[BE][Easy][6/19] enforce style for empty lines in import segments in test/ (#129757)

See pytorch/pytorch#129751 (comment). Most changes are auto-generated by linter.

You can review these PRs via:

```bash
git diff --ignore-all-space --ignore-blank-lines HEAD~1
```

Pull Request resolved: pytorch/pytorch#129757
Approved by: https://github.com/ezyang

Author: XuehaiPan

test/conftest.py

@@ -17,8 +17,10 @@
 from _pytest.reports import TestReport
 from _pytest.stash import StashKey
 from _pytest.terminal import _get_raw_skip_reason
+
 from pytest_shard_custom import pytest_addoptions as shard_addoptions, PytestShardPlugin
 
+
 if TYPE_CHECKING:
     from _pytest._code.code import ReprFileLocation
 

test/load_torchscript_model.py

@@ -2,6 +2,7 @@
 
 import torch
 
+
 if __name__ == "__main__":
     script_mod = torch.jit.load(sys.argv[1])
     mod = torch.load(sys.argv[1] + ".orig")

test/run_test.py

@@ -38,10 +38,11 @@
     TEST_WITH_SLOW_GRADCHECK,
 )
 
-REPO_ROOT = Path(__file__).resolve().parent.parent
 
 # using tools/ to optimize test run.
+REPO_ROOT = Path(__file__).resolve().parent.parent
 sys.path.insert(0, str(REPO_ROOT))
+
 from tools.stats.import_test_stats import (
     ADDITIONAL_CI_FILES_FOLDER,
     TEST_CLASS_TIMES_FILE,
@@ -71,10 +72,11 @@
 )
 
 
-HAVE_TEST_SELECTION_TOOLS = True
 # Make sure to remove REPO_ROOT after import is done
 sys.path.remove(str(REPO_ROOT))
 
+
+HAVE_TEST_SELECTION_TOOLS = True
 TEST_CONFIG = os.getenv("TEST_CONFIG", "")
 BUILD_ENVIRONMENT = os.getenv("BUILD_ENVIRONMENT", "")
 RERUN_DISABLED_TESTS = os.getenv("PYTORCH_TEST_RERUN_DISABLED_TESTS", "0") == "1"

test/simulate_nccl_errors.py

@@ -5,6 +5,7 @@
 import torch
 import torch.distributed as c10d
 
+
 logging.basicConfig(
     format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO
 )

test/test_ao_sparsity.py

@@ -1,7 +1,7 @@
 # Owner(s): ["module: unknown"]
 
 # Kernels
-from ao.sparsity.test_kernels import (  # noqa: F401  # noqa: F401
+from ao.sparsity.test_kernels import (  # noqa: F401
     TestQuantizedSparseKernels,
     TestQuantizedSparseLayers,
 )
@@ -10,30 +10,28 @@
 from ao.sparsity.test_parametrization import TestFakeSparsity  # noqa: F401
 
 # Scheduler
-from ao.sparsity.test_scheduler import (  # noqa: F401  # noqa: F401
-    TestCubicScheduler,
-    TestScheduler,
-)
+from ao.sparsity.test_scheduler import TestCubicScheduler, TestScheduler  # noqa: F401
 
 # Sparsifier
-from ao.sparsity.test_sparsifier import (  # noqa: F401  # noqa: F401  # noqa: F401
+from ao.sparsity.test_sparsifier import (  # noqa: F401
     TestBaseSparsifier,
     TestNearlyDiagonalSparsifier,
     TestWeightNormSparsifier,
 )
 
 # Structured Pruning
-from ao.sparsity.test_structured_sparsifier import (  # noqa: F401  # noqa: F401  # noqa: F401
+from ao.sparsity.test_structured_sparsifier import (  # noqa: F401
     TestBaseStructuredSparsifier,
     TestFPGMPruner,
     TestSaliencyPruner,
 )
 
 from torch.testing._internal.common_utils import IS_ARM64, run_tests
 
+
 # Composability
 if not IS_ARM64:
-    from ao.sparsity.test_composability import (  # noqa: F401  # noqa: F401
+    from ao.sparsity.test_composability import (  # noqa: F401
         TestComposability,
         TestFxComposability,
     )
@@ -47,7 +45,7 @@
 from ao.sparsity.test_data_scheduler import TestBaseDataScheduler  # noqa: F401
 
 # Data Sparsifier
-from ao.sparsity.test_data_sparsifier import (  # noqa: F401  # noqa: F401  # noqa: F401
+from ao.sparsity.test_data_sparsifier import (  # noqa: F401
     TestBaseDataSparsifier,
     TestNormDataSparsifiers,
     TestQuantizationUtils,
@@ -56,5 +54,6 @@
 # Utilities
 from ao.sparsity.test_sparsity_utils import TestSparsityUtilFunctions  # noqa: F401
 
