[BE][Easy] eliminate relative import in torchgen (#128872)

Fix generated by:

```bash
ruff check --config 'lint.flake8-tidy-imports.ban-relative-imports="all"' --fix --select=TID $(fd '.pyi?$' torchgen)
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/128872
Approved by: https://github.com/zou3519

torchgen/api/autograd.py

@@ -3,7 +3,6 @@ from dataclasses import dataclass
 from typing import cast, Dict, List, Match, Optional, Sequence, Set, Tuple
 
 from torchgen import local
-
 from torchgen.api import cpp
 from torchgen.api.types import BaseCType, Binding, NamedCType, tensorListT
 from torchgen.model import (

torchgen/api/cpp.py

@@ -48,6 +48,7 @@ from torchgen.model import (
 )
 from torchgen.utils import assert_never
 
+
 # This file describes the translation of JIT schema to the public C++
 # API, which is what people use when they call functions like at::add.
 #

torchgen/api/dispatcher.py

@@ -2,7 +2,6 @@ import itertools
 from typing import List, Sequence, Union
 
 from torchgen.api import cpp
-
 from torchgen.api.types import ArgName, Binding, CType, NamedCType
 from torchgen.model import (
     Argument,
@@ -14,6 +13,7 @@ from torchgen.model import (
 )
 from torchgen.utils import assert_never, concatMap
 
+
 # This file describes the translation of JIT schema to the dispatcher
 # API, the *unboxed* calling convention by which invocations through
 # the dispatcher are made.  Historically, the dispatcher API matched

torchgen/api/lazy.py

@@ -20,7 +20,6 @@ from torchgen.api.types import (
     SymIntT,
     VectorCType,
 )
-
 from torchgen.model import (
     Argument,
     BaseTy,

torchgen/api/meta.py

@@ -1,5 +1,6 @@
 from torchgen.model import NativeFunctionsGroup
 
+
 # Follows dispatcher calling convention, but:
 #   - Mutable arguments not allowed.  Meta functions are always
 #     written in functional form.  Look at FunctionSchema.signature()

torchgen/api/native.py

@@ -2,7 +2,6 @@ from typing import List, Optional, Sequence, Union
 
 from torchgen import local
 from torchgen.api import cpp
-
 from torchgen.api.types import (
     ArgName,
     BaseCType,
@@ -30,6 +29,7 @@ from torchgen.model import (
 )
 from torchgen.utils import assert_never
 
+
 # This file describes the translation of JIT schema to the native functions API.
 # This looks a lot like the C++ API (which makes historical sense, because the
 # idea was you wrote native functions to implement functions in the C++ API),

torchgen/api/python.py

@@ -17,6 +17,7 @@ from torchgen.model import (
     Variant,
 )
 
+
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #
 #
 #                           Data Models

torchgen/api/structured.py

@@ -1,7 +1,6 @@
 from typing import List, Union
 
 from torchgen.api import cpp
-
 from torchgen.api.types import (
     ArgName,
     ArrayRefCType,
@@ -33,6 +32,7 @@ from torchgen.model import (
 )
 from torchgen.utils import assert_never
 
+
 # This file describes the translation of JIT schema to the structured functions API.
 # This is similar to native API, but a number of historical problems with native
 # API have been fixed.

torchgen/api/translate.py

@@ -33,6 +33,7 @@ from torchgen.api.types import (
     VectorCType,
 )
 
+
 # This file implements a small program synthesis engine that implements
 # conversions between one API to another.
 #

torchgen/api/types/__init__.py

@@ -1,3 +1,3 @@
-from .types import *
-from .types_base import *
-from .signatures import *  # isort:skip
+from torchgen.api.types.types import *
+from torchgen.api.types.types_base import *
+from torchgen.api.types.signatures import *  # usort:skip

torchgen/api/types/signatures.py

@@ -1,7 +1,7 @@
 from dataclasses import dataclass
-
 from typing import Iterator, List, Optional, Sequence, Set, Tuple, Union
 
+from torchgen.api.types.types_base import Binding, CType, Expr
 from torchgen.model import (
     BackendIndex,
     FunctionSchema,
@@ -10,8 +10,6 @@ from torchgen.model import (
     NativeFunctionsViewGroup,
 )
 
-from .types_base import Binding, CType, Expr
-
 
 @dataclass(frozen=True)
 class CppSignature:

torchgen/api/types/types.py

@@ -15,9 +15,7 @@ Add new types to `types_base.py` if they are basic and not attached to ATen/c10.
