
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A							=       {"""configuration_dinat""": ["""DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DinatConfig"""]}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _A							=       [
          """DINAT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """DinatForImageClassification""",
          """DinatModel""",
          """DinatPreTrainedModel""",
          """DinatBackbone""",
      ]

if TYPE_CHECKING:
      from .configuration_dinat import DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP, DinatConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_dinat import (
                DINAT_PRETRAINED_MODEL_ARCHIVE_LIST,
                DinatBackbone,
                DinatForImageClassification,
                DinatModel,
                DinatPreTrainedModel,
            )

else:
      import sys

      _A							=       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








'''simple docstring'''






from unittest.mock import patch

import datasets
from datasets import Dataset




def        snake_case_   (	)->						str:





       '''simple docstring'''


       _UpperCAmelCase    :		Tuple     	=					Dataset.from_dict({"""col_1""": [3, 2, 0, 1]}						)

       with patch("""tqdm.auto.tqdm"""						) as mock_tqdm:
              datasets.disable_progress_bar()
              dset.map(lambda lowerCAmelCase_						: {"col_2": x["col_1"] + 1}						)
              mock_tqdm.assert_not_called()

              mock_tqdm.reset_mock()

              datasets.enable_progress_bar()
              dset.map(lambda lowerCAmelCase_						: {"col_2": x["col_1"] + 1}						)
              mock_tqdm.assert_called()



