





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


lowercase :			int     		=    logging.get_logger(__name__)

lowercase :			str     		=    {
    """speechbrain/m-ctc-t-large""": """https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json""",
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}





class 					A__       (				A_      ):




   """simple docstring"""



   __A  :							Any			    =    '''mctct'''

   def __init__(   self   ,    lowercase=8065   ,    lowercase=1536   ,    lowercase=36   ,    lowercase=6144   ,    lowercase=4   ,    lowercase=384   ,    lowercase=920   ,    lowercase=1e-5   ,    lowercase=0.3   ,    lowercase="relu"   ,    lowercase=0.02   ,    lowercase=0.3   ,    lowercase=0.3   ,    lowercase=1   ,    lowercase=0   ,    lowercase=2   ,    lowercase=1   ,    lowercase=0.3   ,    lowercase=1   ,    lowercase=(7,)   ,    lowercase=(3,)   ,    lowercase=80   ,    lowercase=1   ,    lowercase=None   ,    lowercase="sum"   ,    lowercase=False   ,    **lowercase   ,    )     ->		Dict:







          '''simple docstring'''

          super().__init__(**lowercase   ,    pad_token_id=lowercase   ,    bos_token_id=lowercase   ,    eos_token_id=lowercase)
          a__		:      List[Any]					=							vocab_size
          a__		:      Optional[Any]					=							hidden_size
          a__		:      int					=							num_hidden_layers
          a__		:      Tuple					=							intermediate_size
          a__		:      Any					=							num_attention_heads
          a__		:      List[str]					=							attention_head_dim
          a__		:      Any					=							max_position_embeddings
          a__		:      int					=							layer_norm_eps
          a__		:      str					=							layerdrop
          a__		:      Optional[Any]					=							hidden_act
          a__		:      int					=							initializer_range
          a__		:      List[str]					=							hidden_dropout_prob
          a__		:      Union[str, Any]					=							attention_probs_dropout_prob
          a__		:      Optional[Any]					=							pad_token_id
          a__		:      List[str]					=							bos_token_id
          a__		:      int					=							eos_token_id
          a__		:      int					=							conv_glu_dim
          a__		:      Any					=							conv_dropout
          a__		:      int					=							num_conv_layers
          a__		:      str					=							input_feat_per_channel
          a__		:      int					=							input_channels
          a__		:      List[Any]					=							conv_channels
          a__		:      Optional[int]					=							ctc_loss_reduction
          a__		:      Union[str, Any]					=							ctc_zero_infinity

          # prevents config testing fail with exporting to json
          a__		:      List[Any]					=							list(lowercase)
          a__		:      Tuple					=							list(lowercase)

          if len(self.conv_kernel) != self.num_conv_layers:
                 raise ValueError(
                     'Configuration for convolutional module is incorrect. '
                     'It is required that `len(config.conv_kernel)` == `config.num_conv_layers` '
                     F'but is `len(config.conv_kernel) = {len(self.conv_kernel)}`, '
                     F'`config.num_conv_layers = {self.num_conv_layers}`.')






"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments

def 				_snake_case      (   ):




   """simple docstring"""







   _lowerCamelCase	:					Any   =		HfArgumentParser(__snake_case   )
   _lowerCamelCase	:					int   =		parser.parse_args_into_dataclasses()[0]
   _lowerCamelCase	:					Dict   =		TensorFlowBenchmark(args=__snake_case   )
   try:
      _lowerCamelCase	:					Optional[int]   =		parser.parse_args_into_dataclasses()[0]
   except ValueError as e:
      _lowerCamelCase	:					Union[str, Any]   =		"""Arg --no_{0} is no longer used, please use --no-{0} instead."""
      _lowerCamelCase	:					List[str]   =		""" """.join(str(__snake_case   ).split(""" """   )[:-1]   )
      _lowerCamelCase	:					Dict   =		""""""
      _lowerCamelCase	:					List[Any]   =		eval(str(__snake_case   ).split(""" """   )[-1]   )
      _lowerCamelCase	:					Tuple   =		[]
      for arg in depreciated_args:
         # arg[2:] removes '--'
         if arg[2:] in TensorFlowBenchmark.deprecated_args:
            # arg[5:] removes '--no_'
            full_error_msg += arg_error_msg.format(arg[5:]   )
         else:
            wrong_args.append(__snake_case   )
      if len(__snake_case   ) > 0:
         _lowerCamelCase	:					Tuple   =		full_error_msg + begin_error_msg + str(__snake_case   )
      raise ValueError(__snake_case   )
   benchmark.run()


if __name__ == "__main__":
 main()

