[BE][Easy][19/19] enforce style for empty lines in import segments in torch/[o-z]*/ (#129771)

See https://github.com/pytorch/pytorch/pull/129751#issue-2380881501. 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: https://github.com/pytorch/pytorch/pull/129771
Approved by: https://github.com/justinchuby, https://github.com/janeyx99

tools/linter/adapters/ufmt_linter.py

@@ -56,7 +56,6 @@ ISORT_SKIPLIST = re.compile(
                     # torch/[e-n]*/**
                     "torch/[e-n]*/**",
                     # torch/[o-z]*/**
-                    "torch/[o-z]*/**",
                 ],
             ),
         )

torch/onnx/__init__.py

@@ -3,6 +3,28 @@ from torch import _C
 from torch._C import _onnx as _C_onnx
 from torch._C._onnx import OperatorExportTypes, TensorProtoDataType, TrainingMode
 
+from ._exporter_states import ExportTypes
+from ._internal.onnxruntime import (
+    is_onnxrt_backend_supported,
+    OrtBackend as _OrtBackend,
+    OrtBackendOptions as _OrtBackendOptions,
+    OrtExecutionProvider as _OrtExecutionProvider,
+)
+from ._type_utils import JitScalarType
+from .errors import CheckerError  # Backwards compatibility
+from .utils import (
+    _optimize_graph,
+    _run_symbolic_function,
+    _run_symbolic_method,
+    export,
+    export_to_pretty_string,
+    is_in_onnx_export,
+    register_custom_op_symbolic,
+    select_model_mode_for_export,
+    unregister_custom_op_symbolic,
+)
+
+
 from . import (  # usort: skip. Keep the order instead of sorting lexicographically
     _deprecation,
     errors,
@@ -25,20 +47,6 @@ from . import (  # usort:skip. Keep the order instead of sorting lexicographical
     utils,
 )
 
-from ._exporter_states import ExportTypes
-from ._type_utils import JitScalarType
-from .errors import CheckerError  # Backwards compatibility
-from .utils import (
-    _optimize_graph,
-    _run_symbolic_function,
-    _run_symbolic_method,
-    export,
-    export_to_pretty_string,
-    is_in_onnx_export,
-    register_custom_op_symbolic,
-    select_model_mode_for_export,
-    unregister_custom_op_symbolic,
-)
 
 from ._internal.exporter import (  # usort: skip. needs to be last to avoid circular import
     DiagnosticOptions,
@@ -53,12 +61,6 @@ from ._internal.exporter import (  # usort:skip. needs to be last to avoid circu
     enable_fake_mode,
 )
 
-from ._internal.onnxruntime import (
-    is_onnxrt_backend_supported,
-    OrtBackend as _OrtBackend,
-    OrtBackendOptions as _OrtBackendOptions,
-    OrtExecutionProvider as _OrtExecutionProvider,
-)
 
 __all__ = [
     # Modules

torch/onnx/_deprecation.py

@@ -6,6 +6,7 @@ import warnings
 from typing import Callable, TypeVar
 from typing_extensions import ParamSpec
 
+
 _T = TypeVar("_T")
 _P = ParamSpec("_P")
 

torch/onnx/_internal/diagnostics/__init__.py

@@ -9,6 +9,7 @@ from ._diagnostic import (
 from ._rules import rules
 from .infra import levels
 
+
 __all__ = [
     "TorchScriptOnnxExportDiagnostic",
     "ExportDiagnosticEngine",

torch/onnx/_internal/diagnostics/_diagnostic.py

@@ -7,12 +7,12 @@ import gzip
 from typing import TYPE_CHECKING
 
 import torch
-
 from torch.onnx._internal.diagnostics import infra
 from torch.onnx._internal.diagnostics.infra import formatter, sarif
 from torch.onnx._internal.diagnostics.infra.sarif import version as sarif_version
 from torch.utils import cpp_backtrace
 
+
 if TYPE_CHECKING:
     from collections.abc import Generator
 

torch/onnx/_internal/diagnostics/_rules.py

@@ -13,6 +13,7 @@ from typing import Tuple
 # flake8: noqa
 from torch.onnx._internal.diagnostics import infra
 
+
 """
 GENERATED CODE - DO NOT EDIT DIRECTLY
 The purpose of generating a class for each rule is to override the `format_message`

torch/onnx/_internal/diagnostics/infra/__init__.py

@@ -14,6 +14,7 @@ from ._infra import (
 )
 from .context import Diagnostic, DiagnosticContext, RuntimeErrorWithDiagnostic
 
+
 __all__ = [
     "Diagnostic",
     "DiagnosticContext",

torch/onnx/_internal/diagnostics/infra/context.py

@@ -4,14 +4,10 @@
 from __future__ import annotations
 
 import contextlib
-
 import dataclasses
 import gzip
-
 import logging
-
 from typing import Callable, Generator, Generic, Literal, Mapping, TypeVar
-
 from typing_extensions import Self
 
 from torch.onnx._internal.diagnostics import infra

torch/onnx/_internal/diagnostics/infra/formatter.py

@@ -7,7 +7,6 @@ import traceback
 from typing import Any, Callable, Union
 
 from torch._logging import LazyString
-
 from torch.onnx._internal.diagnostics.infra import sarif
 