+
 if __name__ == "__main__":
     run_tests()

test/test_autograd.py

@@ -29,7 +29,6 @@
 import torch
 import torch.autograd._functions
 import torch.autograd.forward_ad as fwAD
-
 from torch import inf, nan, nn
 from torch.autograd import (
     _calculate_shape,
@@ -14064,6 +14063,7 @@ def log_grad_order(grad: torch.Tensor, name: str, order):
 from autograd.test_functional import TestAutogradFunctional  # noqa: F401
 from autograd.test_logging import TestAutogradLogging  # noqa: F401
 
+
 # e.g., TestAutogradDeviceTypeCPU and TestAutogradDeviceTypeCUDA
 instantiate_device_type_tests(TestAutogradDeviceType, globals(), except_for=None)
 

test/test_binary_ufuncs.py

@@ -12,7 +12,6 @@
 import numpy as np
 
 import torch
-
 import torch.autograd.forward_ad as fwAD
 from torch import inf, nan
 from torch.testing import make_tensor
@@ -68,6 +67,7 @@
     xfailIfTorchDynamo,
 )
 
+
 if TEST_SCIPY:
     import scipy.integrate
     import scipy.special

test/test_bundled_images.py

@@ -10,6 +10,7 @@
 import torch.utils.bundled_inputs
 from torch.testing._internal.common_utils import TestCase
 
+
 torch.ops.load_library("//caffe2/torch/fb/operators:decode_bundled_image")
 
 

test/test_compile_benchmark_util.py

@@ -6,6 +6,7 @@
 import torch._dynamo as torchdynamo
 from torch.testing._internal.common_utils import run_tests, TEST_CUDA, TestCase
 
+
 try:
     import tabulate  # noqa: F401  # type: ignore[import]
 

test/test_complex.py

@@ -10,6 +10,7 @@
 from torch.testing._internal.common_dtype import complex_types
 from torch.testing._internal.common_utils import run_tests, set_default_dtype, TestCase
 
+
 devices = (torch.device("cpu"), torch.device("cuda:0"))
 
 

test/test_cpp_api_parity.py

@@ -16,6 +16,7 @@
 import torch.testing._internal.common_nn as common_nn
 import torch.testing._internal.common_utils as common
 
+
 # NOTE: turn this on if you want to print source code of all C++ tests (e.g. for debugging purpose)
 PRINT_CPP_SOURCE = False
 

test/test_cpp_extensions_aot.py

@@ -8,12 +8,12 @@
 
 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, skipIfTorchDynamo
 
+
 try:
     import pytest
 

test/test_cpp_extensions_jit.py

@@ -13,7 +13,6 @@
 import torch
 import torch.backends.cudnn
 import torch.multiprocessing as mp
-
 import torch.testing._internal.common_utils as common
 import torch.utils.cpp_extension
 from torch.testing._internal.common_cuda import TEST_CUDA, TEST_CUDNN
@@ -27,6 +26,7 @@
     ROCM_HOME,
 )
 
+
 # define TEST_ROCM before changing TEST_CUDA
 TEST_ROCM = TEST_CUDA and torch.version.hip is not None and ROCM_HOME is not None
 TEST_CUDA = TEST_CUDA and CUDA_HOME is not None

test/test_cpp_extensions_open_device_registration.py

@@ -10,7 +10,6 @@
 from unittest.mock import patch
 
 import torch
-
 import torch.testing._internal.common_utils as common
 import torch.utils.cpp_extension
 from torch.testing._internal.common_utils import (

test/test_cuda.py

@@ -19,7 +19,6 @@
 
 import torch
 import torch.cuda
-
 from torch import inf, nan
 from torch.cuda._memory_viz import (
     _profile_to_snapshot,
@@ -72,6 +71,7 @@
 from torch.utils.checkpoint import checkpoint_sequential
 from torch.utils.viz._cycles import observe_tensor_cycles
 
+
 # load_tests from common_utils is used to automatically filter tests for
 # sharding on sandcastle. This line silences flake warnings
 load_tests = load_tests

test/test_cuda_expandable_segments.py

@@ -11,15 +11,16 @@
 )
 
 import torch
-
 from torch.testing._internal.common_cuda import IS_JETSON, IS_WINDOWS
 from torch.testing._internal.common_utils import run_tests, TEST_WITH_ROCM
 
