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Previously we relied on gc to get the snapshot of fake tensors before and after export to get list of fake tensors that are created during export. This caused some flakiness in our test suite (https://github.com/pytorch/pytorch/issues/162232). it seems super hard to make gc deterministic, so we just instrument fake tensor creation which seems lot better. In addition, it is also quite faster than previous approach becuase we are no longer manually triggering garbage collector. Differential Revision: [D82966648](https://our.internmc.facebook.com/intern/diff/D82966648) Pull Request resolved: https://github.com/pytorch/pytorch/pull/163516 Approved by: https://github.com/ezyang
32 lines
883 B
Python
32 lines
883 B
Python
"""
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Configuration module for torch.export.export.
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This module contains various configuration flags and settings that control torch.export's
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behavior, including:
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- Runtime behavior flags
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- Debugging and development options
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"""
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import sys
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from typing import Any, TYPE_CHECKING
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from torch.utils._config_module import install_config_module
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# this flag controls whether we use new functional tracer. It
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# should be True in the long term.
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use_new_tracer_experimental = False
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# this flag is used to control whether we want to instrument
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# fake tensor creation to track potential leaks. It is off
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# by default, but user can turn it on to debug leaks.
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detect_non_strict_fake_tensor_leaks = False
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if TYPE_CHECKING:
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from torch.utils._config_typing import * # noqa: F401, F403
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def _make_closure_patcher(**changes: Any) -> Any: ...
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install_config_module(sys.modules[__name__])
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