



'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_A				:    Tuple     						=logging.get_logger(__name__)

_A				:    str     						={
    '''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}



class 		lowerCamelCase__      (						A     ):




					'''simple docstring'''



					A_						    =						"""vit_mae"""




					def __init__(  self				:	int     ,  UpperCamelCase_				:	Union[str, Any]=768     ,  UpperCamelCase_				:	Optional[Any]=12     ,  UpperCamelCase_				:	Any=12     ,  UpperCamelCase_				:	Any=3072     ,  UpperCamelCase_				:	int="gelu"     ,  UpperCamelCase_				:	str=0.0     ,  UpperCamelCase_				:	str=0.0     ,  UpperCamelCase_				:	Union[str, Any]=0.02     ,  UpperCamelCase_				:	int=1E-12     ,  UpperCamelCase_				:	Dict=224     ,  UpperCamelCase_				:	Optional[Any]=16     ,  UpperCamelCase_				:	List[str]=3     ,  UpperCamelCase_				:	str=True     ,  UpperCamelCase_				:	Optional[int]=16     ,  UpperCamelCase_				:	Optional[Any]=512     ,  UpperCamelCase_				:	Tuple=8     ,  UpperCamelCase_				:	Dict=2048     ,  UpperCamelCase_				:	List[str]=0.75     ,  UpperCamelCase_				:	Dict=False     ,  **UpperCamelCase_				:	Dict     ,  )  ->       Dict:



						'''simple docstring'''





						super().__init__(**UpperCamelCase_					)

						_lowercase					:       Optional[Any]       =		hidden_size
						_lowercase					:       Dict       =		num_hidden_layers
						_lowercase					:       Union[str, Any]       =		num_attention_heads
						_lowercase					:       int       =		intermediate_size
						_lowercase					:       Dict       =		hidden_act
						_lowercase					:       Any       =		hidden_dropout_prob
						_lowercase					:       Optional[int]       =		attention_probs_dropout_prob
						_lowercase					:       str       =		initializer_range
						_lowercase					:       List[str]       =		layer_norm_eps
						_lowercase					:       int       =		image_size
						_lowercase					:       List[str]       =		patch_size
						_lowercase					:       List[Any]       =		num_channels
						_lowercase					:       Dict       =		qkv_bias
						_lowercase					:       Dict       =		decoder_num_attention_heads
						_lowercase					:       Any       =		decoder_hidden_size
						_lowercase					:       List[Any]       =		decoder_num_hidden_layers
						_lowercase					:       Union[str, Any]       =		decoder_intermediate_size
						_lowercase					:       Optional[Any]       =		mask_ratio
						_lowercase					:       Tuple       =		norm_pix_loss





'''simple docstring'''

_A				:    Dict     						='''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

_A				:    Dict     						=[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
_A				:    Dict     						={
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}