 from dataclasses import dataclass
 from typing import Dict
 
-from torchgen.model import BaseTy, ScalarType
-
-from .types_base import (
+from torchgen.api.types.types_base import (
     BaseCppType,
     BaseCType,
     boolT,
@@ -30,6 +28,7 @@ from .types_base import (
     longT,
     shortT,
 )
+from torchgen.model import BaseTy, ScalarType
 
 
 TENSOR_LIST_LIKE_CTYPES = [

torchgen/api/types/types_base.py

@@ -19,6 +19,7 @@ from typing import List, Optional, Union
 
 from torchgen.model import Argument, SelfArgument, TensorOptionsArguments
 
+
 # An ArgName is just the str name of the argument in schema;
 # but in some special circumstances, we may add a little extra
 # context.  The Enum SpecialArgName covers all of these cases;

torchgen/api/ufunc.py

@@ -2,7 +2,6 @@ from dataclasses import dataclass
 from typing import List, Optional
 
 import torchgen.api.types as api_types
-
 from torchgen.api import cpp, structured
 from torchgen.api.types import (
     ArgName,

torchgen/api/unboxing.py

@@ -12,6 +12,7 @@ from torchgen.model import (
     Type,
 )
 
+
 # This file generates the code for unboxing wrappers, i.e., the glue logic to unbox a boxed operator and convert the
 # ivalues from stack to correct arguments to the unboxed kernel, based on corresponding JIT schema. This codegen is
 # an alternative way to generate unboxing wrappers similar to the existing C++ metaprogramming approach but gets the

torchgen/code_template.py

@@ -1,6 +1,7 @@
 import re
 from typing import Mapping, Match, Optional, Sequence
 
+
 # match $identifier or ${identifier} and replace with value in env
 # If this identifier is at the beginning of whitespace on a line
 # and its value is a list then it is treated as

torchgen/context.py

@@ -1,5 +1,4 @@
 import contextlib
-
 import functools
 from typing import Any, Callable, Dict, Iterator, List, Optional, Tuple, TypeVar, Union
 
@@ -13,6 +12,7 @@ from torchgen.model import (
 )
 from torchgen.utils import context, S, T
 
+
 # Helper functions for defining generators on things in the model
 
 F = TypeVar(

torchgen/decompositions/gen_jit_decompositions.py

@@ -4,6 +4,7 @@ from pathlib import Path
 
 from torch.jit._decompositions import decomposition_table
 
+
 # from torchgen.code_template import CodeTemplate
 
 DECOMP_HEADER = r"""

torchgen/dest/__init__.py

@@ -1,18 +1,18 @@
-from .lazy_ir import (
+from torchgen.dest.lazy_ir import (
     generate_non_native_lazy_ir_nodes as generate_non_native_lazy_ir_nodes,
     GenLazyIR as GenLazyIR,
     GenLazyNativeFuncDefinition as GenLazyNativeFuncDefinition,
     GenLazyShapeInferenceDefinition as GenLazyShapeInferenceDefinition,
 )
-from .native_functions import (
+from torchgen.dest.native_functions import (
     compute_native_function_declaration as compute_native_function_declaration,
 )
-from .register_dispatch_key import (
+from torchgen.dest.register_dispatch_key import (
     gen_registration_headers as gen_registration_headers,
     gen_registration_helpers as gen_registration_helpers,
     RegisterDispatchKey as RegisterDispatchKey,
 )
-from .ufunc import (
+from torchgen.dest.ufunc import (
     compute_ufunc_cpu as compute_ufunc_cpu,
     compute_ufunc_cpu_kernel as compute_ufunc_cpu_kernel,
     compute_ufunc_cuda as compute_ufunc_cuda,

torchgen/dest/native_functions.py

@@ -3,7 +3,6 @@ from typing import List, Optional, Union
 import torchgen.api.meta as meta
 import torchgen.api.structured as structured
 from torchgen.api.types import kernel_signature
-
 from torchgen.context import with_native_function_and_index
 from torchgen.model import BackendIndex, NativeFunction, NativeFunctionsGroup
 from torchgen.utils import mapMaybe

torchgen/dest/ufunc.py

@@ -27,6 +27,7 @@ from torchgen.model import (
 )
 from torchgen.utils import OrderedSet
 
+
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #
 #
 #                                  CUDA STUFF

torchgen/executorch/api/custom_ops.py

@@ -1,12 +1,11 @@
 from collections import defaultdict
-
 from dataclasses import dataclass
 from typing import Dict, List, Optional, Sequence, Tuple
 
 from torchgen import dest
 
