




'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_SCREAMING_SNAKE_CASE =	{
    "configuration_fsmt": ["FSMT_PRETRAINED_CONFIG_ARCHIVE_MAP", "FSMTConfig"],
    "tokenization_fsmt": ["FSMTTokenizer"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_SCREAMING_SNAKE_CASE =	["FSMTForConditionalGeneration", "FSMTModel", "PretrainedFSMTModel"]


if TYPE_CHECKING:
							from .configuration_fsmt import FSMT_PRETRAINED_CONFIG_ARCHIVE_MAP, FSMTConfig
							from .tokenization_fsmt import FSMTTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_fsmt import FSMTForConditionalGeneration, FSMTModel, PretrainedFSMTModel

else:
							import sys

							_SCREAMING_SNAKE_CASE =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










'''simple docstring'''
from unittest.mock import patch

import datasets
from datasets import Dataset





def  lowerCamelCase(       )		->		Any:
			A_       		=   Dataset.from_dict({'col_1': [3, 2, 0, 1]}    )

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

						mock_tqdm.reset_mock()

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