 

torch/onnx/_internal/diagnostics/infra/sarif/__init__.py

@@ -97,4 +97,5 @@ from torch.onnx._internal.diagnostics.infra.sarif._version_control_details impor
 from torch.onnx._internal.diagnostics.infra.sarif._web_request import WebRequest
 from torch.onnx._internal.diagnostics.infra.sarif._web_response import WebResponse
 
+
 # flake8: noqa

torch/onnx/_internal/diagnostics/infra/sarif/version.py

@@ -1,5 +1,6 @@
 from typing import Final
 
+
 SARIF_VERSION: Final = "2.1.0"
 SARIF_SCHEMA_LINK: Final = "https://docs.oasis-open.org/sarif/sarif/v2.1.0/cs01/schemas/sarif-schema-2.1.0.json"
 # flake8: noqa

torch/onnx/_internal/diagnostics/infra/utils.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 import functools
-
 import inspect
 import traceback
 from typing import Any, Callable, Mapping, Sequence

torch/onnx/_internal/exporter.py

@@ -4,12 +4,10 @@ from __future__ import (  # for onnx.ModelProto (ONNXProgram) and onnxruntime (O
 )
 
 import abc
-
 import contextlib
 import dataclasses
 import logging
 import os
-
 import tempfile
 import warnings
 from collections import defaultdict
@@ -27,11 +25,9 @@ from typing import (
 from typing_extensions import Self
 
 import torch
-
 import torch._ops
 import torch.export as torch_export
 import torch.utils._pytree as pytree
-
 from torch.onnx._internal import io_adapter
 from torch.onnx._internal.diagnostics import infra
 from torch.onnx._internal.fx import (
@@ -41,6 +37,7 @@ from torch.onnx._internal.fx import (
     serialization as fx_serialization,
 )
 
+
 # We can only import onnx from this module in a type-checking context to ensure that
 # 'import torch.onnx' continues to work without having 'onnx' installed. We fully
 # 'import onnx' inside of dynamo_export (by way of _assert_dependencies).
@@ -48,6 +45,7 @@ if TYPE_CHECKING:
     import io
 
     import onnx
+
     import onnxruntime  # type: ignore[import]
     import onnxscript  # type: ignore[import]
     from onnxscript.function_libs.torch_lib import (  # type: ignore[import]
@@ -55,7 +53,6 @@ if TYPE_CHECKING:
     )
 
     from torch._subclasses import fake_tensor
-
     from torch.onnx._internal.fx import diagnostics
 
 _DEFAULT_OPSET_VERSION: Final[int] = 18

torch/onnx/_internal/fx/_pass.py

@@ -2,23 +2,20 @@
 from __future__ import annotations
 
 import abc
-
 import contextlib
 import dataclasses
 import difflib
-
 import io
 import logging
 import sys
-
 from typing import Any, Callable, TYPE_CHECKING
 
 import torch
 import torch.fx
 from torch.fx.experimental.proxy_tensor import maybe_disable_fake_tensor_mode
-
 from torch.onnx._internal.fx import diagnostics, onnxfunction_dispatcher
 
+
 if TYPE_CHECKING:
     from torch._subclasses import fake_tensor
 

torch/onnx/_internal/fx/analysis/__init__.py

@@ -1,5 +1,6 @@
 from .unsupported_nodes import UnsupportedFxNodesAnalysis
 
+
 __all__ = [
     "UnsupportedFxNodesAnalysis",
 ]

torch/onnx/_internal/fx/decomposition_skip.py

@@ -15,7 +15,6 @@ from __future__ import annotations
 
 import abc
 import contextlib
-
 from typing import Callable, Sequence
 
 from onnxscript.function_libs.torch_lib.ops import (  # type: ignore[import-not-found]
@@ -26,6 +25,7 @@ from onnxscript.function_libs.torch_lib.ops import (  # type: ignore[import-not-
 import torch
 from torch._decomp import decompositions
 
+
 _NEW_OP_NAMESPACE: str = "onnx_export"
 """The namespace for the custom operator."""
 

torch/onnx/_internal/fx/decomposition_table.py

@@ -8,7 +8,6 @@ from typing import Callable
 import torch
 import torch._ops
 import torch.fx
-
 from torch.onnx._internal.fx import registration
 
 

torch/onnx/_internal/fx/diagnostics.py

@@ -2,9 +2,7 @@
 from __future__ import annotations
 
 import dataclasses
-
 import functools
-
 from typing import Any, TYPE_CHECKING
 
 import onnxscript  # type: ignore[import]
@@ -17,6 +15,7 @@ from torch.onnx._internal.diagnostics import infra
 from torch.onnx._internal.diagnostics.infra import decorator, formatter
 from torch.onnx._internal.fx import registration, type_utils as fx_type_utils
 
