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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/45232 **Summary** This commit updates the TorchScript language reference to include documentation on recently-added TorchScript enums. It also removed `torch.no_grad` from the list of known unsupported `torch` modules and classes because it is now supported. **Test Plan** Continuous integration. Test Plan: Imported from OSS Reviewed By: ZolotukhinM Differential Revision: D23971884 Pulled By: SplitInfinity fbshipit-source-id: 5e2c164ed59bc0926b11201106952cff86e9356e
92 lines
2.8 KiB
ReStructuredText
92 lines
2.8 KiB
ReStructuredText
.. _jit_unsupported:
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TorchScript Unsupported Pytorch Constructs
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============================================
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Torch and Tensor Unsupported Attributes
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------------------------------------------
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TorchScript supports most methods defined on ``torch`` and ``torch.Tensor``, but we do not have full coverage.
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Here are specific known ops and categories of ops which have diverging behavior between
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Python and TorchScript. If you encounter something else that is not supported please
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file a GitHub issue. Deprecated ops are not listed below.
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.. automodule:: torch.jit.unsupported_tensor_ops
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Functions Not Correctly Bound on Torch
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The following functions will fail if used in TorchScript, either because they
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are not bound on `torch` or because Python expects a different schema than
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TorchScript.
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* :func:`torch.tensordot`
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* :func:`torch.nn.init.calculate_gain`
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* :func:`torch.nn.init.eye_`
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* :func:`torch.nn.init.dirac_`
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* :func:`torch.nn.init.kaiming_normal_`
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* :func:`torch.nn.init.orthogonal_`
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* :func:`torch.nn.init.sparse`
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Ops With Divergent Schemas Between Torch & Python
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The following categories of ops have divergent schemas:
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Functions which construct tensors from non-tensor inputs do not support the `requires_grad`
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argument, except for `torch.tensor`. This covers the following ops:
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* :func:`torch.norm`
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* :func:`torch.bartlett_window`
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* :func:`torch.blackman_window`
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* :func:`torch.empty`
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* :func:`torch.empty_like`
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* :func:`torch.empty_strided`
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* :func:`torch.eye`
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* :func:`torch.full`
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* :func:`torch.full_like`
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* :func:`torch.hamming_window`
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* :func:`torch.hann_window`
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* :func:`torch.linspace`
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* :func:`torch.logspace`
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* :func:`torch.normal`
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* :func:`torch.ones`
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* :func:`torch.rand`
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* :func:`torch.rand_like`
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* :func:`torch.randint_like`
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* :func:`torch.randn`
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* :func:`torch.randn_like`
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* :func:`torch.randperm`
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* :func:`torch.tril_indices`
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* :func:`torch.triu_indices`
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* :func:`torch.vander`
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* :func:`torch.zeros`
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* :func:`torch.zeros_like`
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The following functions require `dtype`, `layout`, `device` as parameters in TorchScript,
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but these parameters are optional in Python.
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* :func:`torch.randint`
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* :func:`torch.sparse_coo_tensor`
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* :meth:`~torch.Tensor.to`
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PyTorch Unsupported Modules and Classes
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------------------------------------------
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TorchScript cannot currently compile a number of other commonly used PyTorch
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constructs. Below are listed the modules that TorchScript does not support, and
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an incomplete list of PyTorch classes that are not supported. For unsupported modules
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we suggest using :meth:`torch.jit.trace`.
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* :class:`torch.nn.RNN`
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* :class:`torch.nn.AdaptiveLogSoftmaxWithLoss`
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* :class:`torch.autograd.Function`
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* :class:`torch.autograd.enable_grad`
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* :class:`torch.Generator`
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