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d57daa6f85
Summary: Address black + isort fbsource linter warnings from D20558374 (previous diff) Reviewed By: nikhilaravi Differential Revision: D20558373 fbshipit-source-id: d3607de4a01fb24c0d5269634563a7914bddf1c8
59 lines
1.8 KiB
Python
59 lines
1.8 KiB
Python
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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import unittest
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import numpy as np
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import torch
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class TestCaseMixin(unittest.TestCase):
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def assertSeparate(self, tensor1, tensor2) -> None:
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"""
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Verify that tensor1 and tensor2 have their data in distinct locations.
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"""
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self.assertNotEqual(tensor1.storage().data_ptr(), tensor2.storage().data_ptr())
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def assertNotSeparate(self, tensor1, tensor2) -> None:
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"""
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Verify that tensor1 and tensor2 have their data in the same locations.
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"""
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self.assertEqual(tensor1.storage().data_ptr(), tensor2.storage().data_ptr())
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def assertAllSeparate(self, tensor_list) -> None:
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"""
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Verify that all tensors in tensor_list have their data in
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distinct locations.
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"""
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ptrs = [i.storage().data_ptr() for i in tensor_list]
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self.assertCountEqual(ptrs, set(ptrs))
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def assertClose(
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self,
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input,
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other,
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*,
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rtol: float = 1e-05,
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atol: float = 1e-08,
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equal_nan: bool = False
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) -> None:
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"""
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Verify that two tensors or arrays are the same shape and close.
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Args:
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input, other: two tensors or two arrays.
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rtol, atol, equal_nan: as for torch.allclose.
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Note:
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Optional arguments here are all keyword-only, to avoid confusion
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with msg arguments on other assert functions.
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"""
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self.assertEqual(np.shape(input), np.shape(other))
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if torch.is_tensor(input):
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close = torch.allclose(
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input, other, rtol=rtol, atol=atol, equal_nan=equal_nan
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)
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else:
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close = np.allclose(input, other, rtol=rtol, atol=atol, equal_nan=equal_nan)
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self.assertTrue(close)
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