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c25e33789e
Summary: Resubmit #20698 which got messed up. Idea is that when PyTorch is used in a custom build environment (e.g. Facebook), it's useful to track usage of various APIs centrally. This PR introduces a simple very lightweight mechanism to do so - only first invocation of a trigger point would be logged. This is significantly more lightweight than #18235 and thus we can allow to put logging in e.g. TensorImpl. Also adds an initial list of trigger points. Trigger points are added in such a way that no static initialization triggers them, i.e. just linking with libtorch.so will not cause any logging. Further suggestions of what to log are welcomed. Pull Request resolved: https://github.com/pytorch/pytorch/pull/20745 Differential Revision: D15429196 Pulled By: dzhulgakov fbshipit-source-id: a5e41a709a65b7ebccc6b95f93854e583cf20aca |
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| .. | ||
| backcompat | ||
| bottleneck | ||
| data | ||
| ffi | ||
| tensorboard | ||
| __init__.py | ||
| _cpp_extension_versioner.py | ||
| checkpoint.py | ||
| collect_env.py | ||
| cpp_extension.py | ||
| dlpack.py | ||
| file_baton.py | ||
| hooks.py | ||
| mkldnn.py | ||
| model_zoo.py | ||