[BE][Easy][7/19] enforce style for empty lines in import segments in test/[a-c]*/ and test/[q-z]*/ (pytorch#129758)

See 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#129758
Approved by: https://github.com/ezyang

Author: XuehaiPan

test/ao/sparsity/test_activation_sparsifier.py

@@ -13,6 +13,7 @@
 from torch.ao.pruning.sparsifier.utils import module_to_fqn
 from torch.testing._internal.common_utils import skipIfTorchDynamo, TestCase
 
+
 logging.basicConfig(
     format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO
 )

test/ao/sparsity/test_composability.py

@@ -16,6 +16,7 @@
 )
 from torch.testing._internal.common_utils import TestCase
 
+
 logging.basicConfig(
     format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO
 )

test/ao/sparsity/test_data_scheduler.py

@@ -8,10 +8,10 @@
 import torch
 from torch import nn
 from torch.ao.pruning._experimental.data_scheduler import BaseDataScheduler
-
 from torch.ao.pruning._experimental.data_sparsifier import DataNormSparsifier
 from torch.testing._internal.common_utils import TestCase
 
+
 logging.basicConfig(
     format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO
 )

test/ao/sparsity/test_data_sparsifier.py

@@ -4,12 +4,10 @@
 import itertools
 import logging
 import math
-
 from typing import Tuple
 
 import torch
 from torch import nn
-
 from torch.ao.pruning._experimental.data_sparsifier import (
     BaseDataSparsifier,
     DataNormSparsifier,
@@ -20,6 +18,7 @@
 from torch.nn.utils.parametrize import is_parametrized
 from torch.testing._internal.common_utils import TestCase
 
+
 logging.basicConfig(
     format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO
 )

test/ao/sparsity/test_kernels.py

@@ -9,7 +9,6 @@
 
 import torch
 import torch.ao.quantization as tq
-
 from torch import nn
 from torch.ao.pruning.sparsifier.utils import fqn_to_module
 from torch.testing._internal.common_quantized import (
@@ -20,9 +19,9 @@
     qengine_is_qnnpack,
     qengine_is_x86,
 )
-
 from torch.testing._internal.common_utils import run_tests, skipIfTorchDynamo, TestCase
 
+
 # TODO: Once more test files are created, move the contents to a ao folder.
 
 logging.basicConfig(

test/ao/sparsity/test_parametrization.py

@@ -4,12 +4,12 @@
 import logging
 
 import torch
-
 from torch import nn
 from torch.ao.pruning.sparsifier import utils
 from torch.nn.utils import parametrize
 from torch.testing._internal.common_utils import TestCase
 
+
 logging.basicConfig(
     format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO
 )

test/ao/sparsity/test_scheduler.py

@@ -3,9 +3,7 @@
 import warnings
 
 from torch import nn
-
 from torch.ao.pruning import BaseScheduler, CubicSL, LambdaSL, WeightNormSparsifier
-
 from torch.testing._internal.common_utils import TestCase
 
 

test/ao/sparsity/test_sparsifier.py

@@ -18,9 +18,9 @@
     MockSparseLinear,
     SimpleLinear,
 )
-
 from torch.testing._internal.common_utils import TestCase
 
+
 logging.basicConfig(
     format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO
 )

test/ao/sparsity/test_sparsity_utils.py

@@ -9,7 +9,6 @@
     get_arg_info_from_tensor_fqn,
     module_to_fqn,
 )
-
 from torch.testing._internal.common_quantization import (
     ConvBnReLUModel,
     ConvModel,
@@ -21,6 +20,7 @@
 )
 from torch.testing._internal.common_utils import TestCase
 
+
 logging.basicConfig(
     format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO
 )

test/ao/sparsity/test_structured_sparsifier.py

@@ -29,7 +29,6 @@
     SimpleConv2d,
     SimpleLinear,
 )
-
 from torch.testing._internal.common_utils import skipIfTorchDynamo, TestCase
 
 

test/autograd/test_complex.py

@@ -1,7 +1,6 @@
 # Owner(s): ["module: autograd"]
 
 import torch
-
 from torch.testing._internal.common_utils import gradcheck, run_tests, TestCase
 
