





import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


A   : Tuple			=				pytest.mark.integration







@pytest.mark.parametrize("""path"""   ,					["""paws""", """csv"""]   )
def        __lowerCamelCase (							__a       :Union[str, Any]   ,					__a       :Optional[Any]   )		->    Optional[int]:






		"""simple docstring"""

		inspect_dataset(__a   ,					__a   )
		A__  				=       path + """.py"""
		assert script_name in os.listdir(__a   )
		assert "__pycache__" not in os.listdir(__a   )







@pytest.mark.filterwarnings("""ignore:inspect_metric is deprecated:FutureWarning"""   )
@pytest.mark.filterwarnings("""ignore:metric_module_factory is deprecated:FutureWarning"""   )
@pytest.mark.parametrize("""path"""   ,					["""accuracy"""]   )
def        __lowerCamelCase (							__a       :Optional[int]   ,					__a       :Dict   )		->    List[str]:






		"""simple docstring"""

		inspect_metric(__a   ,					__a   )
		A__  				=       path + """.py"""
		assert script_name in os.listdir(__a   )
		assert "__pycache__" not in os.listdir(__a   )







@pytest.mark.parametrize(
    """path, config_name, expected_splits"""   ,					[
        ("""squad""", """plain_text""", ["""train""", """validation"""]),
        ("""dalle-mini/wit""", """dalle-mini--wit""", ["""train"""]),
        ("""paws""", """labeled_final""", ["""train""", """test""", """validation"""]),
    ]   ,					)
def        __lowerCamelCase (							__a       :Optional[int]   ,					__a       :Optional[int]   ,					__a       :int   )		->    str:






		"""simple docstring"""

		A__  				=       get_dataset_config_info(__a   ,					config_name=__a   )
		assert info.config_name == config_name
		assert list(info.splits.keys()   ) == expected_splits







@pytest.mark.parametrize(
    """path, config_name, expected_exception"""   ,					[
        ("""paws""", None, ValueError),
    ]   ,					)
def        __lowerCamelCase (							__a       :Optional[Any]   ,					__a       :Dict   ,					__a       :Optional[int]   )		->    List[Any]:






		"""simple docstring"""

		with pytest.raises(__a   ):
				get_dataset_config_info(__a   ,					config_name=__a   )







@pytest.mark.parametrize(
    """path, expected"""   ,					[
        ("""squad""", """plain_text"""),
        ("""acronym_identification""", """default"""),
        ("""lhoestq/squad""", """plain_text"""),
        ("""lhoestq/test""", """default"""),
        ("""lhoestq/demo1""", """lhoestq--demo1"""),
        ("""dalle-mini/wit""", """dalle-mini--wit"""),
    ]   ,					)
def        __lowerCamelCase (							__a       :Dict   ,					__a       :List[str]   )		->    str:






		"""simple docstring"""

		A__  				=       get_dataset_config_names(__a   )
		assert expected in config_names







@pytest.mark.parametrize(
    """path, expected_configs, expected_splits_in_first_config"""   ,					[
        ("""squad""", ["""plain_text"""], ["""train""", """validation"""]),
        ("""dalle-mini/wit""", ["""dalle-mini--wit"""], ["""train"""]),
        ("""paws""", ["""labeled_final""", """labeled_swap""", """unlabeled_final"""], ["""train""", """test""", """validation"""]),
    ]   ,					)
def        __lowerCamelCase (							__a       :str   ,					__a       :Any   ,					__a       :List[Any]   )		->    Any:






		"""simple docstring"""

		A__  				=       get_dataset_infos(__a   )
		assert list(infos.keys()   ) == expected_configs
		A__  				=       expected_configs[0]
		assert expected_config in infos
		A__  				=       infos[expected_config]
		assert info.config_name == expected_config
		assert list(info.splits.keys()   ) == expected_splits_in_first_config







@pytest.mark.parametrize(
    """path, expected_config, expected_splits"""   ,					[
        ("""squad""", """plain_text""", ["""train""", """validation"""]),
        ("""dalle-mini/wit""", """dalle-mini--wit""", ["""train"""]),
        ("""paws""", """labeled_final""", ["""train""", """test""", """validation"""]),
    ]   ,					)
def        __lowerCamelCase (							__a       :Any   ,					__a       :int   ,					__a       :Union[str, Any]   )		->    Tuple:






		"""simple docstring"""

		A__  				=       get_dataset_infos(__a   )
		assert expected_config in infos
		A__  				=       infos[expected_config]
		assert info.config_name == expected_config
		assert list(info.splits.keys()   ) == expected_splits







@pytest.mark.parametrize(
    """path, config_name, expected_exception"""   ,					[
        ("""paws""", None, ValueError),
    ]   ,					)
def        __lowerCamelCase (							__a       :Optional[int]   ,					__a       :Any   ,					__a       :Tuple   )		->    Dict:






		"""simple docstring"""

		with pytest.raises(__a   ):
				get_dataset_split_names(__a   ,					config_name=__a   )










from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


A   : Optional[Any]			=				{'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A   : List[str]			=				[
					    '''VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''ViTMAEForPreTraining''',
					    '''ViTMAELayer''',
					    '''ViTMAEModel''',
					    '''ViTMAEPreTrainedModel''',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A   : Any			=				[
					    '''TFViTMAEForPreTraining''',
					    '''TFViTMAEModel''',
					    '''TFViTMAEPreTrainedModel''',
					]

if TYPE_CHECKING:
					from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_vit_mae import (
										    VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ViTMAEForPreTraining,
										    ViTMAELayer,
										    ViTMAEModel,
										    ViTMAEPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
					import sys

					A   : str			=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



