



"""simple docstring"""






from queue import PriorityQueue
from typing import Any

import numpy as np


def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,)						->   float | int:
			for nxt, d in graph[v]:
						if nxt in visited_forward:
									continue
						__lowerCAmelCase      :  Optional[Any]												=       cst_fwd.get(__snake_case					,np.inf	)
						__lowerCAmelCase      :  str												=       cst_fwd[v] + d
						if new_cost_f < old_cost_f:
									queue.put((new_cost_f, nxt)	)
									__lowerCAmelCase      :  List[str]												=       new_cost_f
									__lowerCAmelCase      :  Optional[Any]												=       v
						if nxt in visited_backward:
									if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
												__lowerCAmelCase      :  str												=       cst_fwd[v] + d + cst_bwd[nxt]
			return shortest_distance


def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case					,__snake_case	)						->   int:
			__lowerCAmelCase      :  Any												=       -1

			__lowerCAmelCase      :  str												=       set()
			__lowerCAmelCase      :  Optional[Any]												=       set()
			__lowerCAmelCase      :  int												=       {source: 0}
			__lowerCAmelCase      :  Tuple												=       {destination: 0}
			__lowerCAmelCase      :  Union[str, Any]												=       {source: None}
			__lowerCAmelCase      :  Dict												=       {destination: None}
			__lowerCAmelCase      :  PriorityQueue[Any]												=       PriorityQueue()
			__lowerCAmelCase      :  PriorityQueue[Any]												=       PriorityQueue()

			__lowerCAmelCase      :  Tuple												=       np.inf

			queue_forward.put((0, source)	)
			queue_backward.put((0, destination)	)

			if source == destination:
						return 0

			while not queue_forward.empty() and not queue_backward.empty():
						__lowerCAmelCase						,	__lowerCAmelCase      :  List[Any]												=       queue_forward.get()
						visited_forward.add(__snake_case	)

						__lowerCAmelCase						,	__lowerCAmelCase      :  str												=       queue_backward.get()
						visited_backward.add(__snake_case	)

						__lowerCAmelCase      :  Optional[Any]												=       pass_and_relaxation(
						    __snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,)

						__lowerCAmelCase      :  Optional[Any]												=       pass_and_relaxation(
						    __snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,)

						if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
									break

			if shortest_distance != np.inf:
						__lowerCAmelCase      :  Any												=       shortest_distance
			return shortest_path_distance


__snake_case							:   int      =    {
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}
__snake_case							:   List[Any]      =    {
    'B': [['E', 1]],
    'C': [['B', 1]],
    'D': [['C', 1]],
    'F': [['D', 1], ['G', 1]],
    'E': [[None, np.inf]],
    'G': [['E', 2]],
}

if __name__ == "__main__":
	import doctest

	doctest.testmod()




"""simple docstring"""






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


__snake_case							:   List[Any]      =    logging.get_logger(__name__)

__snake_case							:   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 			A__   (  __SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE          =	'mctct'

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

				# prevents config testing fail with exporting to json
				__lowerCAmelCase      :  List[str]												=       list(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase      :  Dict												=       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}`.""")