Add __all__ to torch.distributed, futures, fx, nn, package, benchmark submodules (#80520)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/80520
Approved by: https://github.com/rohan-varma

test/allowlist_for_publicAPI.json

@@ -459,12 +459,6 @@
   "torch.distributed.elastic.metrics": [
     "Optional"
   ],
-  "torch.distributed.elastic.metrics.api": [
-    "Dict",
-    "Optional",
-    "namedtuple",
-    "wraps"
-  ],
   "torch.distributed.elastic.multiprocessing": [
     "Callable",
     "Dict",
@@ -508,12 +502,6 @@
     "get_logger",
     "wraps"
   ],
-  "torch.distributed.elastic.multiprocessing.errors.error_handler": [
-    "Optional"
-  ],
-  "torch.distributed.elastic.multiprocessing.errors.handlers": [
-    "ErrorHandler"
-  ],
   "torch.distributed.elastic.multiprocessing.redirects": [
     "contextmanager",
     "partial",
@@ -920,15 +908,7 @@
     "svd_lowrank"
   ],
   "torch.futures": [
-    "Callable",
-    "Future",
-    "Generic",
-    "List",
-    "Optional",
-    "Type",
-    "TypeVar",
-    "Union",
-    "cast"
+    "Future"
   ],
   "torch.fx": [
     "ProxyableClassMeta",
@@ -1033,25 +1013,6 @@
     "Tuple",
     "compatibility"
   ],
-  "torch.fx.node": [
-    "Any",
-    "ArgsKwargsPair",
-    "Argument",
-    "BaseArgumentTypes",
-    "Callable",
-    "Dict",
-    "List",
-    "Optional",
-    "Set",
-    "Target",
-    "Tuple",
-    "Union",
-    "compatibility",
-    "immutable_dict",
-    "immutable_list",
-    "normalize_function",
-    "normalize_module"
-  ],
   "torch.fx.operator_schemas": [
     "Any",
     "Callable",
@@ -1072,53 +1033,6 @@
     "chain",
     "compatibility"
   ],
-  "torch.fx.passes.graph_manipulation": [
-    "Any",
-    "Argument",
-    "Dict",
-    "Graph",
-    "GraphModule",
-    "List",
-    "NamedTuple",
-    "Node",
-    "Optional",
-    "ShapeProp",
-    "Target",
-    "Tuple",
-    "compatibility",
-    "lift_lowering_attrs_to_nodes",
-    "map_aggregate",
-    "map_arg"
-  ],
-  "torch.fx.passes.param_fetch": [
-    "Any",
-    "Callable",
-    "Dict",
-    "GraphModule",
-    "List",
-    "Tuple",
-    "Type",
-    "compatibility"
-  ],
-  "torch.fx.passes.shape_prop": [
-    "Any",
-    "Dict",
-    "NamedTuple",
-    "Node",
-    "Optional",
-    "Tuple",
-    "compatibility",
-    "map_aggregate"
-  ],
-  "torch.fx.passes.split_module": [
-    "Any",
-    "Callable",
-    "Dict",
-    "GraphModule",
-    "List",
-    "Optional",
-    "compatibility"
-  ],
   "torch.fx.proxy": [
     "assert_fn"
   ],
@@ -1412,11 +1326,6 @@
   "torch.nn.intrinsic.modules": [
     "_FusedModule"
   ],
-  "torch.nn.intrinsic.qat.modules.conv_fused": [
-    "Parameter",
-    "TypeVar",
-    "fuse_conv_bn_weights"
-  ],
   "torch.nn.intrinsic.qat.modules.linear_fused": [
     "Parameter",
     "fuse_linear_bn_weights"
@@ -1436,14 +1345,6 @@
   "torch.nn.parallel.comm": [
     "List"
   ],
-  "torch.nn.parallel.data_parallel": [
-    "Module",
-    "chain",
-    "gather",
-    "parallel_apply",
-    "replicate",
-    "scatter_kwargs"
-  ],
   "torch.nn.parallel.parallel_apply": [
     "ExceptionWrapper",
     "autocast"
@@ -1452,8 +1353,7 @@
     "OrderedDict"
   ],
   "torch.nn.parallel.scatter_gather": [
-    "Gather",
-    "Scatter"
+    "is_namedtuple"
   ],
   "torch.nn.parameter": [
     "OrderedDict"
@@ -1514,26 +1414,6 @@
     "Iterable",
     "Optional"
   ],
-  "torch.nn.utils.parametrizations": [
-    "Enum",
-    "Module",
-    "Optional",
-    "Tensor",
-    "auto"
-  ],
-  "torch.nn.utils.parametrize": [
-    "Dict",
-    "Module",
-    "ModuleDict",
-    "ModuleList",
-    "Optional",
-    "Parameter",
-    "Sequence",
-    "Tensor",
-    "Tuple",
-    "Union",
-    "contextmanager"
-  ],
   "torch.onnx": [
     "Dict",
     "OperatorExportTypes",
@@ -1550,11 +1430,6 @@
     "has_torch_function",
     "push_torch_function_mode"
   ],
-  "torch.package.analyze.find_first_use_of_broken_modules": [
-    "Dict",
-    "List",
-    "PackagingError"
-  ],
   "torch.package.analyze.is_from_package": [
     "Any",
     "ModuleType",
@@ -1919,10 +1794,6 @@
     "rand",
     "randn"
   ],
-  "torch.torch_version": [
-    "Any",
-    "Iterable"
-  ],
   "torch.types": [
     "Any",
     "Device",
@@ -1937,14 +1808,6 @@
     "enable_minidumps",
     "enable_minidumps_on_exceptions"
   ],
-  "torch.utils.benchmark.utils.common": [
-    "_make_temp_dir",
-    "ordered_unique",
-    "select_unit",
-    "set_torch_threads",
-    "trim_sigfig",
-    "unit_to_english"
-  ],
   "torch.utils.benchmark.utils.compare": [
     "Colorize",
     "Table",

