
"""simple docstring"""






import json
import os
import tempfile

from transformers.testing_utils import check_json_file_has_correct_format

class 					__a     :



							'''simple docstring'''







							_lowerCamelCase					:			int          =   None
							def   SCREAMING_SNAKE_CASE						(     self       )			->							Tuple:




										'''simple docstring'''
										__lowercase       =       self.feature_extraction_class(**self.feat_extract_dict       )
										__lowercase       =       json.loads(feat_extract.to_json_string()       )
										for key, value in self.feat_extract_dict.items():
													self.assertEqual(obj[key]  ,    _lowerCamelCase       )
							def   SCREAMING_SNAKE_CASE						(     self       )			->							Any:




										'''simple docstring'''
										__lowercase       =       self.feature_extraction_class(**self.feat_extract_dict       )

										with tempfile.TemporaryDirectory() as tmpdirname:
													__lowercase       =       os.path.join(_lowerCamelCase  ,    "feat_extract.json"       )
													feat_extract_first.to_json_file(_lowerCamelCase       )
													__lowercase       =       self.feature_extraction_class.from_json_file(_lowerCamelCase       )

										self.assertEqual(feat_extract_second.to_dict()  ,    feat_extract_first.to_dict()       )
							def   SCREAMING_SNAKE_CASE						(     self       )			->							Union[str, Any]:




										'''simple docstring'''
										__lowercase       =       self.feature_extraction_class(**self.feat_extract_dict       )

										with tempfile.TemporaryDirectory() as tmpdirname:
													__lowercase       =       feat_extract_first.save_pretrained(_lowerCamelCase       )[0]
													check_json_file_has_correct_format(_lowerCamelCase       )
													__lowercase       =       self.feature_extraction_class.from_pretrained(_lowerCamelCase       )

										self.assertEqual(feat_extract_second.to_dict()  ,    feat_extract_first.to_dict()       )





							def   SCREAMING_SNAKE_CASE						(     self       )			->							List[Any]:




										'''simple docstring'''
										__lowercase       =       self.feature_extraction_class()
										self.assertIsNotNone(_lowerCamelCase       )







"""simple docstring"""






from typing import TYPE_CHECKING

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


_lowercase							=				{'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}

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

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowercase							=				[
					    '''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

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





