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https://github.com/zebrajr/pytorch.git
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802dd2b725
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/68728 This removes the ability for `assert_close` to `.coalesce()` the tensors internally. Additionally, we now also check `.sparse_dim()`. Sparse team: please make sure that is the behavior you want for all sparse COO comparisons in the future. #67796 will temporarily keep BC by always coalescing, but in the future `TestCase.assertEqual` will no longer do that. cc nikitaved pearu cpuhrsch IvanYashchuk Test Plan: Imported from OSS Reviewed By: ngimel Differential Revision: D33542996 Pulled By: mruberry fbshipit-source-id: a8d2322c6ee1ca424e3efb14ab21787328cf28fc
104 lines
3.4 KiB
Python
104 lines
3.4 KiB
Python
"""This module exists since the `torch.testing` exposed a lot of stuff that shouldn't have been public. Although this
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was never documented anywhere, some other internal FB projects as well as downstream OSS projects might use this. Thus,
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we don't internalize without warning, but still go through a deprecation cycle.
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"""
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import functools
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import warnings
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from typing import Any, Callable, Dict, Optional, Tuple, Union
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import torch
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from . import _legacy
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__all__ = [
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"rand",
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"randn",
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"assert_allclose",
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"get_all_device_types",
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]
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def warn_deprecated(instructions: Union[str, Callable[[str, Tuple[Any, ...], Dict[str, Any], Any], str]]) -> Callable:
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def outer_wrapper(fn: Callable) -> Callable:
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name = fn.__name__
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head = f"torch.testing.{name}() is deprecated and will be removed in a future release. "
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@functools.wraps(fn)
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def inner_wrapper(*args: Any, **kwargs: Any) -> Any:
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return_value = fn(*args, **kwargs)
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tail = instructions(name, args, kwargs, return_value) if callable(instructions) else instructions
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msg = (head + tail).strip()
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warnings.warn(msg, FutureWarning)
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return return_value
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return inner_wrapper
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return outer_wrapper
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rand = warn_deprecated("Use torch.rand instead.")(torch.rand)
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randn = warn_deprecated("Use torch.randn instead.")(torch.randn)
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_DTYPE_PRECISIONS = {
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torch.float16: (1e-3, 1e-3),
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torch.float32: (1e-4, 1e-5),
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torch.float64: (1e-5, 1e-8),
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}
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def _get_default_rtol_and_atol(actual: torch.Tensor, expected: torch.Tensor) -> Tuple[float, float]:
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actual_rtol, actual_atol = _DTYPE_PRECISIONS.get(actual.dtype, (0.0, 0.0))
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expected_rtol, expected_atol = _DTYPE_PRECISIONS.get(expected.dtype, (0.0, 0.0))
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return max(actual_rtol, expected_rtol), max(actual_atol, expected_atol)
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# TODO: include the deprecation as soon as torch.testing.assert_close is stable
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# @warn_deprecated(
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# "Use torch.testing.assert_close instead. "
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# "For detailed upgrade instructions see https://github.com/pytorch/pytorch/issues/61844."
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# )
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def assert_allclose(
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actual: Any,
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expected: Any,
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rtol: Optional[float] = None,
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atol: Optional[float] = None,
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equal_nan: bool = True,
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msg: str = "",
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) -> None:
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if not isinstance(actual, torch.Tensor):
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actual = torch.tensor(actual)
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if not isinstance(expected, torch.Tensor):
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expected = torch.tensor(expected, dtype=actual.dtype)
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if rtol is None and atol is None:
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rtol, atol = _get_default_rtol_and_atol(actual, expected)
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torch.testing.assert_close(
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actual,
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expected,
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rtol=rtol,
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atol=atol,
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equal_nan=equal_nan,
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check_device=True,
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check_dtype=False,
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check_stride=False,
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msg=msg or None,
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)
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# We iterate over all dtype getters and expose them here with an added deprecation warning
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for name in _legacy.__all_dtype_getters__:
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fn = getattr(_legacy, name)
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instructions = (
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lambda name, args, kwargs, return_value: f"This call to {name}(...) can be replaced with {return_value}."
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)
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globals()[name] = warn_deprecated(instructions)(fn)
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__all__.append(name)
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instructions = lambda name, args, kwargs, return_value: f"This call can be replaced with {return_value}." # noqa: E731
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get_all_device_types = warn_deprecated(instructions)(_legacy.get_all_device_types)
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