+
 if TYPE_CHECKING:
     import logging
 

torch/onnx/_internal/fx/fx_onnx_interpreter.py

@@ -16,7 +16,6 @@ from onnxscript.function_libs.torch_lib import (  # type: ignore[import]
 import torch
 import torch.fx
 from torch.onnx import _type_utils as jit_type_utils
-
 from torch.onnx._internal.fx import (
     _pass,
     diagnostics,

torch/onnx/_internal/fx/fx_symbolic_graph_extractor.py

@@ -2,16 +2,15 @@
 from __future__ import annotations
 
 import functools
-
 from typing import Any, Callable, Mapping, Sequence
 
 import torch
 import torch.fx
 import torch.onnx
-
 import torch.onnx._internal.fx.passes as passes
 from torch.onnx._internal import exporter, io_adapter
 
+
 # Functions directly wrapped to produce torch.fx.Proxy so that symbolic
 # data can flow through those functions. Python functions (e.g., `torch.arange`)
 # not defined by pybind11 in C++ do not go though Python dispatcher, so

torch/onnx/_internal/fx/onnxfunction_dispatcher.py

@@ -11,13 +11,13 @@ from typing import Any, Callable, Sequence, TYPE_CHECKING
 import torch
 import torch._ops
 import torch.fx
-
 from torch.onnx._internal.fx import (
     diagnostics,
     registration,
     type_utils as fx_type_utils,
 )
 
+
 if TYPE_CHECKING:
     import onnxscript  # type: ignore[import]
     from onnxscript.function_libs.torch_lib import (  # type: ignore[import]

torch/onnx/_internal/fx/op_validation.py

@@ -13,7 +13,6 @@ import torch
 import torch.fx
 from torch.fx.experimental import symbolic_shapes
 from torch.onnx import _constants, _type_utils as jit_type_utils
-
 from torch.onnx._internal.fx import (
     diagnostics,
     fx_onnx_interpreter,

torch/onnx/_internal/fx/passes/__init__.py

@@ -5,6 +5,7 @@ from .readability import RestoreParameterAndBufferNames
 from .type_promotion import InsertTypePromotion
 from .virtualization import MovePlaceholderToFront, ReplaceGetAttrWithPlaceholder
 
+
 __all__ = [
     "Decompose",
     "InsertTypePromotion",

torch/onnx/_internal/fx/passes/_utils.py

@@ -6,9 +6,7 @@ These functions should NOT be directly invoked outside of `passes` package.
 from __future__ import annotations
 
 import collections
-
 import re
-
 from typing import Callable
 
 import torch.fx

torch/onnx/_internal/fx/passes/decomp.py

@@ -2,7 +2,6 @@
 from __future__ import annotations
 
 import contextlib
-
 from typing import Callable, Mapping, TYPE_CHECKING
 
 import torch
@@ -12,6 +11,7 @@ from torch.fx.experimental import proxy_tensor
 from torch.onnx._internal.fx import _pass, diagnostics
 from torch.onnx._internal.fx.passes import _utils
 
+
 if TYPE_CHECKING:
     import torch.fx
     from torch._subclasses import fake_tensor

torch/onnx/_internal/fx/passes/functionalization.py

@@ -2,7 +2,6 @@
 from __future__ import annotations
 
 import contextlib
-
 from typing import Callable, TYPE_CHECKING
 
 import torch
@@ -14,6 +13,7 @@ from torch.onnx._internal.fx import _pass, diagnostics
 from torch.onnx._internal.fx.passes import _utils
 from torch.utils import _pytree as pytree
 
+
 if TYPE_CHECKING:
     from torch._subclasses import fake_tensor
 

torch/onnx/_internal/fx/passes/modularization.py

@@ -2,19 +2,17 @@
 from __future__ import annotations
 
 import abc
-
 import collections
 import copy
 import operator
-
 from typing import Any, Dict, Final, Generator, Iterator, Sequence, Tuple
 
 import torch
 import torch.fx
-
 from torch.onnx._internal.fx import _pass, diagnostics
 from torch.utils import _pytree as pytree
 
+
 _FX_TRACER_NN_MODULE_META_TYPE = Tuple[str, type]
 """Legacy type of item from `node.meta["nn_module_stack"].items()` produced by FX symbolic tracer."""
 _FX_TRACER_NN_MODULE_STACK_META_TYPE = collections.OrderedDict

torch/onnx/_internal/fx/passes/readability.py

@@ -4,7 +4,6 @@ from __future__ import annotations
 from typing import Sequence
 
 import torch
-
 from torch.onnx._internal.fx import _pass, diagnostics
 
 

torch/onnx/_internal/fx/passes/type_promotion.py

@@ -3,20 +3,16 @@
 from __future__ import annotations
 
 import abc
-
 import dataclasses
 import inspect
 import logging
-
 from typing import Any, Callable, Mapping, Sequence, TYPE_CHECKING
 
 import torch
 import torch._ops
 import torch.fx
 import torch.fx.traceback as fx_traceback
-
 from torch import _prims_common, _refs
-
 from torch._prims_common import (
     ELEMENTWISE_TYPE_PROMOTION_KIND,
     wrappers as _prims_common_wrappers,
@@ -24,15 +20,16 @@ from torch._prims_common import (
 from torch._refs import linalg as _linalg_refs, nn as _nn_refs, special as _special_refs
 from torch._refs.nn import functional as _functional_refs
 from torch.fx.experimental import proxy_tensor
-
 from torch.onnx._internal.fx import _pass, diagnostics, type_utils as fx_type_utils
 from torch.utils import _python_dispatch, _pytree
 
