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[Infra][Numpy2] Use `np.asarray` in both np1 and np2 by SigureMo · Pull Request #65947 · PaddlePaddle/Paddle · GitHub
[Infra][Numpy2] Use
[Infra][Numpy2] Use
SigureMo
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[Infra][Numpy2] Use np.asarray directly
[Infra][Numpy2] Use Jul 11, 2024
SigureMo
changed the title
[Infra][Numpy2] Use
[Infra][Numpy2] Use Jul 11, 2024
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[Infra][Numpy2] Use np.asarray in both np1 and np2
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risemeup1
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Jul 15, 2024
Merged
[Infra][Numpy2] Use np.asarray in both np1 and np2
#65947
risemeup1
merged 7 commits into
PaddlePaddle:develop
from
cattidea:infra/use-asarray-directly
Jul 15, 2024
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SigureMo
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np.asarray directly
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np.asarray directlynp.asarray in both np1 and np2
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) * [Infra][Numpy2] Use `np.asarray` directly * rename ut * replace all np.array with np.asarray * Revert "replace all np.array with np.asarray" This reverts commit f712a8d. * disable failed case * rename back * fix test_transform_static
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PR Category
Environment Adaptation
PR Types
Bug fixes
Description
1.x 的
np.array(arr, copy=False)在 1.x 或 2.x 都应该替换为np.asarray(arr)而不是np.asarray(arr, False)，因为np.asarray(arr)的行为就是copy=False的np.array，不需要做额外的兼容性处理1，有一个在 PR-CI-Windows-Inference 流水线因为精度挂掉的 case 暂时禁掉，以免导致整个单测都禁掉顺带修复了下
test_transform_static单测，问题很容易复现，主要是对比裁剪区域时应该跑h_image - h_crop + 1次，但是原来的代码里少了一次，比如原图5x5，裁剪区域4x4，那么对比时应该为(5-4+1) ** 2 = 4次，而不是 1 次PCard-66972
Footnotes
https://numpy.org/devdocs/numpy_2_0_migration_guide.html#adapting-to-changes-in-the-copy-keyword ↩