


'''simple docstring'''



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


_lowercase      :      List[str]            =  logging.get_logger(__name__)

_lowercase      :      Dict            =  {
    """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__(       lowerCAmelCase	):
				__magic_name__    :				List[str]  		=	"mctct"




				def __init__(		self      :			Union[str, Any]				,   lowerCAmelCase      :			Any=8065				,   lowerCAmelCase      :			List[Any]=1536				,   lowerCAmelCase      :			Tuple=36				,   lowerCAmelCase      :			Union[str, Any]=6144				,   lowerCAmelCase      :			List[str]=4				,   lowerCAmelCase      :			str=384				,   lowerCAmelCase      :			List[str]=920				,   lowerCAmelCase      :			Optional[int]=1E-5				,   lowerCAmelCase      :			Dict=0.3				,   lowerCAmelCase      :			Union[str, Any]="relu"				,   lowerCAmelCase      :			Tuple=0.02				,   lowerCAmelCase      :			List[str]=0.3				,   lowerCAmelCase      :			Optional[int]=0.3				,   lowerCAmelCase      :			str=1				,   lowerCAmelCase      :			List[Any]=0				,   lowerCAmelCase      :			str=2				,   lowerCAmelCase      :			Any=1				,   lowerCAmelCase      :			Dict=0.3				,   lowerCAmelCase      :			Dict=1				,   lowerCAmelCase      :			Any=(7,)				,   lowerCAmelCase      :			List[Any]=(3,)				,   lowerCAmelCase      :			Optional[int]=80				,   lowerCAmelCase      :			Dict=1				,   lowerCAmelCase      :			Dict=None				,   lowerCAmelCase      :			Optional[Any]="sum"				,   lowerCAmelCase      :			List[Any]=False				,   **lowerCAmelCase      :			Tuple				,   )->					Optional[int]:

										"""simple docstring"""




										super().__init__(**lowerCAmelCase				,   pad_token_id=lowerCAmelCase				,   bos_token_id=lowerCAmelCase				,   eos_token_id=lowerCAmelCase				)
										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(lowerCAmelCase				)
										UpperCAmelCase					    =     list(lowerCAmelCase				)

										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}`."""				)









'''simple docstring'''



from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass






@dataclass
class 	UpperCamelCase__:
				__magic_name__    :				int
				__magic_name__    :				TreeNode | None  		=	None
				__magic_name__    :				TreeNode | None  		=	None







_lowercase      :      Tuple            =					namedtuple("""CoinsDistribResult""", """moves excess""")


def 				lowerCamelCase__				(	A       :      TreeNode | None					):




						'''simple docstring'''






						if root is None:
												return 0

						# Validation
						def count_nodes(A       :      TreeNode | None					) -> int:
												if node is None:
																		return 0

												return count_nodes(node.left					) + count_nodes(node.right					) + 1

						def count_coins(A       :      TreeNode | None					) -> int:
												if node is None:
																		return 0

												return count_coins(node.left					) + count_coins(node.right					) + node.data

						if count_nodes(A					) != count_coins(A					):
												raise ValueError('''The nodes number should be same as the number of coins'''					)

						# Main calculation
						def get_distrib(A       :      TreeNode | None					) -> CoinsDistribResult:

												if node is None:
																		return CoinsDistribResult(0				,       1					)

												UpperCAmelCase    ,    UpperCAmelCase					    =     get_distrib(node.left					)
												UpperCAmelCase    ,    UpperCAmelCase					    =     get_distrib(node.right					)

												UpperCAmelCase					    =     1 - left_distrib_excess
												UpperCAmelCase					    =     1 - right_distrib_excess

												UpperCAmelCase					    =     (
												    left_distrib_moves
												    + right_distrib_moves
												    + abs(A					)
												    + abs(A					)
												)
												UpperCAmelCase					    =     node.data - coins_to_left - coins_to_right

												return CoinsDistribResult(A				,       A					)

						return get_distrib(A					)[0]


if __name__ == "__main__":
	import doctest

	doctest.testmod()