+
 if TYPE_CHECKING:
     from types import ModuleType
 
     from torch._subclasses import fake_tensor
 
+
 logger = logging.getLogger(__name__)
 
 # TODO(bowbao): move to type utils.

torch/onnx/_internal/fx/passes/virtualization.py

@@ -4,9 +4,9 @@ from __future__ import annotations
 from typing import TYPE_CHECKING
 
 import torch
-
 from torch.onnx._internal.fx import _pass
 
+
 if TYPE_CHECKING:
     import torch.fx
 

torch/onnx/_internal/fx/patcher.py

@@ -5,6 +5,7 @@ from typing import List, TYPE_CHECKING, Union
 
 import torch
 
+
 if TYPE_CHECKING:
     import io
 
@@ -16,7 +17,6 @@ def has_safetensors_and_transformers():
         # safetensors is not an exporter requirement, but needed for some huggingface models
         import safetensors  # type: ignore[import]  # noqa: F401
         import transformers  # type: ignore[import]  # noqa: F401
-
         from safetensors import torch as safetensors_torch  # noqa: F401
 
         return True

torch/onnx/_internal/fx/torch_export_graph_extractor.py

@@ -13,6 +13,7 @@ import torch.fx
 from torch.onnx._internal import exporter, io_adapter
 from torch.onnx._internal.diagnostics import infra
 
+
 if TYPE_CHECKING:
     import torch.onnx
     from torch.export.exported_program import ExportedProgram

torch/onnx/_internal/fx/type_utils.py

@@ -15,11 +15,13 @@ from typing import (
 )
 
 import numpy
+
 import onnx
 
 import torch
 from torch._subclasses import fake_tensor
 
+
 if TYPE_CHECKING:
     import onnx.defs.OpSchema.AttrType  # type: ignore[import]  # noqa: TCH004
 

torch/onnx/_internal/io_adapter.py

@@ -13,9 +13,9 @@ from typing import (
 
 import torch
 import torch.export as torch_export
-
 from torch.utils import _pytree as pytree
 
+
 if TYPE_CHECKING:
     import inspect
 

torch/onnx/_internal/jit_utils.py

@@ -1,10 +1,11 @@
 # mypy: allow-untyped-defs
 """Utilities for manipulating the torch.Graph object and the torchscript."""
-from __future__ import annotations
 
 # TODO(justinchuby): Move more of the symbolic helper functions here and expose
 # them to the user.
 
+from __future__ import annotations
+
 import dataclasses
 import re
 import typing

torch/onnx/_internal/onnxruntime.py

@@ -4,7 +4,6 @@ import dataclasses
 import importlib
 import logging
 import os
-
 from typing import (
     Any,
     Callable,
@@ -33,6 +32,7 @@ from torch.fx.passes.operator_support import OperatorSupport
 from torch.fx.passes.tools_common import CALLABLE_NODE_OPS
 from torch.utils import _pytree
 
+
 if TYPE_CHECKING:
     import onnx
 
@@ -929,7 +929,7 @@ class OrtBackend:
             try:
                 from onnxscript import optimizer  # type: ignore[import]
                 from onnxscript.rewriter import (  # type: ignore[import]
-                    onnxruntime as ort_rewriter,  # type: ignore[import]
+                    onnxruntime as ort_rewriter,
                 )
 
                 onnx_model = optimizer.optimize(onnx_model)
@@ -1112,7 +1112,6 @@ class OrtBackend:
         the ``compile`` method is invoked directly."""
         if self._options.use_aot_autograd:
             from functorch.compile import min_cut_rematerialization_partition
-
             from torch._dynamo.backends.common import aot_autograd
 
             return aot_autograd(

torch/onnx/_type_utils.py

@@ -10,6 +10,7 @@ import torch
 from torch._C import _onnx as _C_onnx
 from torch.onnx import errors
 
+
 if typing.TYPE_CHECKING:
     # Hack to help mypy to recognize torch._C.Value
     from torch import _C  # noqa: F401

torch/onnx/errors.py

@@ -7,6 +7,7 @@ from typing import TYPE_CHECKING
 from torch.onnx import _constants
 from torch.onnx._internal import diagnostics
 
+
 if TYPE_CHECKING:
     from torch import _C
 

torch/onnx/symbolic_helper.py

@@ -19,6 +19,7 @@ from torch.onnx import _constants, _type_utils, errors, utils
 from torch.onnx._globals import GLOBALS
 from torch.onnx._internal import jit_utils
 
