


import os

import pytest

from transformers.dynamic_module_utils import get_imports


SCREAMING_SNAKE_CASE       :      Optional[int]												= "\nimport os\n"

SCREAMING_SNAKE_CASE       :      str												= "\ndef foo():\n    import os\n    return False\n"

SCREAMING_SNAKE_CASE       :      str												= "\ndef foo():\n    def bar():\n        if True:\n            import os\n        return False\n    return bar()\n"

SCREAMING_SNAKE_CASE       :      Tuple												= "\nimport os\n\ntry:\n    import bar\nexcept ImportError:\n    raise ValueError()\n"

SCREAMING_SNAKE_CASE       :      Dict												= "\nimport os\n\ndef foo():\n    try:\n        import bar\n    except ImportError:\n        raise ValueError()\n"

SCREAMING_SNAKE_CASE       :      Dict												= "\nimport os\n\ntry:\n    import bar\nexcept (ImportError, AttributeError):\n    raise ValueError()\n"

SCREAMING_SNAKE_CASE       :      Tuple												= "\nimport os\n\ntry:\n    import bar\nexcept ImportError as e:\n    raise ValueError()\n"

SCREAMING_SNAKE_CASE       :      Tuple												= "\nimport os\n\ntry:\n    import bar\nexcept:\n    raise ValueError()\n"

SCREAMING_SNAKE_CASE       :      List[Any]												= "\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    raise ValueError()\n"

SCREAMING_SNAKE_CASE       :      List[Any]												= "\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    x = 1\n    raise ValueError()\n"

SCREAMING_SNAKE_CASE       :      Any												= [
    TOP_LEVEL_IMPORT,
    IMPORT_IN_FUNCTION,
    DEEPLY_NESTED_IMPORT,
    TOP_LEVEL_TRY_IMPORT,
    GENERIC_EXCEPT_IMPORT,
    MULTILINE_TRY_IMPORT,
    MULTILINE_BOTH_IMPORT,
    MULTIPLE_EXCEPTS_IMPORT,
    EXCEPT_AS_IMPORT,
    TRY_IMPORT_IN_FUNCTION,
]



@pytest.mark.parametrize('case'							, lowerCamelCase_ )
def 				UpperCamelCase_(      lowerCamelCase_							, lowerCamelCase_ )    ->						Tuple:
    _lowercase       :							List[str]      		=		os.path.join(lowerCamelCase_							, 'test_file.py' )
    with open(lowerCamelCase_							, 'w' ) as _tmp_file:
        _tmp_file.write(lowerCamelCase_ )

    _lowercase       :							Tuple      		=		get_imports(lowerCamelCase_ )
    assert parsed_imports == ["os"]










"""simple docstring"""



import os
from argparse import ArgumentParser
from typing import List

import torch.utils.data

from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node


_UpperCamelCase		:  List[Any]						=		4
_UpperCamelCase		:  Optional[Any]						=		3

class        a     (   a_	):
    pass


def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  List[str]    ):





  '''simple docstring'''





  for shard in shards:
    for i in range(__snake_case    ):
      yield {"i": i, "shard": shard}
def 						_SCREAMING_SNAKE_CASE (    ):





  '''simple docstring'''





  lowercase							    =       int(os.environ['RANK']    )
  lowercase							    =       int(os.environ['WORLD_SIZE']    )

  lowercase							    =       ArgumentParser()
  parser.add_argument('--streaming'		,					type=__snake_case    )
  parser.add_argument('--local_rank'		,					type=__snake_case    )
  parser.add_argument('--num_workers'		,					type=__snake_case		,					default=0    )
  lowercase							    =       parser.parse_args()
  lowercase							    =       args.streaming
  lowercase							    =       args.num_workers

  lowercase							    =       {'shards': [f'shard_{shard_idx}' for shard_idx in range(__snake_case    )]}
  lowercase							    =       IterableDataset.from_generator(__snake_case		,					gen_kwargs=__snake_case    )
  if not streaming:
    lowercase							    =       Dataset.from_list(list(__snake_case    )    )

  lowercase							    =       split_dataset_by_node(__snake_case		,					rank=__snake_case		,					world_size=__snake_case    )
  lowercase							    =       torch.utils.data.DataLoader(__snake_case		,					num_workers=__snake_case    )

  lowercase							    =       NUM_SHARDS * NUM_ITEMS_PER_SHARD
  lowercase							    =       full_size // world_size
  expected_local_size += int(rank < (full_size % world_size)    )

  lowercase							    =       sum(1 for _ in dataloader    )
  if local_size != expected_local_size:
    raise FailedTestError(f'local_size {local_size} != expected_local_size {expected_local_size}'    )


if __name__ == "__main__":
    main()


