




'''simple docstring'''





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


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

UpperCamelCase_		:    Union[str, Any]									=		{
    '''MCG-NJU/videomae-base''': '''https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json''',
}

class      _a       (		__lowerCAmelCase							):
     SCREAMING_SNAKE_CASE_							:					Any					       =		"""videomae"""






     def __init__(				self      ,_SCREAMING_SNAKE_CASE=224      ,_SCREAMING_SNAKE_CASE=16      ,_SCREAMING_SNAKE_CASE=3      ,_SCREAMING_SNAKE_CASE=16      ,_SCREAMING_SNAKE_CASE=2      ,_SCREAMING_SNAKE_CASE=768      ,_SCREAMING_SNAKE_CASE=12      ,_SCREAMING_SNAKE_CASE=12      ,_SCREAMING_SNAKE_CASE=3_072      ,_SCREAMING_SNAKE_CASE="gelu"      ,_SCREAMING_SNAKE_CASE=0.0      ,_SCREAMING_SNAKE_CASE=0.0      ,_SCREAMING_SNAKE_CASE=0.0_2      ,_SCREAMING_SNAKE_CASE=1e-12      ,_SCREAMING_SNAKE_CASE=True      ,_SCREAMING_SNAKE_CASE=True      ,_SCREAMING_SNAKE_CASE=6      ,_SCREAMING_SNAKE_CASE=384      ,_SCREAMING_SNAKE_CASE=4      ,_SCREAMING_SNAKE_CASE=1_536      ,_SCREAMING_SNAKE_CASE=True      ,**_SCREAMING_SNAKE_CASE      ,)							->    Union[str, Any]:
          super().__init__(**_SCREAMING_SNAKE_CASE					)

          _snake_case							=   image_size
          _snake_case							=   patch_size
          _snake_case							=   num_channels
          _snake_case							=   num_frames
          _snake_case							=   tubelet_size

          _snake_case							=   hidden_size
          _snake_case							=   num_hidden_layers
          _snake_case							=   num_attention_heads
          _snake_case							=   intermediate_size
          _snake_case							=   hidden_act
          _snake_case							=   hidden_dropout_prob
          _snake_case							=   attention_probs_dropout_prob
          _snake_case							=   initializer_range
          _snake_case							=   layer_norm_eps
          _snake_case							=   qkv_bias
          _snake_case							=   use_mean_pooling

          _snake_case							=   decoder_num_attention_heads
          _snake_case							=   decoder_hidden_size
          _snake_case							=   decoder_num_hidden_layers
          _snake_case							=   decoder_intermediate_size
          _snake_case							=   norm_pix_loss








'''simple docstring'''





UpperCamelCase_		:    Optional[Any]									=		'''
# Diffusers installation
! pip install diffusers transformers datasets accelerate
# 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/diffusers.git
'''

UpperCamelCase_		:    List[Any]									=		[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]


