
"""simple docstring"""

from typing import Callable, Optional, Union

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


_A				=					logging.get_logger(__name__)

_A				=					{
    'microsoft/prophetnet-large-uncased': (
        'https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json'
    ),
}






class 			_lowercase  (							__UpperCAmelCase						):
	lowercase_								=      'prophetnet'
	lowercase_								=      ['past_key_values']
	lowercase_								=      {
	    'num_attention_heads': 'num_encoder_attention_heads',
	}




	def __init__(					self						,					UpperCAmelCase_ = 0.1						,					UpperCAmelCase_ = "gelu"						,					UpperCAmelCase_ = 30522						,					UpperCAmelCase_ = 1024						,					UpperCAmelCase_ = 4096						,					UpperCAmelCase_ = 12						,					UpperCAmelCase_ = 16						,					UpperCAmelCase_ = 4096						,					UpperCAmelCase_ = 12						,					UpperCAmelCase_ = 16						,					UpperCAmelCase_ = 0.1						,					UpperCAmelCase_ = 0.1						,					UpperCAmelCase_ = 512						,					UpperCAmelCase_ = 0.02						,					UpperCAmelCase_ = True						,					UpperCAmelCase_ = True						,					UpperCAmelCase_ = 0						,					UpperCAmelCase_ = 2						,					UpperCAmelCase_ = 32						,					UpperCAmelCase_ = 128						,					UpperCAmelCase_ = False						,					UpperCAmelCase_ = 0.0						,					UpperCAmelCase_ = True						,					UpperCAmelCase_ = 0						,					UpperCAmelCase_ = 1						,					UpperCAmelCase_ = 2						,					**UpperCAmelCase_						,					)						->				Optional[Any]:
			lowerCamelCase	:     Tuple            =       vocab_size
			lowerCamelCase	:     Union[str, Any]            =       hidden_size
			lowerCamelCase	:     Optional[int]            =       encoder_ffn_dim
			lowerCamelCase	:     str            =       num_encoder_layers
			lowerCamelCase	:     List[Any]            =       num_encoder_attention_heads
			lowerCamelCase	:     List[Any]            =       decoder_ffn_dim
			lowerCamelCase	:     List[str]            =       num_decoder_layers
			lowerCamelCase	:     Optional[int]            =       num_decoder_attention_heads
			lowerCamelCase	:     List[str]            =       max_position_embeddings
			lowerCamelCase	:     List[Any]            =       init_std  # Normal(0, this parameter)
			lowerCamelCase	:     Optional[int]            =       activation_function

			# parameters for prophetnet
			lowerCamelCase	:     Union[str, Any]            =       ngram
			lowerCamelCase	:     List[str]            =       num_buckets
			lowerCamelCase	:     Tuple            =       relative_max_distance
			lowerCamelCase	:     Optional[int]            =       disable_ngram_loss
			lowerCamelCase	:     Tuple            =       eps

			# 3 Types of Dropout
			lowerCamelCase	:     str            =       attention_dropout
			lowerCamelCase	:     List[Any]            =       activation_dropout
			lowerCamelCase	:     Optional[int]            =       dropout

			lowerCamelCase	:     List[str]            =       use_cache

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




	@property
	def      _UpperCamelCase       (					self   )						->				int:
			return self.num_encoder_layers + self.num_decoder_layers




	@num_hidden_layers.setter
	def      _UpperCamelCase       (					self						,					UpperCAmelCase_   )						->				Optional[int]:
			raise NotImplementedError(
			    'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
			    ' `num_decoder_layers`.'   )








"""simple docstring"""

from __future__ import annotations

from queue import Queue
def 						UpperCAmelCase   (						a_,		a_     ):





		'''simple docstring'''


		a ^= b
		b ^= a
		a ^= b
		return a, b
def 						UpperCAmelCase   (						a_,		a_     ):





		'''simple docstring'''


		lowerCamelCase	:     int            =       1
		while (1 << j) < max_node:
				for i in range(1,		max_node + 1     ):
						lowerCamelCase	:     Tuple            =       parent[j - 1][parent[j - 1][i]]
				j += 1
		return parent
def 						UpperCAmelCase   (						a_,		a_,		a_,		a_     ):





		'''simple docstring'''


		if level[u] < level[v]:
				lowerCamelCase      ,       lowerCamelCase	:     List[Any]            =       swap(a_,		a_     )
		# making depth of u same as depth of v
		for i in range(18,		-1,		-1     ):
				if level[u] - (1 << i) >= level[v]:
						lowerCamelCase	:     int            =       parent[i][u]
    # at the same depth if u==v that mean lca is found
		if u == v:
				return u
		# moving both nodes upwards till lca in found
		for i in range(18,		-1,		-1     ):
				if parent[i][u] not in [0, parent[i][v]]:
						lowerCamelCase      ,       lowerCamelCase	:     str            =       parent[i][u], parent[i][v]
    # returning longest common ancestor of u,v
		return parent[0][u]
def 						UpperCAmelCase   (						a_,		a_,		a_,		a_,		a_ = 1,		):





		'''simple docstring'''


		lowerCamelCase	:     Any            =       0
		lowerCamelCase	:     Queue[int]            =       Queue(maxsize=a_     )
		q.put(a_     )
		while q.qsize() != 0:
				lowerCamelCase	:     Tuple            =       q.get()
				for v in graph[u]:
						if level[v] == -1:
								lowerCamelCase	:     Optional[Any]            =       level[u] + 1
								q.put(a_     )
								lowerCamelCase	:     str            =       u
		return level, parent
def 						UpperCAmelCase   (						):





		'''simple docstring'''


		lowerCamelCase	:     Any            =       13
		# initializing with 0
		lowerCamelCase	:     Dict            =       [[0 for _ in range(max_node + 10     )] for _ in range(20     )]
		# initializing with -1 which means every node is unvisited
		lowerCamelCase	:     List[Any]            =       [-1 for _ in range(max_node + 10     )]
		lowerCamelCase	:     dict[int, list[int]]            =       {
		    1: [2, 3, 4],
		    2: [5],
		    3: [6, 7],
		    4: [8],
		    5: [9, 10],
		    6: [11],
		    7: [],
		    8: [12, 13],
		    9: [],
		    10: [],
		    11: [],
		    12: [],
		    13: [],
		}
		lowerCamelCase      ,       lowerCamelCase	:     Dict            =       breadth_first_search(a_,		a_,		a_,		a_,		1     )
		lowerCamelCase	:     List[Any]            =       create_sparse(a_,		a_     )
		print('LCA of node 1 and 3 is: ',		lowest_common_ancestor(1,		3,		a_,		a_     )     )
		print('LCA of node 5 and 6 is: ',		lowest_common_ancestor(5,		6,		a_,		a_     )     )
		print('LCA of node 7 and 11 is: ',		lowest_common_ancestor(7,		11,		a_,		a_     )     )
		print('LCA of node 6 and 7 is: ',		lowest_common_ancestor(6,		7,		a_,		a_     )     )
		print('LCA of node 4 and 12 is: ',		lowest_common_ancestor(4,		12,		a_,		a_     )     )
		print('LCA of node 8 and 8 is: ',		lowest_common_ancestor(8,		8,		a_,		a_     )     )


if __name__ == "__main__":
					main()






