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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/45461 This PR disables autograd for all C -> C, R -> C functions which are not included in the whitelist `GRADIENT_IMPLEMENTED_FOR_COMPLEX`. In practice, there will be a RuntimeError during forward computation when the outputs are differentiable: ``` >>> x=torch.randn(4, 4, requires_grad=True, dtype=torch.cdouble) >>> x.pow(3) Traceback (most recent call last): File "<stdin>", line 1, in <module> RuntimeError: pow does not support automatic differentiation for outputs with complex dtype. ``` The implicit assumption here is that all the C -> R functions have correct backward definitions. So before merging this PR, the following functions must be tested and verified to have correct backward definitions: `torch.abs` (updated in #39955 ), `torch.angle`, `torch.norm`, `torch.irfft`, `torch.istft`. Test Plan: Imported from OSS Reviewed By: malfet Differential Revision: D23998156 Pulled By: anjali411 fbshipit-source-id: 370eb07fe56ac84dd8e2233ef7bf3a3eb8aeb179 |
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| .. | ||
| _C | ||
| autograd | ||
| backends | ||
| contrib | ||
| csrc | ||
| cuda | ||
| distributed | ||
| distributions | ||
| fft | ||
| for_onnx | ||
| futures | ||
| fx | ||
| jit | ||
| legacy | ||
| lib | ||
| linalg | ||
| multiprocessing | ||
| nn | ||
| onnx | ||
| optim | ||
| package | ||
| quantization | ||
| sparse | ||
| testing | ||
| utils | ||
| __config__.py | ||
| __future__.py | ||
| __init__.py | ||
| _appdirs.py | ||
| _classes.py | ||
| _jit_internal.py | ||
| _linalg_utils.py | ||
| _lobpcg.py | ||
| _lowrank.py | ||
| _namedtensor_internals.py | ||
| _ops.py | ||
| _six.py | ||
| _storage_docs.py | ||
| _tensor_docs.py | ||
| _tensor_str.py | ||
| _torch_docs.py | ||
| _utils_internal.py | ||
| _utils.py | ||
| _VF.py | ||
| _vmap_internals.py | ||
| abi-check.cpp | ||
| CMakeLists.txt | ||
| custom_class_detail.h | ||
| custom_class.h | ||
| extension.h | ||
| functional.py | ||
| hub.py | ||
| library.h | ||
| overrides.py | ||
| py.typed | ||
| quasirandom.py | ||
| random.py | ||
| README.txt | ||
| script.h | ||
| serialization.py | ||
| storage.py | ||
| tensor.py | ||
| types.py | ||
Note [TH abstraction violation] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ TH/THC provide some hpp headers, which are proper C++ headers rather than C headers. These headers serve double duty as *internal implementation detail* headers, whose contents should largely not be used by external clients. Ideally, we would not install these headers at all; instead, you should use public functions (in headers like `THTensor.h`, NOT `THTensor.hpp`) to manipulate these structs. However, there are a few places in torch/csrc where we violate this abstraction. They are marked with a pointer to this note. Each of those sites will have to be refactored when we refactor the guts of THTensor and related structures.