






import re
from pathlib import Path
from unittest import TestCase

import pytest





@pytest.mark.integration
class __lowerCamelCase (      snake_case__):





	"""simple docstring"""






	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							with open(UpperCAmelCase       ,    encoding='utf-8'    ) as input_file:
													_UpperCAmelCase									=			re.compile(R'(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)'    )
													_UpperCAmelCase									=			input_file.read()
													_UpperCAmelCase									=			regexp.search(UpperCAmelCase    )

							return match

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							with open(UpperCAmelCase       ,    encoding='utf-8'    ) as input_file:
													_UpperCAmelCase									=			re.compile(R'#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()'       ,    re.DOTALL    )
													_UpperCAmelCase									=			input_file.read()
													# use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
													_UpperCAmelCase									=			regexp.finditer(UpperCAmelCase    )

							_UpperCAmelCase									=			[match for match in matches if match is not None and match.group(1    ) is not None]
							return matches[0] if matches else None

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			Path('./datasets'    )
							_UpperCAmelCase									=			list(dataset_paths.absolute().glob('**/*.py'    )    )

							for dataset in dataset_files:
													if self._no_encoding_on_file_open(str(UpperCAmelCase    )    ):
																			raise AssertionError(F"""open(...) must use utf-8 encoding in {dataset}"""    )

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			Path('./datasets'    )
							_UpperCAmelCase									=			list(dataset_paths.absolute().glob('**/*.py'    )    )

							for dataset in dataset_files:
													if self._no_print_statements(str(UpperCAmelCase    )    ):
																			raise AssertionError(F"""print statement found in {dataset}. Use datasets.logger/logging instead."""    )

from typing import TYPE_CHECKING

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


__lowerCamelCase					:	Dict       =  {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}

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

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase					:	Optional[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

		__lowerCamelCase					:	Any       =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
