





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


_UpperCamelCase							=			logging.get_logger(__name__)

_UpperCamelCase							=			{
    '''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"""






      UpperCAmelCase_    :   int      ="mctct"







      def __init__(			self					,    UpperCAmelCase=8065					,    UpperCAmelCase=1536					,    UpperCAmelCase=36					,    UpperCAmelCase=6144					,    UpperCAmelCase=4					,    UpperCAmelCase=384					,    UpperCAmelCase=920					,    UpperCAmelCase=1E-5					,    UpperCAmelCase=0.3					,    UpperCAmelCase="relu"					,    UpperCAmelCase=0.02					,    UpperCAmelCase=0.3					,    UpperCAmelCase=0.3					,    UpperCAmelCase=1					,    UpperCAmelCase=0					,    UpperCAmelCase=2					,    UpperCAmelCase=1					,    UpperCAmelCase=0.3					,    UpperCAmelCase=1					,    UpperCAmelCase=(7,)					,    UpperCAmelCase=(3,)					,    UpperCAmelCase=80					,    UpperCAmelCase=1					,    UpperCAmelCase=None					,    UpperCAmelCase="sum"					,    UpperCAmelCase=False					,    **UpperCAmelCase					,    )							-> 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 )
        __snake_case :					str          =							vocab_size
        __snake_case :					Dict          =							hidden_size
        __snake_case :					Dict          =							num_hidden_layers
        __snake_case :					Optional[Any]          =							intermediate_size
        __snake_case :					str          =							num_attention_heads
        __snake_case :					str          =							attention_head_dim
        __snake_case :					List[str]          =							max_position_embeddings
        __snake_case :					Any          =							layer_norm_eps
        __snake_case :					Any          =							layerdrop
        __snake_case :					int          =							hidden_act
        __snake_case :					Optional[int]          =							initializer_range
        __snake_case :					List[str]          =							hidden_dropout_prob
        __snake_case :					Optional[int]          =							attention_probs_dropout_prob
        __snake_case :					List[str]          =							pad_token_id
        __snake_case :					Tuple          =							bos_token_id
        __snake_case :					Any          =							eos_token_id
        __snake_case :					Optional[Any]          =							conv_glu_dim
        __snake_case :					Union[str, Any]          =							conv_dropout
        __snake_case :					Any          =							num_conv_layers
        __snake_case :					List[str]          =							input_feat_per_channel
        __snake_case :					List[str]          =							input_channels
        __snake_case :					Tuple          =							conv_channels
        __snake_case :					List[str]          =							ctc_loss_reduction
        __snake_case :					str          =							ctc_zero_infinity

        # prevents config testing fail with exporting to json
        __snake_case :					Any          =							list(__SCREAMING_SNAKE_CASE )
        __snake_case :					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}`.""" )



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


lowerCamelCase  =logging.get_logger(__name__)

lowerCamelCase  ={
    "abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json",
}




class 					_lowerCamelCase			(   UpperCamelCase_			):





     """simple docstring"""







     SCREAMING_SNAKE_CASE_		 =	'''gpt_neox_japanese'''






     def __init__(				self    ,    __SCREAMING_SNAKE_CASE=3_2_0_0_0    ,    __SCREAMING_SNAKE_CASE=2_5_6_0    ,    __SCREAMING_SNAKE_CASE=3_2    ,    __SCREAMING_SNAKE_CASE=3_2    ,    __SCREAMING_SNAKE_CASE=4    ,    __SCREAMING_SNAKE_CASE="gelu"    ,    __SCREAMING_SNAKE_CASE=1.00    ,    __SCREAMING_SNAKE_CASE=1_0_0_0_0    ,    __SCREAMING_SNAKE_CASE=2_0_4_8    ,    __SCREAMING_SNAKE_CASE=0.02    ,    __SCREAMING_SNAKE_CASE=1e-5    ,    __SCREAMING_SNAKE_CASE=True    ,    __SCREAMING_SNAKE_CASE=3_1_9_9_6    ,    __SCREAMING_SNAKE_CASE=3_1_9_9_9    ,    __SCREAMING_SNAKE_CASE=0.1    ,    __SCREAMING_SNAKE_CASE=0.0    ,    **__SCREAMING_SNAKE_CASE    ,    )	-> List[str]:




           """simple docstring"""







           super().__init__(bos_token_id=__SCREAMING_SNAKE_CASE    ,    eos_token_id=__SCREAMING_SNAKE_CASE    ,    **__SCREAMING_SNAKE_CASE	)
           UpperCamelCase__     : List[str]											=					vocab_size
           UpperCamelCase__     : int											=					max_position_embeddings
           UpperCamelCase__     : Union[str, Any]											=					hidden_size
           UpperCamelCase__     : Any											=					num_hidden_layers
           UpperCamelCase__     : List[Any]											=					num_attention_heads
           UpperCamelCase__     : int											=					intermediate_multiple_size
           UpperCamelCase__     : List[Any]											=					hidden_act
           UpperCamelCase__     : Tuple											=					rotary_pct
           UpperCamelCase__     : Optional[int]											=					rotary_emb_base
           UpperCamelCase__     : Optional[Any]											=					initializer_range
           UpperCamelCase__     : Optional[int]											=					layer_norm_eps
           UpperCamelCase__     : Optional[Any]											=					use_cache
           UpperCamelCase__     : List[str]											=					attention_dropout
           UpperCamelCase__     : Optional[int]											=					hidden_dropout


