def 							UpperCamelCase				(    lowerCAmelCase_   )		->						int:




       '''simple docstring'''






       _A=	len(lowerCAmelCase_   )
       _A=	len(matrix[0]   )
       _A=	min(lowerCAmelCase_       ,					lowerCAmelCase_   )

       for row in range(lowerCAmelCase_   ):
              # Check if diagonal element is not zero
              if matrix[row][row] != 0:
                     # Eliminate all the elements below the diagonal
                     for col in range(row + 1       ,					lowerCAmelCase_   ):
                            _A=	matrix[col][row] / matrix[row][row]
                            for i in range(lowerCAmelCase_       ,					lowerCAmelCase_   ):
                                   matrix[col][i] -= multiplier * matrix[row][i]
              else:
                     # Find a non-zero diagonal element to swap rows
                     _A=	True
                     for i in range(row + 1       ,					lowerCAmelCase_   ):
                            if matrix[i][row] != 0:
                                   _A,			_A=	matrix[i], matrix[row]
                                   _A=	False
                                   break
                     if reduce:
                            rank -= 1
                            for i in range(lowerCAmelCase_   ):
                                   _A=	matrix[i][rank]

            # Reduce the row pointer by one to stay on the same row
                     row -= 1

       return rank


if __name__ == "__main__":
      import doctest

      doctest.testmod()







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


UpperCAmelCase_								=							logging.get_logger(__name__)

UpperCAmelCase_								=							{
    '''facebook/s2t-wav2vec2-large-en-de''': (
        '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json'''
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech2text2
}





class      lowerCAmelCase						(					_a			):
     _SCREAMING_SNAKE_CASE     :     Optional[Any]		="""speech_to_text_2"""
     _SCREAMING_SNAKE_CASE     :     str		=["""past_key_values"""]
     _SCREAMING_SNAKE_CASE     :     Tuple		={"""num_attention_heads""": """decoder_attention_heads""", """hidden_size""": """d_model"""}



     def __init__(					self				,      lowerCAmelCase__=10000				,      lowerCAmelCase__=6				,      lowerCAmelCase__=2048				,      lowerCAmelCase__=4				,      lowerCAmelCase__=0.0				,      lowerCAmelCase__=True				,      lowerCAmelCase__="relu"				,      lowerCAmelCase__=256				,      lowerCAmelCase__=0.1				,      lowerCAmelCase__=0.0				,      lowerCAmelCase__=0.0				,      lowerCAmelCase__=0.02				,      lowerCAmelCase__=2				,      lowerCAmelCase__=True				,      lowerCAmelCase__=1				,      lowerCAmelCase__=0				,      lowerCAmelCase__=2				,      lowerCAmelCase__=1024				,      **lowerCAmelCase__				,      ):
            _A=	vocab_size
            _A=	d_model
            _A=	decoder_ffn_dim
            _A=	decoder_layers
            _A=	decoder_attention_heads
            _A=	dropout
            _A=	attention_dropout
            _A=	activation_dropout
            _A=	activation_function
            _A=	init_std
            _A=	decoder_layerdrop
            _A=	use_cache
            _A=	decoder_layers
            _A=	scale_embedding  # scale factor will be sqrt(d_model) if True
            _A=	max_target_positions

            super().__init__(
                pad_token_id=lowerCAmelCase__				,      bos_token_id=lowerCAmelCase__				,      eos_token_id=lowerCAmelCase__				,      decoder_start_token_id=lowerCAmelCase__				,      **lowerCAmelCase__				,      )