+
 if typing.TYPE_CHECKING:
     from torch.types import Number
 

torch/onnx/symbolic_opset10.py

@@ -23,6 +23,7 @@ from torch.onnx import (
 from torch.onnx._globals import GLOBALS
 from torch.onnx._internal import jit_utils, registration
 
+
 # EDITING THIS FILE? READ THIS FIRST!
 # see Note [Edit Symbolic Files] in README.md
 

torch/onnx/symbolic_opset11.py

@@ -21,6 +21,7 @@ from torch.onnx import (
 )
 from torch.onnx._internal import jit_utils, registration
 
+
 # EDITING THIS FILE? READ THIS FIRST!
 # see Note [Edit Symbolic Files] in README.md
 

torch/onnx/symbolic_opset14.py

@@ -25,6 +25,7 @@ from torch.onnx import _constants, _type_utils, symbolic_helper
 from torch.onnx._globals import GLOBALS
 from torch.onnx._internal import jit_utils, registration
 
+
 __all__ = [
     "hardswish",
     "tril",

torch/onnx/symbolic_opset15.py

@@ -33,6 +33,7 @@ from torch import _C
 from torch.onnx import symbolic_helper, symbolic_opset9 as opset9
 from torch.onnx._internal import jit_utils, registration
 
+
 _onnx_symbolic = functools.partial(registration.onnx_symbolic, opset=15)
 
 

torch/onnx/symbolic_opset16.py

@@ -36,6 +36,7 @@ from torch.nn.functional import (
 from torch.onnx import _type_utils, errors, symbolic_helper, utils
 from torch.onnx._internal import jit_utils, registration
 
+
 _onnx_symbolic = functools.partial(registration.onnx_symbolic, opset=16)
 
 

torch/onnx/symbolic_opset17.py

@@ -25,6 +25,7 @@ from torch import _C
 from torch.onnx import _type_utils, errors, symbolic_helper
 from torch.onnx._internal import jit_utils, registration
 
+
 # EDITING THIS FILE? READ THIS FIRST!
 # see Note [Edit Symbolic Files] in README.md
 

torch/onnx/symbolic_opset18.py

@@ -27,6 +27,7 @@ from torch import _C
 from torch.onnx import _type_utils, symbolic_helper, symbolic_opset9 as opset9
 from torch.onnx._internal import jit_utils, registration
 
+
 # EDITING THIS FILE? READ THIS FIRST!
 # see Note [Edit Symbolic Files] in symbolic_helper.py
 

torch/onnx/symbolic_opset19.py

@@ -26,6 +26,7 @@ Size
 
 from typing import List
 
+
 # EDITING THIS FILE? READ THIS FIRST!
 # see Note [Edit Symbolic Files] in symbolic_helper.py
 

torch/onnx/symbolic_opset20.py

@@ -24,11 +24,11 @@ New operators:
 import functools
 
 import torch.nn.functional as F
-
 from torch import _C
 from torch.onnx import symbolic_helper
 from torch.onnx._internal import jit_utils, registration
 
+
 # EDITING THIS FILE? READ THIS FIRST!
 # see Note [Edit Symbolic Files] in symbolic_helper.py
 

torch/onnx/symbolic_opset8.py

@@ -39,6 +39,7 @@ from torch._C import _onnx as _C_onnx
 from torch.onnx import _type_utils, errors, symbolic_helper, symbolic_opset9 as opset9
 from torch.onnx._internal import jit_utils, registration
 
+
 _onnx_symbolic = functools.partial(registration.onnx_symbolic, opset=8)
 
 block_listed_operators = (

torch/onnx/symbolic_opset9.py

@@ -27,6 +27,7 @@ from torch.onnx import _constants, _deprecation, _type_utils, errors, symbolic_h
 from torch.onnx._globals import GLOBALS
 from torch.onnx._internal import jit_utils, registration
 
+
 if TYPE_CHECKING:
     from torch.types import Number
 

torch/onnx/verification.py

@@ -30,6 +30,7 @@ from torch.onnx._globals import GLOBALS
 from torch.onnx._internal import onnx_proto_utils
 from torch.types import Number
 
+
 _ORT_PROVIDERS = ("CPUExecutionProvider",)
 
 _NumericType = Union[Number, torch.Tensor, np.ndarray]

torch/optim/__init__.py

@@ -23,6 +23,7 @@ from torch.optim.rprop import Rprop
 from torch.optim.sgd import SGD
 from torch.optim.sparse_adam import SparseAdam
 
+
 Adafactor.__module__ = "torch.optim"
 
 

torch/optim/_adafactor.py

@@ -4,6 +4,7 @@ from typing import List, Optional, Tuple, Union
 
 import torch
 from torch import Tensor
+
 from .optimizer import (
     _disable_dynamo_if_unsupported,
     _get_scalar_dtype,
@@ -12,6 +13,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["Adafactor", "adafactor"]
 
 

torch/optim/adadelta.py

@@ -20,6 +20,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["Adadelta", "adadelta"]
 
