


"""simple docstring"""






import pytest

from datasets.utils.version import Version




@pytest.mark.parametrize(
    'other, expected_equality'       ,   [
        (Version('1.0.0'				), True),
        ('1.0.0', True),
        (Version('2.0.0'				), False),
        ('2.0.0', False),
        ('1', False),
        ('a', False),
        (1, False),
        (None, False),
    ]       ,   )
def        A_					(					UpperCAmelCase__       ,   UpperCAmelCase__				)     ->     Optional[int]:
   a   :	Dict						=    Version('1.0.0'				)
   assert (version == other) is expected_equality
   assert (version != other) is not expected_equality
   assert (hash(UpperCAmelCase__				) == hash(UpperCAmelCase__				)) is expected_equality










'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


SCREAMING_SNAKE_CASE__     : int				=   {"""configuration_bert_generation""": ["""BertGenerationConfig"""]}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__     : List[Any]				=   ["""BertGenerationTokenizer"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__     : Optional[Any]				=   [
							    """BertGenerationDecoder""",
							    """BertGenerationEncoder""",
							    """BertGenerationPreTrainedModel""",
							    """load_tf_weights_in_bert_generation""",
							]


if TYPE_CHECKING:
							from .configuration_bert_generation import BertGenerationConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_bert_generation import BertGenerationTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_bert_generation import (
														    BertGenerationDecoder,
														    BertGenerationEncoder,
														    BertGenerationPreTrainedModel,
														    load_tf_weights_in_bert_generation,
														)

else:
							import sys

							SCREAMING_SNAKE_CASE__     : Any				=   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