torch/distributed/elastic/metrics/api.py

@@ -13,6 +13,10 @@ from collections import namedtuple
 from functools import wraps
 from typing import Dict, Optional
 
+__all__ = ['MetricsConfig', 'MetricHandler', 'ConsoleMetricHandler', 'NullMetricHandler', 'MetricStream',
+           'configure', 'getStream', 'prof', 'profile', 'put_metric', 'publish_metric', 'get_elapsed_time_ms',
+           'MetricData']
+
 MetricData = namedtuple("MetricData", ["timestamp", "group_name", "name", "value"])
 
 

torch/distributed/elastic/multiprocessing/errors/error_handler.py

@@ -14,6 +14,7 @@ import traceback
 import warnings
 from typing import Optional
 
+__all__ = ['ErrorHandler']
 
 log = logging.getLogger(__name__)
 

torch/distributed/elastic/multiprocessing/errors/handlers.py

@@ -10,6 +10,7 @@
 
 from torch.distributed.elastic.multiprocessing.errors.error_handler import ErrorHandler
 
+__all__ = ['get_error_handler']
 
 def get_error_handler():
     return ErrorHandler()

torch/futures/__init__.py

@@ -4,6 +4,8 @@ from typing import cast, Callable, Generic, List, Optional, Type, TypeVar, Union
 
 import torch
 
+__all__ = ['Future', 'collect_all', 'wait_all']
+
 T = TypeVar("T")
 S = TypeVar("S")
 

torch/fx/node.py

@@ -11,6 +11,8 @@ from torch.fx.operator_schemas import normalize_function, normalize_module, Args
 if TYPE_CHECKING:
     from .graph import Graph
 
+__all__ = ['Node', 'map_arg', 'map_aggregate']
+
 BaseArgumentTypes = Union[str, int, float, bool, complex, torch.dtype,
                           torch.Tensor, torch.device, torch.memory_format, torch.layout]
 base_types = BaseArgumentTypes.__args__  # type: ignore[attr-defined]

torch/fx/passes/graph_drawer.py

@@ -9,6 +9,7 @@ from torch.fx.passes.shape_prop import TensorMetadata
 from torch.fx._compatibility import compatibility
 from itertools import chain
 
+__all__ = ['FxGraphDrawer']
 try:
     import pydot
     HAS_PYDOT = True

torch/fx/passes/graph_manipulation.py

@@ -11,6 +11,9 @@ from torch.fx.node import (
 )
 from torch.fx.passes.shape_prop import ShapeProp
 
+__all__ = ['replace_target_nodes_with', 'size_bytes', 'get_size_of_all_nodes', 'get_tensor_meta',
+           'get_size_of_node']
+
 @compatibility(is_backward_compatible=False)
 def replace_target_nodes_with(
     fx_module: GraphModule,

torch/fx/passes/param_fetch.py

@@ -5,6 +5,7 @@ import torch.nn as nn
 
 from torch.fx._compatibility import compatibility
 
+__all__ = ['default_matching', 'extract_attrs_for_lowering', 'lift_lowering_attrs_to_nodes']
 
 # Matching method matches the attribute name of current version to the attribute name of `target_version`
 @compatibility(is_backward_compatible=False)

torch/fx/passes/shape_prop.py

@@ -6,6 +6,7 @@ from torch.fx.node import Node, map_aggregate
 from typing import Any, Tuple, NamedTuple, Optional, Dict
 from torch.fx._compatibility import compatibility
 
+__all__ = ['TensorMetadata', 'ShapeProp']
 
 @compatibility(is_backward_compatible=True)
 class TensorMetadata(NamedTuple):

torch/fx/passes/split_module.py

@@ -4,6 +4,8 @@ from typing import Callable, List, Dict, Any, Optional
 from torch.fx._compatibility import compatibility
 import inspect
 
+__all__ = ['Partition', 'split_module']
+
 @compatibility(is_backward_compatible=True)
 class Partition:
     def __init__(self, name: str):

torch/nn/intrinsic/qat/modules/conv_fused.py

@@ -10,6 +10,8 @@ from torch.nn.modules.utils import _single, _pair, _triple
 from torch.nn.parameter import Parameter
 from typing import TypeVar
 
