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[BE] Enable ruff's UP rules and autoformat test/ (#105434)

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Pull Request resolved: https://github.com/pytorch/pytorch/pull/105434
Approved by: https://github.com/albanD
This commit is contained in:
Justin Chu
2023-07-19 07:40:18 -07:00
committed by PyTorch MergeBot
parent 7b56238551
commit 73e1455327
88 changed files with 427 additions and 451 deletions
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14
test/test_reductions.py
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@ -1968,9 +1968,9 @@ class TestReductions(TestCase):
a[2, 2] = nan
actual = f(a.to(device)).cpu()
expected = f(a).cpu()
self.assertEqual(torch.isnan(actual), torch.isnan(expected), msg='nans for {}'.format(name))
self.assertEqual(torch.isnan(actual), torch.isnan(expected), msg=f'nans for {name}')
self.assertEqual(actual[~torch.isnan(actual)],
expected[~torch.isnan(expected)], msg='nans for {}'.format(name))
expected[~torch.isnan(expected)], msg=f'nans for {name}')
# TODO: make this test generic using OpInfos
@onlyCUDA
@ -2199,16 +2199,16 @@ class TestReductions(TestCase):
fn_tuple(y, 1, keepdim=False, out=(values[:, 1], indices[:, 1]))
values_expected, indices_expected = fn_tuple(y, 1, keepdim=False)
self.assertEqual(values[:, 1], values_expected,
msg='{} values with out= kwarg'.format(fn_name))
msg=f'{fn_name} values with out= kwarg')
self.assertEqual(indices[:, 1], indices_expected,
msg='{} indices with out= kwarg'.format(fn_name))
msg=f'{fn_name} indices with out= kwarg')
continue
x = torch.randn(5, 3, device=device)
y = torch.randn(5, 3, device=device)
fn(y, 1, keepdim=False, out=x[:, 1])
expected = fn(y, 1, keepdim=False)
self.assertEqual(x[:, 1], expected, msg='{} with out= kwarg'.format(fn_name))
self.assertEqual(x[:, 1], expected, msg=f'{fn_name} with out= kwarg')
@onlyCUDA
@largeTensorTest('10GB')
@ -3498,8 +3498,8 @@ as the input tensor excluding its innermost dimension'):
expected = np.asarray(expected) # transform numpy scalars to numpy.ndarray instances
msg = ("Failed to produce expected results! Input tensor was"
" {0}, torch result is {1}, and reference result is"
" {2}.").format(t, actual, expected) if t.numel() < 10 else None
" {}, torch result is {}, and reference result is"
" {}.").format(t, actual, expected) if t.numel() < 10 else None
self.assertEqual(actual, expected, msg, exact_dtype=exact_dtype)