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Revert D25757691: [pytorch][PR] Run mypy over test/test_utils.py
Test Plan: revert-hammer
Differential Revision:
D25757691 (c86cfcd81d)
Original commit changeset: 145ce3ae532c
fbshipit-source-id: 3dfd68f0c42fc074cde15c6213a630b16e9d8879
This commit is contained in:
Rong Rong (AI Infra)
Facebook GitHub Bot
parent
e442ac1e3f
commit
e3c56ddde6
3
mypy.ini
3
mypy.ini
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@ -26,8 +26,7 @@ files =
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test/test_numpy_interop.py,
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test/test_torch.py,
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test/test_type_hints.py,
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test/test_type_info.py,
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test/test_utils.py
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test/test_type_info.py
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# Minimum version supported - variable annotations were introduced
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@ -10,7 +10,6 @@ import unittest
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import torch
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import torch.nn as nn
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import torch.utils.data
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from torch.utils.data import DataLoader
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import torch.cuda
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from torch.utils.checkpoint import checkpoint, checkpoint_sequential
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import torch.utils.cpp_extension
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@ -29,7 +28,7 @@ HAS_CUDA = torch.cuda.is_available()
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from torch.testing._internal.common_utils import TestCase, run_tests
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class RandomDatasetMock(torch.utils.data.Dataset):
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class RandomDatasetMock(object):
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def __getitem__(self, index):
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return torch.tensor([torch.rand(1).item(), random.uniform(0, 1)])
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@ -191,7 +190,7 @@ class TestCheckpoint(TestCase):
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b = torch.randn(1, 100, requires_grad=True)
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with self.assertRaises(TypeError):
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checkpoint_sequential(model, 1, a, b) # type: ignore[call-arg]
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checkpoint_sequential(model, 1, a, b)
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def test_checkpoint_sequential_deprecated_no_args(self):
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class Noop(nn.Module):
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@ -201,7 +200,7 @@ class TestCheckpoint(TestCase):
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model = nn.Sequential(Noop())
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with self.assertRaises(TypeError):
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checkpoint_sequential(model, 1) # type: ignore[call-arg]
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checkpoint_sequential(model, 1)
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def test_checkpoint_rng_cpu(self):
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for _ in range(5):
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@ -278,7 +277,7 @@ class TestCheckpoint(TestCase):
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out = checkpoint(run_fn, input_var, input_var2)
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out[0].sum().backward()
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def run_fn2(tensor1, tensor2):
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def run_fn(tensor1, tensor2):
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return tensor1
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input_var = torch.randn(1, 4, requires_grad=False)
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input_var2 = torch.randn(1, 4, requires_grad=True)
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@ -286,7 +285,7 @@ class TestCheckpoint(TestCase):
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RuntimeError,
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r"none of output has requires_grad=True, this checkpoint\(\) is not necessary"
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):
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out = checkpoint(run_fn2, input_var, input_var2)
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out = checkpoint(run_fn, input_var, input_var2)
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out.sum().backward()
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class TestDataLoader(TestCase):
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@ -309,10 +308,7 @@ class TestDataLoader(TestCase):
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self.assertEqual(x1, x2)
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def test_single_keep(self):
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# self.dataset is a Tensor here; technically not a valid input because
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# not a Dataset subclass, but needs to stay working so add ignore's
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# for type checking with mypy
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dataloader : DataLoader = DataLoader(self.dataset, # type: ignore[arg-type]
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dataloader = torch.utils.data.DataLoader(self.dataset,
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batch_size=self.batch_size,
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num_workers=0,
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drop_last=False)
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@ -320,7 +316,7 @@ class TestDataLoader(TestCase):
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self.assertEqual(len(list(dataiter)), 2)
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def test_single_drop(self):
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dataloader : DataLoader = DataLoader(self.dataset, # type: ignore[arg-type]
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dataloader = torch.utils.data.DataLoader(self.dataset,
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batch_size=self.batch_size,
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num_workers=0,
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drop_last=True)
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@ -329,7 +325,7 @@ class TestDataLoader(TestCase):
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@unittest.skip("FIXME: Intermittent CUDA out-of-memory error on Windows and time-out under ASAN")
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def test_multi_keep(self):
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dataloader : DataLoader = DataLoader(self.dataset, # type: ignore[arg-type]
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dataloader = torch.utils.data.DataLoader(self.dataset,
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batch_size=self.batch_size,
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num_workers=2,
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drop_last=False)
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@ -337,7 +333,7 @@ class TestDataLoader(TestCase):
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self.assertEqual(len(list(dataiter)), 2)
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def test_multi_drop(self):
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dataloader : DataLoader = DataLoader(self.dataset, # type: ignore[arg-type]
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dataloader = torch.utils.data.DataLoader(self.dataset,
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batch_size=self.batch_size,
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num_workers=2,
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drop_last=True)
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@ -351,7 +347,7 @@ test_dir = os.path.abspath(os.path.dirname(str(__file__)))
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class TestFFI(TestCase):
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def test_deprecated(self):
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with self.assertRaisesRegex(ImportError, "torch.utils.ffi is deprecated. Please use cpp extensions instead."):
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from torch.utils.ffi import create_extension # type: ignore # noqa: F401
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from torch.utils.ffi import create_extension # noqa: F401
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@unittest.skipIf('SKIP_TEST_BOTTLENECK' in os.environ.keys(), 'SKIP_TEST_BOTTLENECK is set')
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@ -368,9 +364,9 @@ class TestBottleneck(TestCase):
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p.kill()
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output, err = p.communicate()
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rc = p.returncode
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output_str = output.decode("ascii")
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err_str = err.decode("ascii")
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return (rc, output_str, err_str)
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output = output.decode("ascii")
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err = err.decode("ascii")
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return (rc, output, err)
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def _run_bottleneck(self, test_file, scriptargs=''):
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curdir = os.path.dirname(os.path.abspath(__file__))
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@ -665,7 +661,7 @@ class TestAssert(TestCase):
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# data can be passed without errors
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x = torch.randn(4, 4).fill_(1.0)
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ms(x)
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with self.assertRaisesRegex(torch.jit.Error, "foo"): # type: ignore[type-var]
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with self.assertRaisesRegex(torch.jit.Error, "foo"):
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ms(torch.tensor([False], dtype=torch.bool))
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@ -17,7 +17,7 @@ from .file_baton import FileBaton
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from ._cpp_extension_versioner import ExtensionVersioner
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from .hipify import hipify_python
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from .hipify.hipify_python import get_hip_file_path, GeneratedFileCleaner
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from typing import List, Optional, Union
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from typing import List, Optional
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from setuptools.command.build_ext import build_ext
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from pkg_resources import packaging # type: ignore
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@ -980,7 +980,7 @@ def library_paths(cuda: bool = False) -> List[str]:
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def load(name,
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sources: Union[str, List[str]],
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sources: List[str],
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extra_cflags=None,
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extra_cuda_cflags=None,
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extra_ldflags=None,
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