 # disable import sorting to avoid circular dependency.
-from torchgen.api.types import DispatcherSignature  # isort:skip
+from torchgen.api.types import DispatcherSignature  # usort:skip
 from torchgen.context import method_with_native_function
 from torchgen.executorch.model import ETKernelIndex
 from torchgen.model import BaseTy, BaseType, DispatchKey, NativeFunction, Variant

torchgen/executorch/api/et_cpp.py

@@ -15,6 +15,14 @@ from torchgen.api.types import (
     VectorCType,
     voidT,
 )
+from torchgen.executorch.api.types import (
+    ArrayRefCType,
+    BaseTypeToCppMapping,
+    OptionalCType,
+    scalarT,
+    tensorListT,
+    tensorT,
+)
 from torchgen.model import (
     Argument,
     Arguments,
@@ -29,14 +37,7 @@ from torchgen.model import (
     Type,
 )
 from torchgen.utils import assert_never
-from .types import (
-    ArrayRefCType,
-    BaseTypeToCppMapping,
-    OptionalCType,
-    scalarT,
-    tensorListT,
-    tensorT,
-)
+
 
 """
 This file describes the translation of JIT schema to the public C++ API, which is what people use when they call

torchgen/executorch/api/types/__init__.py

@@ -1,2 +1,2 @@
-from .types import *
-from .signatures import *  # isort:skip
+from torchgen.executorch.api.types.types import *
+from torchgen.executorch.api.types.signatures import *  # usort:skip

torchgen/executorch/api/types/signatures.py

@@ -2,12 +2,10 @@ from dataclasses import dataclass
 from typing import List, Optional, Set
 
 import torchgen.api.cpp as aten_cpp
-
 from torchgen.api.types import Binding, CType
+from torchgen.executorch.api.types.types import contextArg
 from torchgen.model import FunctionSchema, NativeFunction
 
-from .types import contextArg
-
 
 @dataclass(frozen=True)
 class ExecutorchCppSignature:

torchgen/executorch/api/types/types.py

@@ -15,6 +15,7 @@ from torchgen.api.types import (
 )
 from torchgen.model import BaseTy
 
+
 halfT = BaseCppType("torch::executor", "Half")
 bfloat16T = BaseCppType("torch::executor", "BFloat16")
 stringT = BaseCppType("torch::executor", "string_view")

torchgen/executorch/api/unboxing.py

@@ -12,6 +12,7 @@ from torchgen.model import (
     Type,
 )
 
+
 connector = "\n\t"
 
 

torchgen/executorch/model.py

@@ -17,6 +17,7 @@ from torchgen.model import (
 )
 from torchgen.utils import assert_never
 
+
 KERNEL_KEY_VERSION = 1
 
 

torchgen/executorch/parse.py

@@ -4,7 +4,6 @@ from typing import Any, Dict, List, Optional, Set, Tuple
 import yaml
 
 from torchgen.executorch.model import ETKernelIndex, ETKernelKey
-
 from torchgen.gen import LineLoader, parse_native_yaml
 from torchgen.model import (
     BackendMetadata,
@@ -15,6 +14,7 @@ from torchgen.model import (
 )
 from torchgen.utils import NamespaceHelper
 
+
 # Parse native_functions.yaml into a sequence of NativeFunctions and ET Backend Indices.
 ETParsedYaml = namedtuple("ETParsedYaml", ["native_functions", "et_kernel_indices"])
 

torchgen/fuse/gen_patterns.py

@@ -4,6 +4,7 @@ import os
 from torch._inductor import pattern_matcher
 from torch._inductor.fx_passes import joint_graph
 
+
 if __name__ == "__main__":
