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https://github.com/zebrajr/pytorch.git
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6ba83e06a5
As the title stated. **Changes:** - torch.cuda.amp.autocast - torch.cpu.amp.autocast - add explicit `__new__` and `__init_subclass__` for those class above for inspect.signature to retrieve correct signature Pull Request resolved: https://github.com/pytorch/pytorch/pull/163654 Approved by: https://github.com/Skylion007
72 lines
2.1 KiB
Python
72 lines
2.1 KiB
Python
# mypy: allow-untyped-defs
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import sys
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from typing import Any
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from typing_extensions import deprecated
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import torch
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__all__ = ["autocast"]
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@deprecated(
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"`torch.cpu.amp.autocast(args...)` is deprecated. "
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"Please use `torch.amp.autocast('cpu', args...)` instead.",
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category=FutureWarning,
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)
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class autocast(torch.amp.autocast_mode.autocast):
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r"""
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See :class:`torch.autocast`.
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``torch.cpu.amp.autocast(args...)`` is deprecated. Please use ``torch.amp.autocast("cpu", args...)`` instead.
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"""
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# TODO: remove this conditional once we stop supporting Python < 3.13
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# Prior to Python 3.13, inspect.signature could not retrieve the correct
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# signature information for classes decorated with @deprecated (unless
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# the __new__ static method was explicitly defined);
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#
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# However, this issue has been fixed in Python 3.13 and later versions.
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if sys.version_info < (3, 13):
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def __new__(
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cls,
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enabled: bool = True,
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dtype: torch.dtype = torch.bfloat16,
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cache_enabled: bool = True,
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):
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return super().__new__(cls)
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def __init_subclass__(cls):
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pass
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def __init__(
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self,
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enabled: bool = True,
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dtype: torch.dtype = torch.bfloat16,
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cache_enabled: bool = True,
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):
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if torch._jit_internal.is_scripting():
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self._enabled = enabled
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self.device = "cpu"
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self.fast_dtype = dtype
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return
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super().__init__(
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"cpu", enabled=enabled, dtype=dtype, cache_enabled=cache_enabled
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)
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def __enter__(self):
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if torch._jit_internal.is_scripting():
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return self
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return super().__enter__()
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# TODO: discuss a unified TorchScript-friendly API for autocast
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def __exit__(self, exc_type: Any, exc_val: Any, exc_tb: Any): # type: ignore[override]
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if torch._jit_internal.is_scripting():
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return
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return super().__exit__(exc_type, exc_val, exc_tb)
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def __call__(self, func):
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if torch._jit_internal.is_scripting():
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return func
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return super().__call__(func)
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