

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


lowerCamelCase_    =					logging.get_logger(__name__)

lowerCamelCase_    =					{
    '''dandelin/vilt-b32-mlm''': '''https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json'''
}







class  __lowerCamelCase				(	__snake_case	):
      lowerCamelCase_	:      int          =					'vilt'







      def __init__(     self							,  lowerCamelCase=30522							,  lowerCamelCase=2							,  lowerCamelCase=2							,  lowerCamelCase=40							,  lowerCamelCase=768							,  lowerCamelCase=12							,  lowerCamelCase=12							,  lowerCamelCase=3072							,  lowerCamelCase="gelu"							,  lowerCamelCase=0.0							,  lowerCamelCase=0.0							,  lowerCamelCase=0.02							,  lowerCamelCase=1e-12							,  lowerCamelCase=384							,  lowerCamelCase=32							,  lowerCamelCase=3							,  lowerCamelCase=True							,  lowerCamelCase=-1							,  lowerCamelCase=False							,  lowerCamelCase=-1							,  **lowerCamelCase							,  )						->       int:
        super().__init__(tie_word_embeddings=lowerCamelCase							,  **lowerCamelCase   )

        snake_case_       						=      vocab_size
        snake_case_       						=      type_vocab_size
        snake_case_       						=      modality_type_vocab_size
        snake_case_       						=      max_position_embeddings

        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_       						=      patch_size
        snake_case_       						=      num_channels
        snake_case_       						=      qkv_bias
        snake_case_       						=      max_image_length
        snake_case_       						=      num_images


from __future__ import annotations

from collections.abc import Generator



def    UpperCamelCase(					lowercase_							)	->				Generator[int, None, None]:





  '''simple docstring'''





  if not isinstance(lowercase_			,					lowercase_							) or n < 1:
    raise Exception("""Sequence only defined for positive integers"""							)

  yield n
  while n != 1:
    if n % 2 == 0:
      n //= 2
    else:
      snake_case_       						=      3 * n + 1
    yield n



def    UpperCamelCase(					)	->				Optional[int]:





  '''simple docstring'''





  snake_case_       						=      43
  snake_case_       						=      tuple(collatz_sequence(lowercase_							)							)
  print(lowercase_							)
  print(f'''Collatz sequence from {n} took {len(lowercase_							)} steps.'''							)


if __name__ == "__main__":
    main()