 

test/autograd/test_functional.py

@@ -6,7 +6,6 @@
 
 import torch
 import torch.autograd.functional as autogradF
-
 from torch.testing._internal.common_cuda import TEST_CUDA
 from torch.testing._internal.common_utils import (
     gradcheck,
@@ -19,6 +18,7 @@
 )
 from torch.testing._internal.logging_tensor import LoggingTensor
 
+
 # Utilities for parametrizing the tensor constructors used in autograd tests
 #
 # TODO: maybe move somewhere so other tests can also use

test/bottleneck_test/test.py

@@ -2,5 +2,6 @@
 
 import torch
 
+
 x = torch.ones((3, 3), requires_grad=True)
 (3 * x).sum().backward()

test/bottleneck_test/test_args.py

@@ -4,6 +4,7 @@
 
 import torch
 
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
 

test/cpp/aoti_inference/compile_model.py

@@ -1,5 +1,4 @@
 import torch
-
 from torch.export import Dim
 
 

test/cpp/aoti_inference/test.py

@@ -2,6 +2,7 @@
 from torch._export import aot_compile
 from torch.export import Dim
 
+
 torch.manual_seed(1337)
 
 

test/cpp/api/init_baseline.py

@@ -4,6 +4,7 @@
 
 import torch
 
+
 HEADER = """
 #include <torch/types.h>
 

test/cpp_api_parity/functional_impl_check.py

@@ -21,7 +21,6 @@
 from string import Template
 
 import torch
-
 from cpp_api_parity.sample_functional import SAMPLE_FUNCTIONAL_CPP_SOURCE
 from cpp_api_parity.utils import (
     add_test,
@@ -40,6 +39,7 @@
     try_remove_folder,
 )
 
+
 # Expected substitutions:
 #
 # ${functional_variant_name}  (e.g. `BCELoss_no_reduce`)

test/cpp_api_parity/module_impl_check.py

@@ -21,7 +21,6 @@
 from string import Template
 
 import torch
-
 from cpp_api_parity.sample_module import SAMPLE_MODULE_CPP_SOURCE
 from cpp_api_parity.utils import (
     add_test,
@@ -40,6 +39,7 @@
     try_remove_folder,
 )
 
+
 # Expected substitutions:
 #
 # ${module_variant_name}  (e.g. `Linear_no_bias_cpu`)

test/cpp_api_parity/parity_table_parser.py

@@ -1,5 +1,6 @@
 from collections import namedtuple
 
+
 ParityStatus = namedtuple("ParityStatus", ["has_impl_parity", "has_doc_parity"])
 
 """

test/cpp_api_parity/sample_functional.py

@@ -2,6 +2,7 @@
 import torch.nn.functional as F
 from torch.testing._internal.common_nn import wrap_functional
 
+
 """
 `sample_functional` is used by `test_cpp_api_parity.py` to test that Python / C++ API
 parity test harness works for `torch.nn.functional` functions.

test/cpp_api_parity/sample_module.py

@@ -1,5 +1,6 @@
 import torch
 
+
 """
 `SampleModule` is used by `test_cpp_api_parity.py` to test that Python / C++ API
 parity test harness works for `torch.nn.Module` subclasses.

test/cpp_api_parity/utils.py

@@ -9,6 +9,7 @@
 import torch.utils.cpp_extension
 from torch.testing._internal.common_cuda import TEST_CUDA
 
+
 # Note that this namedtuple is for C++ parity test mechanism's internal use.
 # For guidance on how to add a new C++ parity test, please see
 # NOTE [How to check NN module / functional API parity between Python and C++ frontends]

test/cpp_extensions/no_python_abi_suffix_test/setup.py

@@ -2,6 +2,7 @@
 
 from torch.utils.cpp_extension import BuildExtension, CppExtension
 
+
 setup(
     name="no_python_abi_suffix_test",
     ext_modules=[

test/cpp_extensions/setup.py

@@ -13,6 +13,7 @@
     ROCM_HOME,
 )
 