 

torch/optim/adagrad.py

@@ -4,6 +4,7 @@ from typing import List, Optional, Union
 import torch
 from torch import Tensor
 from torch.utils._foreach_utils import _get_fused_kernels_supported_devices
+
 from .optimizer import (
     _default_to_fused_or_foreach,
     _differentiable_doc,
@@ -17,6 +18,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["Adagrad", "adagrad"]
 
 

torch/optim/adam.py

@@ -5,6 +5,7 @@ from typing import List, Optional, Tuple, Union
 import torch
 from torch import Tensor
 from torch.utils._foreach_utils import _get_fused_kernels_supported_devices
+
 from .optimizer import (
     _capturable_doc,
     _default_to_fused_or_foreach,
@@ -24,6 +25,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["Adam", "adam"]
 
 

torch/optim/adamax.py

@@ -21,6 +21,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["Adamax", "adamax"]
 
 

torch/optim/adamw.py

@@ -5,6 +5,7 @@ from typing import cast, List, Optional, Tuple, Union
 import torch
 from torch import Tensor
 from torch.utils._foreach_utils import _get_fused_kernels_supported_devices
+
 from .optimizer import (
     _capturable_doc,
     _default_to_fused_or_foreach,
@@ -24,6 +25,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["AdamW", "adamw"]
 
 

torch/optim/asgd.py

@@ -21,6 +21,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["ASGD", "asgd"]
 
 

torch/optim/lbfgs.py

@@ -3,8 +3,10 @@ from typing import Optional, Union
 
 import torch
 from torch import Tensor
+
 from .optimizer import Optimizer, ParamsT
 
+
 __all__ = ["LBFGS"]
 
 

torch/optim/lr_scheduler.py

@@ -26,6 +26,7 @@ from torch import inf, Tensor
 
 from .optimizer import Optimizer
 
+
 __all__ = [
     "LambdaLR",
     "MultiplicativeLR",

torch/optim/nadam.py

@@ -5,6 +5,7 @@ from typing import cast, List, Optional, Tuple, Union
 
 import torch
 from torch import Tensor
+
 from .optimizer import (
     _capturable_doc,
     _default_to_fused_or_foreach,
@@ -22,6 +23,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["NAdam", "nadam"]
 
 

torch/optim/optimizer.py

@@ -35,6 +35,7 @@ from torch.utils._foreach_utils import (
 )
 from torch.utils.hooks import RemovableHandle
 
+
 Args: TypeAlias = Tuple[Any, ...]
 Kwargs: TypeAlias = Dict[str, Any]
 StateDict: TypeAlias = Dict[str, Any]

torch/optim/radam.py

@@ -22,6 +22,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["RAdam", "radam"]
 
 

torch/optim/rmsprop.py

@@ -5,6 +5,7 @@ from typing import List, Optional, Union
 
 import torch
 from torch import Tensor
+
 from .optimizer import (
     _capturable_doc,
     _default_to_fused_or_foreach,
@@ -20,6 +21,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["RMSprop", "rmsprop"]
 
 

torch/optim/rprop.py

@@ -5,6 +5,7 @@ from typing import List, Optional, Tuple, Union
 
 import torch
 from torch import Tensor
+
 from .optimizer import (
     _capturable_doc,
     _default_to_fused_or_foreach,
@@ -20,6 +21,7 @@ from .optimizer import (
     ParamsT,
 )
 
+
 __all__ = ["Rprop", "rprop"]
 
 

torch/optim/sgd.py

@@ -5,6 +5,7 @@ from typing import List, Optional, Union
 import torch
 from torch import Tensor
 from torch.utils._foreach_utils import _get_fused_kernels_supported_devices
+
 from .optimizer import (
     _default_to_fused_or_foreach,
     _differentiable_doc,
@@ -16,6 +17,7 @@ from .optimizer import (
     Optimizer,
 )
 
+
 __all__ = ["SGD", "sgd"]
 
 

torch/optim/sparse_adam.py

@@ -3,9 +3,11 @@ from typing import List, Tuple, Union
 
 import torch
 from torch import Tensor
+
 from . import _functional as F
 from .optimizer import _maximize_doc, Optimizer, ParamsT
 
+
 __all__ = ["SparseAdam"]
 
 

torch/optim/swa_utils.py

@@ -11,8 +11,10 @@ from torch import Tensor
 from torch.nn import Module
 from torch.optim.lr_scheduler import _format_param, LRScheduler
 from torch.utils._foreach_utils import _get_foreach_kernels_supported_devices
+
 from .optimizer import Optimizer
 
+
 __all__ = [
     "AveragedModel",
     "update_bn",
@@ -25,6 +27,7 @@ __all__ = [
 
 from torch.utils._foreach_utils import _group_tensors_by_device_and_dtype
 
+
 PARAM_LIST = Union[Tuple[Tensor, ...], List[Tensor]]
 
 

torch/package/_directory_reader.py

@@ -6,6 +6,7 @@ from typing import cast
 import torch
 from torch.types import Storage
 
+
 __serialization_id_record_name__ = ".data/serialization_id"
 