-REPO_ROOT = pathlib.Path(__file__).resolve().parent.parent
 
+REPO_ROOT = pathlib.Path(__file__).resolve().parent.parent
 sys.path.insert(0, str(REPO_ROOT))
+
 from tools.stats.import_test_stats import get_disabled_tests
 
+
 # Make sure to remove REPO_ROOT after import is done
 sys.path.remove(str(REPO_ROOT))
 

test/test_cuda_multigpu.py

@@ -10,7 +10,6 @@
 import tempfile
 import threading
 import unittest
-
 from itertools import chain, repeat
 from typing import NamedTuple
 
@@ -37,6 +36,7 @@
     TestCase,
 )
 
+
 TEST_CUDAMALLOCASYNC = TEST_CUDA and (
     torch.cuda.get_allocator_backend() == "cudaMallocAsync"
 )

test/test_cuda_nvml_based_avail.py

@@ -8,6 +8,7 @@
 
 import torch
 
+
 # NOTE: Each of the tests in this module need to be run in a brand new process to ensure CUDA is uninitialized
 # prior to test initiation.
 with patch.dict(os.environ, {"PYTORCH_NVML_BASED_CUDA_CHECK": "1"}):

test/test_cuda_primary_ctx.py

@@ -12,6 +12,7 @@
     TestCase,
 )
 
+
 # NOTE: this needs to be run in a brand new process
 
 if not TEST_CUDA:

test/test_cuda_trace.py

@@ -8,6 +8,7 @@
 import torch.cuda._gpu_trace as gpu_trace
 from torch.testing._internal.common_utils import NoTest, run_tests, TEST_CUDA, TestCase
 
+
 # NOTE: Each test needs to be run in a brand new process, to reset the registered hooks
 # and make sure the CUDA streams are initialized for each test that uses them.
 

test/test_custom_ops.py

@@ -1,29 +1,47 @@
 # Owner(s): ["module: custom-operators"]
 
-from torch.testing._internal.common_utils import *  # noqa: F403
-from torch.testing._internal.common_device_type import *  # noqa: F403
 import collections
-
 import itertools
 import os
 import re
+import subprocess
+import sys
 import typing
+import unittest
+from typing import *  # noqa: F403
 
-import torch._custom_ops as custom_ops
+import numpy as np
 
+import torch._custom_ops as custom_ops
 import torch.testing._internal.optests as optests
+import torch.utils._pytree as pytree
 import torch.utils.cpp_extension
-
 from functorch import make_fx
 from torch import Tensor
-from torch._custom_op.impl import custom_op, CustomOp, infer_schema
+from torch._custom_op.impl import CustomOp, infer_schema
 from torch._library.infer_schema import tuple_to_list
 from torch._utils_internal import get_file_path_2
 from torch.testing._internal import custom_op_db
 from torch.testing._internal.common_cuda import TEST_CUDA
+from torch.testing._internal.common_device_type import (
+    instantiate_device_type_tests,
+    OpDTypes,
+    ops,
+)
+from torch.testing._internal.common_utils import (
+    instantiate_parametrized_tests,
+    IS_WINDOWS,
+    parametrize,
+    run_tests,
+    skipIfTorchDynamo,
+    subtest,
+    TestCase,
+)
 from torch.testing._internal.custom_op_db import numpy_nonzero
-from typing import *  # noqa: F403
-import numpy as np
+
+
+# Shadowed by `torch.testing._internal.common_utils.custom_op`
+from torch._custom_op.impl import custom_op  # usort: skip
 
 
 def requires_compile(fun):

test/test_decomp.py

@@ -1,7 +1,6 @@
 # Owner(s): ["module: decompositions"]
 
 import functools
-
 import itertools
 import re
 import unittest
@@ -43,9 +42,9 @@
 )
 from torch.utils import _pytree as pytree
 from torch.utils._python_dispatch import TorchDispatchMode
-
 from torch.utils._pytree import tree_flatten, tree_map, tree_unflatten
 
+
 aten = torch.ops.aten
 
 

test/test_deploy.py

@@ -4,7 +4,6 @@
 import types
 
 from torch.testing._internal.common_utils import run_tests, TestCase
-
 from torch.utils._freeze import Freezer, PATH_MARKER
 
 

test/test_dispatch.py

@@ -3,14 +3,14 @@
 import itertools
 import os
 import re
-
 from collections import namedtuple
 
 import torch._C as C
 import torch.utils.cpp_extension
 from torch._python_dispatcher import PythonDispatcher
 from torch.testing._internal.common_utils import run_tests, TestCase
 
+
 # TODO: Expand the dispatcher API to be a generic API for interfacing with
 # the dispatcher from Python!
 #