+
 if sys.platform == "win32":
     vc_version = os.getenv("VCToolsVersion", "")
     if vc_version.startswith("14.16."):

test/custom_operator/my_custom_ops.py

@@ -2,6 +2,7 @@
 
 import torch
 
+
 torch.ops.load_library(get_custom_op_library_path())
 
 

test/custom_operator/my_custom_ops2.py

@@ -2,6 +2,7 @@
 
 import torch
 
+
 torch.ops.load_library(get_custom_op_library_path())
 
 

test/custom_operator/pointwise.py

@@ -2,6 +2,7 @@
 
 import torch
 
+
 torch.ops.load_library(get_custom_op_library_path())
 
 

test/custom_operator/test_custom_ops.py

@@ -12,6 +12,7 @@
 from torch import ops
 from torch.testing._internal.common_utils import IS_WINDOWS, run_tests, TestCase
 
+
 torch.ops.import_module("pointwise")
 
 

test/quantization/bc/test_backward_compatibility.py

@@ -12,7 +12,6 @@
 import torch.ao.nn.quantized.dynamic as nnqd
 import torch.ao.quantization.quantize_fx as quantize_fx
 import torch.nn as nn
-
 from torch.ao.quantization import MinMaxObserver, PerChannelMinMaxObserver
 from torch.fx import GraphModule
 from torch.testing._internal.common_quantization import skipIfNoFBGEMM

test/quantization/core/experimental/test_adaround_eager.py

@@ -7,7 +7,6 @@
 from torch.ao.quantization.experimental.adaround_optimization import (
     AdaptiveRoundingOptimizer,
 )
-
 from torch.nn import functional as F
 from torch.quantization.observer import MinMaxObserver
 from torch.testing._internal.common_quantization import QuantizationTestCase

test/quantization/core/experimental/test_float8.py

@@ -17,6 +17,7 @@
     TestCase,
 )
 
+
 FLOAT8_DTYPES = [
     torch.float8_e5m2,
     torch.float8_e5m2fnuz,

test/quantization/jit/test_ondevice_quantization.py

@@ -5,25 +5,19 @@
 
 import torch
 import torch._C
-
 from torch.ao.quantization import default_dynamic_qconfig, per_channel_dynamic_qconfig
-
 from torch.ao.quantization.quantize_jit import (
     _prepare_ondevice_dynamic_jit,
     _quantize_ondevice_dynamic_jit,
     convert_dynamic_jit,
     prepare_dynamic_jit,
 )
-
 from torch.jit.mobile import _load_for_lite_interpreter, LiteScriptModule
-
 from torch.testing import FileCheck
-
 from torch.testing._internal.common_quantization import (
     get_script_module,
     LinearAddModel,
 )
-
 from torch.testing._internal.common_utils import TestCase
 from torch.utils import bundled_inputs as bundled_inputs
 

test/quantization/jit/test_quantize_jit.py

@@ -43,13 +43,10 @@
     prepare_jit,
     script_qconfig,
 )
-
 from torch.jit._recursive import wrap_cpp_module
-
 from torch.testing import FileCheck
 
 # Annotated models
-
 from torch.testing._internal.common_quantization import (
     AnnotatedConvBnModel,
     AnnotatedConvModel,
@@ -76,7 +73,6 @@
     qengine_is_fbgemm,
     qengine_is_qnnpack,
 )
-
 from torch.testing._internal.common_utils import set_default_dtype
 from torch.testing._internal.jit_utils import (
     attrs_with_prefix,

test/quantization/pt2e/test_duplicate_dq.py

@@ -5,7 +5,6 @@
 
 import torch
 from torch._export import capture_pre_autograd_graph
-
 from torch.ao.quantization.observer import (
     HistogramObserver,
     MinMaxObserver,
@@ -25,7 +24,6 @@
     OP_TO_ANNOTATOR,
     QuantizationConfig,
 )
-
 from torch.testing._internal.common_quantization import QuantizationTestCase
 from torch.testing._internal.common_utils import IS_WINDOWS
 

test/quantization/pt2e/test_graph_utils.py

@@ -4,7 +4,6 @@
 
 import torch
 import torch._dynamo as torchdynamo
-
 from torch.ao.quantization.pt2e.graph_utils import (
     find_sequential_partitions,
     get_equivalent_types,