 

torch/package/_importlib.py

@@ -2,6 +2,7 @@
 import _warnings
 import os.path
 
+
 # note: implementations
 # copied from cpython's import code
 

torch/package/_mangling.py

@@ -4,6 +4,7 @@ See mangling.md for details.
 """
 import re
 
+
 _mangle_index = 0
 
 

torch/package/analyze/find_first_use_of_broken_modules.py

@@ -1,6 +1,7 @@
 from typing import Dict, List
 
-from ..package_exporter import PackagingError
+from torch.package.package_exporter import PackagingError
+
 
 __all__ = ["find_first_use_of_broken_modules"]
 

torch/package/analyze/trace_dependencies.py

@@ -2,6 +2,7 @@
 import sys
 from typing import Any, Callable, Iterable, List, Tuple
 
+
 __all__ = ["trace_dependencies"]
 
 

torch/package/file_structure_representation.py

@@ -3,6 +3,7 @@ from typing import Dict, List
 
 from .glob_group import GlobGroup, GlobPattern
 
+
 __all__ = ["Directory"]
 
 

torch/package/glob_group.py

@@ -2,6 +2,7 @@
 import re
 from typing import Iterable, Union
 
+
 GlobPattern = Union[str, Iterable[str]]
 
 

torch/package/importer.py

@@ -1,7 +1,7 @@
 # mypy: allow-untyped-defs
 import importlib
 from abc import ABC, abstractmethod
-from pickle import (  # type: ignore[attr-defined]  # type: ignore[attr-defined]
+from pickle import (  # type: ignore[attr-defined]
     _getattribute,
     _Pickler,
     whichmodule as _pickle_whichmodule,
@@ -11,6 +11,7 @@ from typing import Any, Dict, List, Optional, Tuple
 
 from ._mangling import demangle, get_mangle_prefix, is_mangled
 
+
 __all__ = ["ObjNotFoundError", "ObjMismatchError", "Importer", "OrderedImporter"]
 
 

torch/package/package_exporter.py

@@ -39,6 +39,7 @@ from .find_file_dependencies import find_files_source_depends_on
 from .glob_group import GlobGroup, GlobPattern
 from .importer import Importer, OrderedImporter, sys_importer
 
+
 __all__ = [
     "PackagingErrorReason",
     "EmptyMatchError",

torch/package/package_importer.py

@@ -38,6 +38,7 @@ from ._package_unpickler import PackageUnpickler
 from .file_structure_representation import _create_directory_from_file_list, Directory
 from .importer import Importer
 
+
 if TYPE_CHECKING:
     from .glob_group import GlobPattern
 

torch/profiler/__init__.py

@@ -25,6 +25,7 @@ from .profiler import (
     tensorboard_trace_handler,
 )
 
+
 __all__ = [
     "profile",
     "schedule",

torch/profiler/_memory_profiler.py

@@ -32,6 +32,7 @@ from torch._C._profiler import (
 from torch._utils import _element_size
 from torch.profiler import _utils
 
+
 KeyAndID = Tuple["Key", int]
 TensorAndID = Tuple["TensorKey", int]
 

torch/profiler/_utils.py

@@ -7,9 +7,9 @@ from dataclasses import dataclass
 from typing import Dict, List, TYPE_CHECKING
 
 from torch.autograd.profiler import profile
-
 from torch.profiler import DeviceType
 
+
 if TYPE_CHECKING:
     from torch.autograd import _KinetoEvent
 

torch/profiler/itt.py

@@ -1,6 +1,7 @@
 # mypy: allow-untyped-defs
 from contextlib import contextmanager
 
+
 try:
     from torch._C import _itt
 except ImportError:

torch/quantization/__init__.py

@@ -1,16 +1,14 @@
 # mypy: allow-untyped-defs
-from .quantize import *  # noqa: F403
-from .observer import *  # noqa: F403
-from .qconfig import *  # noqa: F403
 from .fake_quantize import *  # noqa: F403
 from .fuse_modules import fuse_modules
-from .stubs import *  # noqa: F403
-from .quant_type import *  # noqa: F403
-from .quantize_jit import *  # noqa: F403
-
-# from .quantize_fx import *
-from .quantization_mappings import *  # noqa: F403
 from .fuser_method_mappings import *  # noqa: F403
+from .observer import *  # noqa: F403
+from .qconfig import *  # noqa: F403
+from .quant_type import *  # noqa: F403
+from .quantization_mappings import *  # noqa: F403
+from .quantize import *  # noqa: F403
+from .quantize_jit import *  # noqa: F403
+from .stubs import *  # noqa: F403
 
 
 def default_eval_fn(model, calib_data):

torch/quantization/fx/pattern_utils.py

@@ -15,6 +15,7 @@ from torch.ao.quantization.fx.pattern_utils import (
     QuantizeHandler,
 )
 
