





from typing import Callable, Optional, Union

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


SCREAMING_SNAKE_CASE_   :      Dict			=   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_   :      List[Any]			=   {
    '''microsoft/xprophetnet-large-wiki100-cased''': (
        '''https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json'''
    ),
}

class 		snake_case_   (							UpperCAmelCase_						):







	'''simple docstring'''
	__UpperCamelCase   =		'''xlm-prophetnet'''
	__UpperCamelCase   =		['''past_key_values''']
	__UpperCamelCase   =		{
	    '''num_attention_heads''': '''num_encoder_attention_heads''',
	}




	def __init__(						self							:     int					,      __lowerCamelCase							:     Optional[float] = 0.1					,      __lowerCamelCase							:     Optional[Union[str, Callable]] = "gelu"					,      __lowerCamelCase							:     Optional[int] = 30_522					,      __lowerCamelCase							:     Optional[int] = 1_024					,      __lowerCamelCase							:     Optional[int] = 4_096					,      __lowerCamelCase							:     Optional[int] = 12					,      __lowerCamelCase							:     Optional[int] = 16					,      __lowerCamelCase							:     Optional[int] = 4_096					,      __lowerCamelCase							:     Optional[int] = 12					,      __lowerCamelCase							:     Optional[int] = 16					,      __lowerCamelCase							:     Optional[float] = 0.1					,      __lowerCamelCase							:     Optional[float] = 0.1					,      __lowerCamelCase							:     Optional[int] = 512					,      __lowerCamelCase							:     Optional[float] = 0.02					,      __lowerCamelCase							:     Optional[bool] = True					,      __lowerCamelCase							:     Optional[bool] = True					,      __lowerCamelCase							:     Optional[int] = 0					,      __lowerCamelCase							:     Optional[int] = 2					,      __lowerCamelCase							:     Optional[int] = 32					,      __lowerCamelCase							:     Optional[int] = 128					,      __lowerCamelCase							:     Optional[bool] = False					,      __lowerCamelCase							:     Optional[float] = 0.0					,      __lowerCamelCase							:     Optional[bool] = True					,      __lowerCamelCase							:     Optional[int] = 0					,      __lowerCamelCase							:     Optional[int] = 1					,      __lowerCamelCase							:     Optional[int] = 2					,      **__lowerCamelCase							:     int					,      )       -> Dict:

			'''simple docstring'''




			__lowercase											=     vocab_size
			__lowercase											=     hidden_size
			__lowercase											=     encoder_ffn_dim
			__lowercase											=     num_encoder_layers
			__lowercase											=     num_encoder_attention_heads
			__lowercase											=     decoder_ffn_dim
			__lowercase											=     num_decoder_layers
			__lowercase											=     num_decoder_attention_heads
			__lowercase											=     max_position_embeddings
			__lowercase											=     init_std  # Normal(0, this parameter)
			__lowercase											=     activation_function

			# parameters for xlmprophetnet
			__lowercase											=     ngram
			__lowercase											=     num_buckets
			__lowercase											=     relative_max_distance
			__lowercase											=     disable_ngram_loss
			__lowercase											=     eps

			# 3 Types of Dropout
			__lowercase											=     attention_dropout
			__lowercase											=     activation_dropout
			__lowercase											=     dropout

			__lowercase											=     use_cache

			super().__init__(
			    pad_token_id=__lowerCamelCase					,      bos_token_id=__lowerCamelCase					,      eos_token_id=__lowerCamelCase					,      is_encoder_decoder=__lowerCamelCase					,      add_cross_attention=__lowerCamelCase					,      decoder_start_token_id=__lowerCamelCase					,      **__lowerCamelCase					,      )




	@property
	def    UpperCAmelCase			(						self							:     Union[str, Any]   )       -> int:

			'''simple docstring'''




			return self.num_encoder_layers + self.num_decoder_layers






	@num_hidden_layers.setter
	def    UpperCAmelCase			(						self							:     Dict					,      __lowerCamelCase							:     int   )       -> List[str]:

			'''simple docstring'''




			raise NotImplementedError(
			    'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
			    ' `num_decoder_layers`.'   )











def  SCREAMING_SNAKE_CASE				(      snake_case						,   snake_case						,   snake_case						,   snake_case							)		->    int:
		# Return True if there is node that has not iterated.
		__lowercase											=     [False] * len(snake_case							)
		__lowercase											=     []
		queue.append(snake_case							)
		__lowercase											=     True

		while queue:
				__lowercase											=     queue.pop(0							)
				for ind in range(len(graph[u]							)							):
						if visited[ind] is False and graph[u][ind] > 0:
								queue.append(snake_case							)
								__lowercase											=     True
								__lowercase											=     u

		return visited[t]



def  SCREAMING_SNAKE_CASE				(      snake_case						,   snake_case						,   snake_case							)		->    Dict:
		# This array is filled by BFS and to store path
		__lowercase											=     [-1] * (len(snake_case							))
		__lowercase											=     0
		while bfs(snake_case						,   snake_case						,   snake_case						,   snake_case							):
				__lowercase											=     float('Inf'							)
				__lowercase											=     sink

				while s != source:
						# Find the minimum value in select path
						__lowercase											=     min(snake_case						,   graph[parent[s]][s]							)
						__lowercase											=     parent[s]

				max_flow += path_flow
				__lowercase											=     sink

				while v != source:
						__lowercase											=     parent[v]
						graph[u][v] -= path_flow
						graph[v][u] += path_flow
						__lowercase											=     parent[v]
		return max_flow


SCREAMING_SNAKE_CASE_   :      Any			=   [
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]

SCREAMING_SNAKE_CASE_	,SCREAMING_SNAKE_CASE_   :      Optional[Any]			=   0, 5


print(ford_fulkerson(graph, source, sink))




