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[codemod][lint][fbcode/c*] Enable BLACK by default

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Test Plan: manual inspection & sandcastle

Reviewed By: zertosh

Differential Revision: D30279364

fbshipit-source-id: c1ed77dfe43a3bde358f92737cd5535ae5d13c9a
This commit is contained in:
Zsolt Dollenstein
2021-08-12 10:56:55 -07:00
committed by Facebook GitHub Bot
parent aac3c7bd06
commit b004307252
188 changed files with 56875 additions and 28744 deletions
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37
test/test_cpp_extensions_aot.py
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@ -1,15 +1,16 @@
import os
import unittest
import torch.testing._internal.common_utils as common
from torch.testing._internal.common_utils import IS_WINDOWS
from torch.testing._internal.common_cuda import TEST_CUDA
import torch
import torch.backends.cudnn
import torch.testing._internal.common_utils as common
import torch.utils.cpp_extension
from torch.testing._internal.common_cuda import TEST_CUDA
from torch.testing._internal.common_utils import IS_WINDOWS
try:
import pytest
HAS_PYTEST = True
except ImportError as e:
HAS_PYTEST = False
@ -102,28 +103,28 @@ class TestCppExtensionAOT(common.TestCase):
class TestMSNPUTensor(common.TestCase):
def test_unregistered(self):
a = torch.arange(0, 10, device='cpu')
a = torch.arange(0, 10, device="cpu")
with self.assertRaisesRegex(RuntimeError, "Could not run"):
b = torch.arange(0, 10, device='msnpu')
b = torch.arange(0, 10, device="msnpu")
def test_zeros(self):
a = torch.empty(5, 5, device='cpu')
self.assertEqual(a.device, torch.device('cpu'))
a = torch.empty(5, 5, device="cpu")
self.assertEqual(a.device, torch.device("cpu"))
b = torch.empty(5, 5, device='msnpu')
self.assertEqual(b.device, torch.device('msnpu', 0))
b = torch.empty(5, 5, device="msnpu")
self.assertEqual(b.device, torch.device("msnpu", 0))
self.assertEqual(msnpu_extension.get_test_int(), 0)
self.assertEqual(torch.get_default_dtype(), b.dtype)
c = torch.empty((5, 5), dtype=torch.int64, device='msnpu')
c = torch.empty((5, 5), dtype=torch.int64, device="msnpu")
self.assertEqual(msnpu_extension.get_test_int(), 0)
self.assertEqual(torch.int64, c.dtype)
def test_add(self):
a = torch.empty(5, 5, device='msnpu', requires_grad=True)
a = torch.empty(5, 5, device="msnpu", requires_grad=True)
self.assertEqual(msnpu_extension.get_test_int(), 0)
b = torch.empty(5, 5, device='msnpu')
b = torch.empty(5, 5, device="msnpu")
self.assertEqual(msnpu_extension.get_test_int(), 0)
c = a + b
@ -132,9 +133,9 @@ class TestMSNPUTensor(common.TestCase):
def test_conv_backend_override(self):
# To simplify tests, we use 4d input here to avoid doing view4d( which
# needs more overrides) in _convolution.
input = torch.empty(2, 4, 10, 2, device='msnpu', requires_grad=True)
weight = torch.empty(6, 4, 2, 2, device='msnpu', requires_grad=True)
bias = torch.empty(6, device='msnpu')
input = torch.empty(2, 4, 10, 2, device="msnpu", requires_grad=True)
weight = torch.empty(6, 4, 2, 2, device="msnpu", requires_grad=True)
bias = torch.empty(6, device="msnpu")
# Make sure forward is overriden
out = torch.nn.functional.conv1d(input, weight, bias, 2, 0, 1, 1)
@ -151,7 +152,6 @@ class TestMSNPUTensor(common.TestCase):
class TestRNGExtension(common.TestCase):
def setUp(self):
super(TestRNGExtension, self).setUp()
@ -161,7 +161,7 @@ class TestRNGExtension(common.TestCase):
t = torch.empty(10, dtype=torch.int64).random_()
self.assertNotEqual(t, fourty_two)
gen = torch.Generator(device='cpu')
gen = torch.Generator(device="cpu")
t = torch.empty(10, dtype=torch.int64).random_(generator=gen)
self.assertNotEqual(t, fourty_two)
@ -187,7 +187,6 @@ class TestRNGExtension(common.TestCase):
@unittest.skipIf(not TEST_CUDA, "CUDA not found")
class TestTorchLibrary(common.TestCase):
def test_torch_library(self):
import torch_test_cpp_extension.torch_library # noqa: F401
@ -203,7 +202,7 @@ class TestTorchLibrary(common.TestCase):
self.assertFalse(s(True, False))
self.assertFalse(s(False, True))
self.assertFalse(s(False, False))
self.assertIn('torch_library::logical_and', str(s.graph))
self.assertIn("torch_library::logical_and", str(s.graph))
if __name__ == "__main__":