+__all__ = ['ConvBn1d', 'ConvBnReLU1d', 'ConvReLU1d', 'ConvBn2d', 'ConvBnReLU2d', 'ConvReLU2d', 'ConvBn3d',
+           'ConvBnReLU3d', 'ConvReLU3d', 'update_bn_stats', 'freeze_bn_stats']
 _BN_CLASS_MAP = {
     1: nn.BatchNorm1d,
     2: nn.BatchNorm2d,

torch/nn/parallel/data_parallel.py

@@ -13,6 +13,8 @@ from torch._utils import (
     _get_devices_properties
 )
 
+__all__ = ['DataParallel', 'data_parallel']
+
 def _check_balance(device_ids):
     imbalance_warn = """
     There is an imbalance between your GPUs. You may want to exclude GPU {} which

torch/nn/parallel/scatter_gather.py

@@ -1,7 +1,15 @@
 import torch
 from ._functions import Scatter, Gather
+import warnings
+
+__all__ = ['scatter', 'scatter_kwargs', 'gather']
 
 def is_namedtuple(obj):
+    # Check if type was created from collections.namedtuple or a typing.NamedTuple.
+    warnings.warn("is_namedtuple is deprecated, please use the python checks instead")
+    return _is_namedtuple(obj)
+
+def _is_namedtuple(obj):
     # Check if type was created from collections.namedtuple or a typing.NamedTuple.
     return (
         isinstance(obj, tuple) and hasattr(obj, "_asdict") and hasattr(obj, "_fields")

torch/nn/utils/parametrizations.py

@@ -8,6 +8,7 @@ from .. import functional as F
 
 from typing import Optional
 
+__all__ = ['orthogonal', 'spectral_norm']
 
 def _is_orthogonal(Q, eps=None):
     n, k = Q.size(-2), Q.size(-1)

torch/nn/utils/parametrize.py

@@ -7,6 +7,9 @@ import collections
 from contextlib import contextmanager
 from typing import Union, Optional, Dict, Tuple, Sequence
 
+__all__ = ['cached', 'ParametrizationList', 'register_parametrization', 'is_parametrized', 'remove_parametrizations',
+           'type_before_parametrizations', 'transfer_parametrizations_and_params']
+
 _cache_enabled = 0
 _cache: Dict[Tuple[int, str], Optional[Tensor]] = {}
 

torch/package/analyze/find_first_use_of_broken_modules.py

@@ -2,6 +2,8 @@ from typing import Dict, List
 
 from ..package_exporter import PackagingError
 
+__all__ = ["find_first_use_of_broken_modules"]
+
 
 def find_first_use_of_broken_modules(exc: PackagingError) -> Dict[str, List[str]]:
     """

torch/torch_version.py

@@ -1,6 +1,8 @@
 from typing import Any, Iterable
 from .version import __version__ as internal_version
 
+__all__ = ['TorchVersion', 'Version', 'InvalidVersion']
+
 class _LazyImport:
     """Wraps around classes lazy imported from packaging.version
     Output of the function v in following snippets are identical:

torch/utils/benchmark/utils/common.py

@@ -14,7 +14,7 @@ import uuid
 import torch
 
 
-__all__ = ["TaskSpec", "Measurement", "_make_temp_dir"]
+__all__ = ["TaskSpec", "Measurement", "select_unit", "unit_to_english", "trim_sigfig", "ordered_unique", "set_torch_threads"]
 
 
 _MAX_SIGNIFICANT_FIGURES = 4

torch/utils/benchmark/utils/compare.py

@@ -7,7 +7,7 @@ from typing import DefaultDict, List, Optional, Tuple
 from torch.utils.benchmark.utils import common
 from torch import tensor as _tensor
 
-__all__ = ["Compare"]
+__all__ = ["Colorize", "Compare"]
 
 BEST = "\033[92m"
 GOOD = "\033[34m"

torch/utils/hipify/hipify_python.py

@@ -46,6 +46,12 @@ HIPIFY_FINAL_RESULT: HipifyFinalResult = {}
 to their actual types."""
 PYTORCH_TEMPLATE_MAP = {"Dtype": "scalar_t", "T": "scalar_t"}
 
+__all__ = ['InputError', 'openf', 'bcolors', 'GeneratedFileCleaner', 'match_extensions', 'matched_files_iter',
+           'preprocess_file_and_save_result', 'compute_stats', 'add_dim3', 'processKernelLaunches', 'find_closure_group',
+           'find_bracket_group', 'find_parentheses_group', 'replace_math_functions', 'hip_header_magic', 'replace_extern_shared',
+           'get_hip_file_path', 'is_out_of_place', 'is_pytorch_file', 'is_cusparse_file', 'is_caffe2_gpu_file',
+           'is_caffe2_gpu_file', 'Trie', 'preprocessor', 'file_specific_replacement', 'file_add_header',
+           'fix_static_global_kernels', 'extract_arguments', 'str2bool', 'hipify']
 
 class InputError(Exception):
     # Exception raised for errors in the input.