf">manager_path</span><span class="p">():</span>
    <span class="kn">import</span> <span class="nn">os</span>
    <span class="n">path</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">abspath</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">dirname</span><span class="p">(</span><span class="vm">__file__</span><span class="p">)),</span> <span class="s1">&#39;lib&#39;</span><span class="p">,</span> <span class="s1">&#39;torch_shm_manager&#39;</span><span class="p">)</span>
    <span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">exists</span><span class="p">(</span><span class="n">path</span><span class="p">):</span>
        <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Unable to find torch_shm_manager at &quot;</span> <span class="o">+</span> <span class="n">path</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">path</span><span class="o">.</span><span class="n">encode</span><span class="p">(</span><span class="s1">&#39;utf-8&#39;</span><span class="p">)</span>


<span class="c1"># Shared memory manager needs to know the exact location of manager executable</span>
<span class="n">_C</span><span class="o">.</span><span class="n">_initExtension</span><span class="p">(</span><span class="n">manager_path</span><span class="p">())</span>
<span class="k">del</span> <span class="n">manager_path</span>

<span class="c1">################################################################################</span>
<span class="c1"># Remove unnecessary members</span>
<span class="c1">################################################################################</span>

<span class="k">del</span> <span class="n">DoubleStorageBase</span>
<span class="k">del</span> <span class="n">FloatStorageBase</span>
<span class="k">del</span> <span class="n">LongStorageBase</span>
<span class="k">del</span> <span class="n">IntStorageBase</span>
<span class="k">del</span> <span class="n">ShortStorageBase</span>
<span class="k">del</span> <span class="n">CharStorageBase</span>
<span class="k">del</span> <span class="n">ByteStorageBase</span>
<span class="k">del</span> <span class="n">DoubleTensorBase</span>
<span class="k">del</span> <span class="n">FloatTensorBase</span>
<span class="k">del</span> <span class="n">LongTensorBase</span>
<span class="k">del</span> <span class="n">IntTensorBase</span>
<span class="k">del</span> <span class="n">ShortTensorBase</span>
<span class="k">del</span> <span class="n">CharTensorBase</span>
<span class="k">del</span> <span class="n">ByteTensorBase</span>

<span class="k">del</span> <span class="n">SparseDoubleTensorBase</span>
<span class="k">del</span> <span class="n">SparseFloatTensorBase</span>
<span class="k">del</span> <span class="n">SparseLongTensorBase</span>
<span class="k">del</span> <span class="n">SparseIntTensorBase</span>
<span class="k">del</span> <span class="n">SparseShortTensorBase</span>
<span class="k">del</span> <span class="n">SparseCharTensorBase</span>
<span class="k">del</span> <span class="n">SparseByteTensorBase</span>

<span class="c1">################################################################################</span>
<span class="c1"># Import most common subpackages</span>
<span class="c1">################################################################################</span>

<span class="kn">import</span> <span class="nn">torch.cuda</span>
<span class="kn">import</span> <span class="nn">torch.autograd</span>
<span class="kn">import</span> <span class="nn">torch.nn</span>
<span class="kn">import</span> <span class="nn">torch.optim</span>
<span class="kn">import</span> <span class="nn">torch.multiprocessing</span>
<span class="kn">import</span> <span class="nn">torch.sparse</span>
<span class="kn">import</span> <span class="nn">torch.utils.backcompat</span>
<span class="n">_C</span><span class="o">.</span><span class="n">_init_names</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">_tensor_classes</span><span class="p">)</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">_storage_classes</span><span class="p">))</span>

<span class="c1"># attach docstrings to torch and tensor functions</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="k">import</span> <span class="n">_torch_docs</span><span class="p">,</span> <span class="n">_tensor_docs</span><span class="p">,</span> <span class="n">_storage_docs</span>
<span class="k">del</span> <span class="n">_torch_docs</span><span class="p">,</span> <span class="n">_tensor_docs</span><span class="p">,</span> <span class="n">_storage_docs</span>
</pre></div>

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