



'''simple docstring'''



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


lowerCAmelCase						:		Optional[Any]						      = logging.get_logger(__name__)

lowerCAmelCase						:		Optional[Any]						      = {
    '''dandelin/vilt-b32-mlm''': '''https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json'''
}






class        UpperCAmelCase__						(		UpperCamelCase__			):
					a   :  Union[str, Any]   =				"""vilt"""



					def __init__(     self      ,					UpperCamelCase=3_0522      ,					UpperCamelCase=2      ,					UpperCamelCase=2      ,					UpperCamelCase=40      ,					UpperCamelCase=768      ,					UpperCamelCase=12      ,					UpperCamelCase=12      ,					UpperCamelCase=3072      ,					UpperCamelCase="gelu"      ,					UpperCamelCase=0.0      ,					UpperCamelCase=0.0      ,					UpperCamelCase=0.02      ,					UpperCamelCase=1E-12      ,					UpperCamelCase=384      ,					UpperCamelCase=32      ,					UpperCamelCase=3      ,					UpperCamelCase=True      ,					UpperCamelCase=-1      ,					UpperCamelCase=False      ,					UpperCamelCase=-1      ,					**UpperCamelCase      ,					)  ->      Tuple:
						super().__init__(tie_word_embeddings=UpperCamelCase      ,					**UpperCamelCase  )

						__lowerCAmelCase       				=	vocab_size
						__lowerCAmelCase       				=	type_vocab_size
						__lowerCAmelCase       				=	modality_type_vocab_size
						__lowerCAmelCase       				=	max_position_embeddings

						__lowerCAmelCase       				=	hidden_size
						__lowerCAmelCase       				=	num_hidden_layers
						__lowerCAmelCase       				=	num_attention_heads
						__lowerCAmelCase       				=	intermediate_size
						__lowerCAmelCase       				=	hidden_act
						__lowerCAmelCase       				=	hidden_dropout_prob
						__lowerCAmelCase       				=	attention_probs_dropout_prob
						__lowerCAmelCase       				=	initializer_range
						__lowerCAmelCase       				=	layer_norm_eps

						__lowerCAmelCase       				=	image_size
						__lowerCAmelCase       				=	patch_size
						__lowerCAmelCase       				=	num_channels
						__lowerCAmelCase       				=	qkv_bias
						__lowerCAmelCase       				=	max_image_length
						__lowerCAmelCase       				=	num_images




'''simple docstring'''



lowerCAmelCase						:		Any						      = '''
# 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
'''

lowerCAmelCase						:		Any						      = [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
lowerCAmelCase						:		str						      = {
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}