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This removes the StochasticFunctions for bernoulli, multinomial, and normal and replaces them with classes in the torch.distributions package. Each distribution supports the differentiable log_prob function that returns the log of the pdf/pmf of the samples. The current StochasticFunction implementation has a few problems: it can be painful to use when there are multiple stochastic outputs which need to be back-propagated through. It also requires that we store grad_fns on Variables that have requires_grad=False in order to find stochastic nodes.
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ReStructuredText
55 lines
983 B
ReStructuredText
.. PyTorch documentation master file, created by
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sphinx-quickstart on Fri Dec 23 13:31:47 2016.
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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:github_url: https://github.com/pytorch/pytorch
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PyTorch documentation
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===================================
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PyTorch is an optimized tensor library for deep learning using GPUs and CPUs.
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.. toctree::
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:glob:
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:maxdepth: 1
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:caption: Notes
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notes/*
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.. toctree::
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:maxdepth: 1
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:caption: Package Reference
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torch
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tensors
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sparse
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storage
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nn
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optim
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torch.autograd <autograd>
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torch.distributions <distributions>
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torch.multiprocessing <multiprocessing>
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torch.distributed <distributed>
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torch.legacy <legacy>
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cuda
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ffi
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data
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model_zoo
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onnx
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.. toctree::
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:glob:
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:maxdepth: 2
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:caption: torchvision Reference
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torchvision/index
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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