+
 # QuantizeHandler.__module__ = _NAMESPACE
 _register_fusion_pattern.__module__ = "torch.ao.quantization.fx.pattern_utils"
 get_default_fusion_patterns.__module__ = "torch.ao.quantization.fx.pattern_utils"

torch/quantization/fx/quantization_patterns.py

@@ -23,6 +23,7 @@ from torch.ao.quantization.fx.quantize_handler import (
     StandaloneModuleQuantizeHandler,
 )
 
+
 QuantizeHandler.__module__ = "torch.ao.quantization.fx.quantization_patterns"
 BinaryOpQuantizeHandler.__module__ = "torch.ao.quantization.fx.quantization_patterns"
 CatQuantizeHandler.__module__ = "torch.ao.quantization.fx.quantization_patterns"

torch/sparse/__init__.py

@@ -15,6 +15,7 @@ from .semi_structured import (
     to_sparse_semi_structured,
 )
 
+
 if TYPE_CHECKING:
     from torch.types import _dtype as DType
 

torch/sparse/_semi_structured_ops.py

@@ -3,6 +3,7 @@ import contextlib
 
 import torch
 
+
 __all__ = [
     "fallback_dispatcher",
     "semi_sparse_values",

torch/sparse/_triton_ops.py

@@ -8,8 +8,10 @@ from typing import Optional, Tuple
 
 import torch
 from torch.utils._triton import has_triton
+
 from ._triton_ops_meta import get_meta
 
+
 TORCH_SPARSE_BSR_SCATTER_MM_LRU_CACHE_SIZE = int(
     os.getenv("TORCH_SPARSE_BSR_SCATTER_MM_LRU_CACHE_SIZE", 2)
 )

torch/sparse/semi_structured.py

@@ -20,6 +20,7 @@ from torch.sparse._semi_structured_ops import (
     semi_sparse_view,
 )
 
+
 __all__ = [
     "SparseSemiStructuredTensor",
     "SparseSemiStructuredTensorCUTLASS",

torch/testing/__init__.py

@@ -1,4 +1,5 @@
 from torch._C import FileCheck as FileCheck
+
 from . import _utils
 from ._comparison import assert_allclose, assert_close as assert_close
 from ._creation import make_tensor as make_tensor

torch/testing/_creation.py

@@ -9,6 +9,7 @@ from typing import cast, List, Optional, Tuple, Union
 
 import torch
 
+
 _INTEGRAL_TYPES = [
     torch.uint8,
     torch.int8,

torch/testing/_internal/distributed/common_state_dict.py

@@ -8,7 +8,6 @@ from typing import Any, Dict
 
 import torch
 import torch.nn as nn
-
 from torch.distributed._sharded_tensor import ShardedTensor
 from torch.distributed._state_dict_utils import _gather_state_dict
 from torch.distributed._tensor import DTensor

torch/testing/_internal/dynamo_test_failures.py

@@ -3,6 +3,7 @@ import logging
 import os
 import sys
 
+
 # NOTE: [dynamo_test_failures.py]
 #
 # We generate xFailIfTorchDynamo* for all tests in `dynamo_expected_failures`

torch/testing/_internal/opinfo/core.py

@@ -34,9 +34,9 @@ from torch.testing._internal.common_utils import (
     TrackedInputIter,
 )
 from torch.testing._internal.opinfo import utils
-
 from torchgen.utils import dataclass_repr
 
+
 # Reasonable testing sizes for dimensions
 L = 20
 M = 10

torch/testing/_internal/opinfo/definitions/__init__.py

@@ -11,6 +11,7 @@ from torch.testing._internal.opinfo.definitions import (
     special,
 )
 
+
 # Operator database
 op_db: List[OpInfo] = [
     *fft.op_db,

torch/testing/_internal/opinfo/definitions/fft.py

@@ -7,7 +7,6 @@ from typing import List
 import numpy as np
 
 import torch
-
 from torch.testing import make_tensor
 from torch.testing._internal.common_cuda import SM53OrLater
 from torch.testing._internal.common_device_type import precisionOverride
@@ -31,6 +30,7 @@ from torch.testing._internal.opinfo.refs import (
     PythonRefInfo,
 )
 
+
 has_scipy_fft = False
 if TEST_SCIPY:
     try:

torch/testing/_internal/opinfo/definitions/linalg.py

@@ -11,7 +11,6 @@ import numpy as np
 from numpy import inf
 
 import torch
-
 from torch.testing import make_tensor
 from torch.testing._internal.common_cuda import (
     _get_magma_version,

torch/testing/_internal/opinfo/definitions/signal.py

@@ -2,7 +2,6 @@
 
 import unittest
 from functools import partial
-
 from itertools import product
 from typing import Callable, List, Tuple
 
@@ -18,6 +17,7 @@ from torch.testing._internal.opinfo.core import (
     SampleInput,
 )
 
+
 if TEST_SCIPY:
     import scipy.signal
 

torch/testing/_internal/opinfo/refs.py

@@ -7,6 +7,7 @@ from torch.testing._internal.opinfo.core import (
     UnaryUfuncInfo,
 )
 
+
 # NOTE [Python References]
 # Python References emulate existing PyTorch operations, but can ultimately
 #   be expressed in terms of "primitive" operations from torch._prims.