




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


__A						:							Tuple							=  logging.get_logger(__name__)

__A						:							Optional[int]							=  {
    """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 			UpperCAmelCase_      (   A       ):




							'''simple docstring'''



							a__						  =     '''mctct'''





							def __init__(					self       :	Optional[int]       ,     a       :	int=8_065       ,     a       :	Union[str, Any]=1_536       ,     a       :	Dict=36       ,     a       :	Union[str, Any]=6_144       ,     a       :	Any=4       ,     a       :	List[str]=384       ,     a       :	Any=920       ,     a       :	Dict=1E-5       ,     a       :	Any=0.3       ,     a       :	Any="relu"       ,     a       :	List[Any]=0.02       ,     a       :	Any=0.3       ,     a       :	Union[str, Any]=0.3       ,     a       :	str=1       ,     a       :	List[Any]=0       ,     a       :	Union[str, Any]=2       ,     a       :	Tuple=1       ,     a       :	Tuple=0.3       ,     a       :	str=1       ,     a       :	str=(7,)       ,     a       :	int=(3,)       ,     a       :	str=80       ,     a       :	Optional[Any]=1       ,     a       :	Union[str, Any]=None       ,     a       :	str="sum"       ,     a       :	List[str]=False       ,     **a       :	Optional[Any]       ,     )			->					Dict:
										super().__init__(**a       ,     pad_token_id=a       ,     bos_token_id=a       ,     eos_token_id=a			)
										SCREAMING_SNAKE_CASE           =					vocab_size
										SCREAMING_SNAKE_CASE           =					hidden_size
										SCREAMING_SNAKE_CASE           =					num_hidden_layers
										SCREAMING_SNAKE_CASE           =					intermediate_size
										SCREAMING_SNAKE_CASE           =					num_attention_heads
										SCREAMING_SNAKE_CASE           =					attention_head_dim
										SCREAMING_SNAKE_CASE           =					max_position_embeddings
										SCREAMING_SNAKE_CASE           =					layer_norm_eps
										SCREAMING_SNAKE_CASE           =					layerdrop
										SCREAMING_SNAKE_CASE           =					hidden_act
										SCREAMING_SNAKE_CASE           =					initializer_range
										SCREAMING_SNAKE_CASE           =					hidden_dropout_prob
										SCREAMING_SNAKE_CASE           =					attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE           =					pad_token_id
										SCREAMING_SNAKE_CASE           =					bos_token_id
										SCREAMING_SNAKE_CASE           =					eos_token_id
										SCREAMING_SNAKE_CASE           =					conv_glu_dim
										SCREAMING_SNAKE_CASE           =					conv_dropout
										SCREAMING_SNAKE_CASE           =					num_conv_layers
										SCREAMING_SNAKE_CASE           =					input_feat_per_channel
										SCREAMING_SNAKE_CASE           =					input_channels
										SCREAMING_SNAKE_CASE           =					conv_channels
										SCREAMING_SNAKE_CASE           =					ctc_loss_reduction
										SCREAMING_SNAKE_CASE           =					ctc_zero_infinity

										# prevents config testing fail with exporting to json
										SCREAMING_SNAKE_CASE           =					list(a			)
										SCREAMING_SNAKE_CASE           =					list(a			)

										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


__A						:							Any							=  logging.get_logger(__name__)

__A						:							int							=  {
    # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}




class 			UpperCAmelCase_      (   A       ):




							'''simple docstring'''



							a__						  =     '''megatron-bert'''





							def __init__(					self       :	str       ,     a       :	Union[str, Any]=29_056       ,     a       :	Optional[int]=1_024       ,     a       :	str=24       ,     a       :	str=16       ,     a       :	str=4_096       ,     a       :	Any="gelu"       ,     a       :	Any=0.1       ,     a       :	Optional[int]=0.1       ,     a       :	Optional[int]=512       ,     a       :	Optional[Any]=2       ,     a       :	List[str]=0.02       ,     a       :	List[Any]=1E-1_2       ,     a       :	Any=0       ,     a       :	List[Any]="absolute"       ,     a       :	List[str]=True       ,     **a       :	Optional[Any]       ,     )			->					List[str]:
										super().__init__(pad_token_id=a       ,     **a			)

										SCREAMING_SNAKE_CASE           =					vocab_size
										SCREAMING_SNAKE_CASE           =					hidden_size
										SCREAMING_SNAKE_CASE           =					num_hidden_layers
										SCREAMING_SNAKE_CASE           =					num_attention_heads
										SCREAMING_SNAKE_CASE           =					hidden_act
										SCREAMING_SNAKE_CASE           =					intermediate_size
										SCREAMING_SNAKE_CASE           =					hidden_dropout_prob
										SCREAMING_SNAKE_CASE           =					attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE           =					max_position_embeddings
										SCREAMING_SNAKE_CASE           =					type_vocab_size
										SCREAMING_SNAKE_CASE           =					initializer_range
										SCREAMING_SNAKE_CASE           =					layer_norm_eps
										SCREAMING_SNAKE_CASE           =					position_embedding_type
										SCREAMING_SNAKE_CASE           =					use_cache






