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cf70466970
Cover more cases of scope inferencing where consecutive nodes don't have valid scope information. Usually these nodes are created in some pass where authors forgot to assign meaningful scope to them. * One rule of `InferScope` is to check if the current node's outputs' users share the same scope. Recursively run `InferScope` on the user nodes if they are missing scope as well. Since the graph is SSA, the depth is finite. * Fix one pass that missed scope information for a new node. Pull Request resolved: https://github.com/pytorch/pytorch/pull/71897 |
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| .. | ||
| _C | ||
| _masked | ||
| ao | ||
| autograd | ||
| backends | ||
| contrib | ||
| cpu | ||
| csrc | ||
| cuda | ||
| distributed | ||
| distributions | ||
| fft | ||
| for_onnx | ||
| futures | ||
| fx | ||
| jit | ||
| legacy | ||
| lib | ||
| linalg | ||
| monitor | ||
| multiprocessing | ||
| nn | ||
| onnx | ||
| optim | ||
| package | ||
| profiler | ||
| quantization | ||
| sparse | ||
| special | ||
| testing | ||
| utils | ||
| __config__.py | ||
| __future__.py | ||
| __init__.py | ||
| _appdirs.py | ||
| _classes.py | ||
| _deploy.py | ||
| _jit_internal.py | ||
| _linalg_utils.py | ||
| _lobpcg.py | ||
| _lowrank.py | ||
| _namedtensor_internals.py | ||
| _ops.py | ||
| _python_dispatcher.py | ||
| _six.py | ||
| _sources.py | ||
| _storage_docs.py | ||
| _tensor_docs.py | ||
| _tensor_str.py | ||
| _tensor.py | ||
| _torch_docs.py | ||
| _utils_internal.py | ||
| _utils.py | ||
| _VF.py | ||
| _vmap_internals.py | ||
| abi-check.cpp | ||
| autocast_mode.py | ||
| CMakeLists.txt | ||
| custom_class_detail.h | ||
| custom_class.h | ||
| deploy.h | ||
| extension.h | ||
| functional.py | ||
| hub.py | ||
| library.h | ||
| overrides.py | ||
| py.typed | ||
| quasirandom.py | ||
| random.py | ||
| README.txt | ||
| return_types.py | ||
| script.h | ||
| serialization.py | ||
| storage.py | ||
| torch_version.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.