




'''simple docstring'''



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


UpperCAmelCase_							:	str	     =		logging.get_logger(__name__)

UpperCAmelCase_							:	str	     =		{
    '''google/vivit-b-16x2-kinetics400''': (
        '''https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json'''
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}





class      lowerCAmelCase (			__A):
       __lowercase	:   int										=      '''vivit'''


       def __init__( self     ,	__SCREAMING_SNAKE_CASE=224     ,	__SCREAMING_SNAKE_CASE=32     ,	__SCREAMING_SNAKE_CASE=[2, 16, 16]     ,	__SCREAMING_SNAKE_CASE=3     ,	__SCREAMING_SNAKE_CASE=768     ,	__SCREAMING_SNAKE_CASE=12     ,	__SCREAMING_SNAKE_CASE=12     ,	__SCREAMING_SNAKE_CASE=3072     ,	__SCREAMING_SNAKE_CASE="gelu_fast"     ,	__SCREAMING_SNAKE_CASE=0.0     ,	__SCREAMING_SNAKE_CASE=0.0     ,	__SCREAMING_SNAKE_CASE=0.02     ,	__SCREAMING_SNAKE_CASE=1E-06     ,	__SCREAMING_SNAKE_CASE=True     ,	**__SCREAMING_SNAKE_CASE     ,	)   ->	Dict:



            '''simple docstring'''




            __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            =	image_size
            __snake_case            =	num_frames
            __snake_case            =	tubelet_size
            __snake_case            =	num_channels
            __snake_case            =	qkv_bias

            super().__init__(**__A	)










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


SCREAMING_SNAKE_CASE							    =							{}


try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE							    =							['MLukeTokenizer']

if TYPE_CHECKING:
  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_mluke import MLukeTokenizer


else:
  import sys

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