     # Start by deleting all the existing patterns.
     for file in os.listdir(pattern_matcher.SERIALIZED_PATTERN_PATH):

torchgen/gen.py

@@ -3,7 +3,6 @@ import functools
 import json
 import os
 import pathlib
-
 from collections import defaultdict, namedtuple, OrderedDict
 from dataclasses import dataclass, field
 from typing import (
@@ -27,7 +26,6 @@ import torchgen.api.meta as meta
 import torchgen.api.native as native
 import torchgen.api.structured as structured
 import torchgen.dest as dest
-
 from torchgen.aoti.fallback_ops import inductor_fallback_ops
 from torchgen.api import cpp
 from torchgen.api.translate import translate
@@ -59,7 +57,6 @@ from torchgen.gen_functionalization_type import (
     GenCompositeViewCopyKernel,
 )
 from torchgen.gen_vmap_plumbing import gen_all_vmap_plumbing
-
 from torchgen.model import (
     Argument,
     BackendIndex,
@@ -105,6 +102,7 @@ from torchgen.utils import (
 )
 from torchgen.yaml_utils import YamlDumper, YamlLoader
 
+
 T = TypeVar("T")
 
 # Welcome to the ATen code generator v2!  The ATen code generator is

torchgen/gen_aoti_c_shim.py

@@ -4,7 +4,6 @@ from typing import Dict, List, Optional, Sequence, Tuple, Union
 
 from torchgen.api.types import DispatcherSignature
 from torchgen.api.types.signatures import CppSignature, CppSignatureGroup
-
 from torchgen.context import method_with_native_function
 from torchgen.model import (
     Argument,
@@ -22,6 +21,7 @@ from torchgen.model import (
 )
 from torchgen.utils import mapMaybe
 
+
 base_type_to_c_type = {
     BaseTy.Tensor: "AtenTensorHandle",
     BaseTy.bool: "int32_t",  # Use int to pass bool

torchgen/gen_functionalization_type.py

@@ -46,7 +46,6 @@ from torchgen.native_function_generation import (
     MUTABLE_OPS_THAT_CANNOT_GET_AN_OUT_VARIANT,
     OUT_OPS_THAT_DONT_GET_GROUPED_PROPERLY,
 )
-
 from torchgen.selective_build.selector import SelectiveBuilder
 from torchgen.utils import dataclass_repr
 

torchgen/gen_lazy_tensor.py

@@ -18,22 +18,21 @@ from typing import (
 import yaml
 
 import torchgen.dest as dest
-
 from torchgen.api.lazy import setValueT
 from torchgen.api.types import BaseCppType
 from torchgen.dest.lazy_ir import GenLazyIR, GenLazyNativeFuncDefinition, GenTSLazyIR
 from torchgen.gen import get_grouped_native_functions, parse_native_yaml
-
-from torchgen.model import NativeFunction, NativeFunctionsGroup, OperatorName
-from torchgen.selective_build.selector import SelectiveBuilder
-from torchgen.utils import FileManager, NamespaceHelper
-from torchgen.yaml_utils import YamlLoader
-from .gen_backend_stubs import (
+from torchgen.gen_backend_stubs import (
     error_on_missing_kernels,
     gen_dispatcher_registrations,
     gen_dispatchkey_nativefunc_headers,
     parse_backend_yaml,
 )
+from torchgen.model import NativeFunction, NativeFunctionsGroup, OperatorName
+from torchgen.selective_build.selector import SelectiveBuilder
+from torchgen.utils import FileManager, NamespaceHelper
+from torchgen.yaml_utils import YamlLoader
+
 
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #
 #

torchgen/local.py

@@ -2,6 +2,7 @@ import threading
 from contextlib import contextmanager
 from typing import Iterator, Optional
 
+
 # Simple dynamic scoping implementation.  The name "parametrize" comes
 # from Racket.
 #

torchgen/model.py

@@ -1,13 +1,13 @@
 import dataclasses
 import itertools
 import re
-
 from dataclasses import dataclass
 from enum import auto, Enum
 from typing import Callable, Dict, Iterator, List, Optional, Sequence, Set, Tuple, Union
 
 from torchgen.utils import assert_never, NamespaceHelper, OrderedSet
 
+
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #
 #
 #                           DATA MODEL

torchgen/native_function_generation.py

@@ -1,5 +1,4 @@
 from collections import defaultdict
-
 from typing import Dict, List, Optional, Sequence, Tuple, Union
 
 import torchgen.api.dispatcher as dispatcher
@@ -27,6 +26,7 @@ from torchgen.model import (
 )
 from torchgen.utils import concatMap
 
+
 # See Note: [Out ops with functional variants that don't get grouped properly]
 OUT_OPS_THAT_DONT_GET_GROUPED_PROPERLY = [
     # This has a functional variant, but it's currently marked private.

torchgen/operator_versions/gen_mobile_upgraders.py

@@ -7,7 +7,6 @@ from typing import Any, Dict, List
 
 import torch
 from torch.jit.generate_bytecode import generate_upgraders_bytecode
-
 from torchgen.code_template import CodeTemplate
 from torchgen.operator_versions.gen_mobile_upgraders_constant import (
     MOBILE_UPGRADERS_HEADER_DESCRIPTION,

torchgen/static_runtime/gen_static_runtime_ops.py

@@ -10,6 +10,7 @@ from torchgen.context import native_function_manager
 from torchgen.model import DispatchKey, NativeFunctionsGroup, NativeFunctionsViewGroup
 from torchgen.static_runtime import config, generator
 
+
 # Given a list of `grouped_native_functions` sorted by their op names, return a list of
 # lists each of which groups ops that share the base name. For example, `mean` and
 # `mean.dim` are grouped together by this function.

torchgen/static_runtime/generator.py

@@ -1,6 +1,5 @@
 import json
 import logging
-
 import math
 from typing import Dict, List, Optional, Sequence, Tuple, Union
 
@@ -21,6 +20,7 @@ from torchgen.model import (
 )
 from torchgen.static_runtime import config
 
+
 logger: logging.Logger = logging.getLogger()