



'''simple docstring'''





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


_lowerCAmelCase										=     logging.get_logger(__name__)

_lowerCAmelCase										=     {
    '''google/realm-cc-news-pretrained-embedder''': (
        '''https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json'''
    ),
    '''google/realm-cc-news-pretrained-encoder''': (
        '''https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json'''
    ),
    '''google/realm-cc-news-pretrained-scorer''': (
        '''https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json'''
    ),
    '''google/realm-cc-news-pretrained-openqa''': (
        '''https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json'''
    ),
    '''google/realm-orqa-nq-openqa''': '''https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json''',
    '''google/realm-orqa-nq-reader''': '''https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json''',
    '''google/realm-orqa-wq-openqa''': '''https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json''',
    '''google/realm-orqa-wq-reader''': '''https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json''',
    # See all REALM models at https://huggingface.co/models?filter=realm
}






class 	lowerCAmelCase_(    SCREAMING_SNAKE_CASE_					):
  '''simple docstring'''




  __lowercase							:				int           =				'''realm'''




  def __init__(   self  ,__UpperCAmelCase=3_0522  ,__UpperCAmelCase=768  ,__UpperCAmelCase=128  ,__UpperCAmelCase=12  ,__UpperCAmelCase=12  ,__UpperCAmelCase=8  ,__UpperCAmelCase=3072  ,__UpperCAmelCase="gelu_new"  ,__UpperCAmelCase=0.1  ,__UpperCAmelCase=0.1  ,__UpperCAmelCase=512  ,__UpperCAmelCase=2  ,__UpperCAmelCase=0.0_2  ,__UpperCAmelCase=1E-12  ,__UpperCAmelCase=256  ,__UpperCAmelCase=10  ,__UpperCAmelCase=1E-3  ,__UpperCAmelCase=5  ,__UpperCAmelCase=320  ,__UpperCAmelCase=1335_3718  ,__UpperCAmelCase=5000  ,__UpperCAmelCase=1  ,__UpperCAmelCase=0  ,__UpperCAmelCase=2  ,**__UpperCAmelCase  ,)   ->		Union[str, Any]:
      super().__init__(pad_token_id=__UpperCAmelCase  ,bos_token_id=__UpperCAmelCase  ,eos_token_id=__UpperCAmelCase  ,**__UpperCAmelCase				)

      # Common config
      lowerCAmelCase__			:  Any											= vocab_size
      lowerCAmelCase__			:  Optional[Any]											= max_position_embeddings
      lowerCAmelCase__			:  int											= hidden_size
      lowerCAmelCase__			:  str											= retriever_proj_size
      lowerCAmelCase__			:  Union[str, Any]											= num_hidden_layers
      lowerCAmelCase__			:  Optional[int]											= num_attention_heads
      lowerCAmelCase__			:  Dict											= num_candidates
      lowerCAmelCase__			:  Optional[Any]											= intermediate_size
      lowerCAmelCase__			:  Dict											= hidden_act
      lowerCAmelCase__			:  Dict											= hidden_dropout_prob
      lowerCAmelCase__			:  Any											= attention_probs_dropout_prob
      lowerCAmelCase__			:  int											= initializer_range
      lowerCAmelCase__			:  List[str]											= type_vocab_size
      lowerCAmelCase__			:  List[str]											= layer_norm_eps

      # Reader config
      lowerCAmelCase__			:  Union[str, Any]											= span_hidden_size
      lowerCAmelCase__			:  str											= max_span_width
      lowerCAmelCase__			:  Any											= reader_layer_norm_eps
      lowerCAmelCase__			:  Any											= reader_beam_size
      lowerCAmelCase__			:  Dict											= reader_seq_len

      # Retrieval config
      lowerCAmelCase__			:  Tuple											= num_block_records
      lowerCAmelCase__			:  int											= searcher_beam_size







'''simple docstring'''





from PIL import Image
def        _SCREAMING_SNAKE_CASE  (	UpperCamelCase      ):



    """simple docstring"""





    lowerCAmelCase__				,       lowerCAmelCase__			:  Dict											= image.size
    lowerCAmelCase__			:  int											= 0
    lowerCAmelCase__			:  int											= image.load()
    for i in range(UpperCamelCase      ):
        for j in range(UpperCamelCase      ):
            lowerCAmelCase__			:  int											= pixels[j, i]
            mean += pixel
    mean //= width * height

    for j in range(UpperCamelCase      ):
        for i in range(UpperCamelCase      ):
            lowerCAmelCase__			:  Dict											= 255 if pixels[i, j] > mean else 0
    return image


if __name__ == "__main__":
 _lowerCAmelCase										=     mean_threshold(Image.open('''path_to_image''').convert('''L'''))
 image.save('''output_image_path''')


