
import numpy as np

from transformers import Pipeline




def 	A_ (							snake_case							:   str )      ->    Optional[Any]:
						__UpperCamelCase       =			np.max(__lowercase ,      axis=-1 ,      keepdims=__lowercase )
						__UpperCamelCase       =			np.exp(outputs - maxes )
						return shifted_exp / shifted_exp.sum(axis=-1 ,      keepdims=__lowercase )






class        SCREAMING_SNAKE_CASE__    (							__A    ):

							"""simple docstring"""






							def     A__		(  self     ,	**SCREAMING_SNAKE_CASE_			)->   Optional[Any]:





													'''simple docstring'''






													__UpperCamelCase       =			{}
													if "second_text" in kwargs:
																			__UpperCamelCase       =			kwargs['second_text']
													return preprocess_kwargs, {}, {}



							def     A__		(  self     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_=None			)->   int:





													'''simple docstring'''






													return self.tokenizer(SCREAMING_SNAKE_CASE_     ,	text_pair=SCREAMING_SNAKE_CASE_     ,	return_tensors=self.framework			)



							def     A__		(  self     ,	SCREAMING_SNAKE_CASE_			)->   str:





													'''simple docstring'''






													return self.model(**SCREAMING_SNAKE_CASE_			)



							def     A__		(  self     ,	SCREAMING_SNAKE_CASE_			)->   Tuple:





													'''simple docstring'''






													__UpperCamelCase       =			model_outputs.logits[0].numpy()
													__UpperCamelCase       =			softmax(SCREAMING_SNAKE_CASE_			)

													__UpperCamelCase       =			np.argmax(SCREAMING_SNAKE_CASE_			)
													__UpperCamelCase       =			self.model.config.idalabel[best_class]
													__UpperCamelCase       =			probabilities[best_class].item()
													__UpperCamelCase       =			logits.tolist()
													return {"label": label, "score": score, "logits": logits}






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


lowercase__							:							Tuple									=			logging.get_logger(__name__)

lowercase__							:							Union[str, Any]									=			{
    "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        SCREAMING_SNAKE_CASE__    (							SCREAMING_SNAKE_CASE_    ):

							"""simple docstring"""






							_snake_case     		=  'mctct'



							def __init__(  self     ,	SCREAMING_SNAKE_CASE_=8065     ,	SCREAMING_SNAKE_CASE_=1536     ,	SCREAMING_SNAKE_CASE_=36     ,	SCREAMING_SNAKE_CASE_=6144     ,	SCREAMING_SNAKE_CASE_=4     ,	SCREAMING_SNAKE_CASE_=384     ,	SCREAMING_SNAKE_CASE_=920     ,	SCREAMING_SNAKE_CASE_=1E-5     ,	SCREAMING_SNAKE_CASE_=0.3     ,	SCREAMING_SNAKE_CASE_="relu"     ,	SCREAMING_SNAKE_CASE_=0.0_2     ,	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_=80     ,	SCREAMING_SNAKE_CASE_=1     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_="sum"     ,	SCREAMING_SNAKE_CASE_=False     ,	**SCREAMING_SNAKE_CASE_     ,	)->   Tuple:





													'''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       =			vocab_size
													__UpperCamelCase       =			hidden_size
													__UpperCamelCase       =			num_hidden_layers
													__UpperCamelCase       =			intermediate_size
													__UpperCamelCase       =			num_attention_heads
													__UpperCamelCase       =			attention_head_dim
													__UpperCamelCase       =			max_position_embeddings
													__UpperCamelCase       =			layer_norm_eps
													__UpperCamelCase       =			layerdrop
													__UpperCamelCase       =			hidden_act
													__UpperCamelCase       =			initializer_range
													__UpperCamelCase       =			hidden_dropout_prob
													__UpperCamelCase       =			attention_probs_dropout_prob
													__UpperCamelCase       =			pad_token_id
													__UpperCamelCase       =			bos_token_id
													__UpperCamelCase       =			eos_token_id
													__UpperCamelCase       =			conv_glu_dim
													__UpperCamelCase       =			conv_dropout
													__UpperCamelCase       =			num_conv_layers
													__UpperCamelCase       =			input_feat_per_channel
													__UpperCamelCase       =			input_channels
													__UpperCamelCase       =			conv_channels
													__UpperCamelCase       =			ctc_loss_reduction
													__UpperCamelCase       =			ctc_zero_infinity

													# prevents config testing fail with exporting to json
													__UpperCamelCase       =			list(SCREAMING_SNAKE_CASE_			)
													__UpperCamelCase       =			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}`."			)




