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


lowerCamelCase  =logging.get_logger(__name__)

lowerCamelCase  ={
    "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 					_lowerCamelCase			(   UpperCamelCase_			):





     """simple docstring"""







     SCREAMING_SNAKE_CASE_		 =	'''mctct'''






     def __init__(				self    ,    __SCREAMING_SNAKE_CASE=8_0_6_5    ,    __SCREAMING_SNAKE_CASE=1_5_3_6    ,    __SCREAMING_SNAKE_CASE=3_6    ,    __SCREAMING_SNAKE_CASE=6_1_4_4    ,    __SCREAMING_SNAKE_CASE=4    ,    __SCREAMING_SNAKE_CASE=3_8_4    ,    __SCREAMING_SNAKE_CASE=9_2_0    ,    __SCREAMING_SNAKE_CASE=1e-5    ,    __SCREAMING_SNAKE_CASE=0.3    ,    __SCREAMING_SNAKE_CASE="relu"    ,    __SCREAMING_SNAKE_CASE=0.02    ,    __SCREAMING_SNAKE_CASE=0.3    ,    __SCREAMING_SNAKE_CASE=0.3    ,    __SCREAMING_SNAKE_CASE=1    ,    __SCREAMING_SNAKE_CASE=0    ,    __SCREAMING_SNAKE_CASE=2    ,    __SCREAMING_SNAKE_CASE=1    ,    __SCREAMING_SNAKE_CASE=0.3    ,    __SCREAMING_SNAKE_CASE=1    ,    __SCREAMING_SNAKE_CASE=(7,)    ,    __SCREAMING_SNAKE_CASE=(3,)    ,    __SCREAMING_SNAKE_CASE=8_0    ,    __SCREAMING_SNAKE_CASE=1    ,    __SCREAMING_SNAKE_CASE=None    ,    __SCREAMING_SNAKE_CASE="sum"    ,    __SCREAMING_SNAKE_CASE=False    ,    **__SCREAMING_SNAKE_CASE    ,    )	-> Any:




           """simple docstring"""







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

           # prevents config testing fail with exporting to json
           UpperCamelCase__     : Any											=					list(__SCREAMING_SNAKE_CASE	)
           UpperCamelCase__     : int											=					list(__SCREAMING_SNAKE_CASE	)

           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}`.'''	)




def 				SCREAMING_SNAKE_CASE_   (      UpperCamelCase__ = 2_0_0_0_0_0_0		):
      UpperCamelCase__     : Dict											=					[0 for i in range(n + 1		)]
      UpperCamelCase__     : Any											=					1
      UpperCamelCase__     : int											=					1

      for i in range(2			,		int(n**0.5		) + 1		):
            if primality_list[i] == 0:
                  for j in range(i * i			,		n + 1			,		UpperCamelCase__		):
                        UpperCamelCase__     : Any											=					1
      UpperCamelCase__     : Optional[Any]											=					0
      for i in range(UpperCamelCase__		):
            if primality_list[i] == 0:
                  sum_of_primes += i
      return sum_of_primes


if __name__ == "__main__":
    print(F'''{solution() = }''')


