

import copy

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


SCREAMING_SNAKE_CASE						:Union[str, Any]      =			logging.get_logger(__name__)

SCREAMING_SNAKE_CASE						:List[str]      =			{}






class 		__magic_name__ (				snake_case							):
     UpperCamelCase_     :List[str]									=	"""fsmt_decoder"""






     def __init__(							self						,		_lowercase=0						,		_lowercase=0     )->			Tuple:
         super().__init__()
         UpperCamelCase_          =		vocab_size
         UpperCamelCase_          =		bos_token_id






class 		__magic_name__ (				snake_case							):
     UpperCamelCase_     :Optional[Any]									=	"""fsmt"""
     UpperCamelCase_     :List[str]									=	{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}






     def __init__(							self						,		_lowercase=["en", "de"]						,		_lowercase=42_024						,		_lowercase=42_024						,		_lowercase="relu"						,		_lowercase=1_024						,		_lowercase=200						,		_lowercase=1_024						,		_lowercase=4_096						,		_lowercase=12						,		_lowercase=16						,		_lowercase=0.0						,		_lowercase=4_096						,		_lowercase=12						,		_lowercase=16						,		_lowercase=0.0						,		_lowercase=0.0						,		_lowercase=0.1						,		_lowercase=0.0						,		_lowercase=0.02						,		_lowercase=2						,		_lowercase=True						,		_lowercase=True						,		_lowercase=False						,		_lowercase=5						,		_lowercase=1.0						,		_lowercase=False						,		_lowercase=True						,		_lowercase=1						,		_lowercase=0						,		_lowercase=2						,		_lowercase=2						,		**_lowercase						,		)->			Union[str, Any]:
         UpperCamelCase_          =		langs
         UpperCamelCase_          =		src_vocab_size
         UpperCamelCase_          =		tgt_vocab_size
         UpperCamelCase_          =		d_model  # encoder_embed_dim and decoder_embed_dim

         UpperCamelCase_          =		encoder_ffn_dim
         UpperCamelCase_          =		UpperCamelCase_          =		encoder_layers
         UpperCamelCase_          =		encoder_attention_heads
         UpperCamelCase_          =		encoder_layerdrop
         UpperCamelCase_          =		decoder_layerdrop
         UpperCamelCase_          =		decoder_ffn_dim
         UpperCamelCase_          =		decoder_layers
         UpperCamelCase_          =		decoder_attention_heads
         UpperCamelCase_          =		max_position_embeddings
         UpperCamelCase_          =		init_std  # Normal(0, this parameter)
         UpperCamelCase_          =		activation_function

         UpperCamelCase_          =		DecoderConfig(vocab_size=_lowercase						,		bos_token_id=_lowercase     )
         if "decoder" in common_kwargs:
             del common_kwargs["decoder"]

         UpperCamelCase_          =		scale_embedding  # scale factor will be sqrt(d_model) if True

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

         UpperCamelCase_          =		use_cache
         super().__init__(
             pad_token_id=_lowercase						,		bos_token_id=_lowercase						,		eos_token_id=_lowercase						,		decoder_start_token_id=_lowercase						,		is_encoder_decoder=_lowercase						,		tie_word_embeddings=_lowercase						,		forced_eos_token_id=_lowercase						,		max_length=_lowercase						,		num_beams=_lowercase						,		length_penalty=_lowercase						,		early_stopping=_lowercase						,		**_lowercase						,		)






     def      UpperCAmelCase_							(							self     )->			Tuple:
         UpperCamelCase_          =		copy.deepcopy(self.__dict__     )
         UpperCamelCase_          =		self.decoder.to_dict()
         UpperCamelCase_          =		self.__class__.model_type
         return output



class 		__magic_name__ :






     def __init__(							self     )->			int:
         UpperCamelCase_          =		[0]
         UpperCamelCase_          =		0






     def      UpperCAmelCase_							(							self						,		_lowercase     )->			None:
         UpperCamelCase_          =		self.__heap[i]
         while i // 2 > 0:
             if self.__heap[i] > self.__heap[i // 2]:
                 UpperCamelCase_          =		self.__heap[i // 2]
                 UpperCamelCase_          =		temporary
             i //= 2






     def      UpperCAmelCase_							(							self						,		_lowercase     )->			None:
         self.__heap.append(_lowercase     )
         self.__size += 1
         self.__swap_up(self.__size     )






     def      UpperCAmelCase_							(							self						,		_lowercase     )->			None:
         while self.__size >= 2 * i:
             if 2 * i + 1 > self.__size:
                 UpperCamelCase_          =		2 * i
             else:
                 if self.__heap[2 * i] > self.__heap[2 * i + 1]:
                     UpperCamelCase_          =		2 * i
                 else:
                     UpperCamelCase_          =		2 * i + 1
             UpperCamelCase_          =		self.__heap[i]
             if self.__heap[i] < self.__heap[bigger_child]:
                 UpperCamelCase_          =		self.__heap[bigger_child]
                 UpperCamelCase_          =		temporary
             UpperCamelCase_          =		bigger_child






     def      UpperCAmelCase_							(							self     )->			int:
         UpperCamelCase_          =		self.__heap[1]
         UpperCamelCase_          =		self.__heap[self.__size]
         self.__size -= 1
         self.__heap.pop()
         self.__swap_down(1     )
         return max_value






     @property
     def      UpperCAmelCase_							(							self     )->			List[Any]:
         return self.__heap[1:]






     def __len__(							self     )->			List[str]:
         return self.__size


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 # create an instance of BinaryHeap
 SCREAMING_SNAKE_CASE						:Optional[int]      =			BinaryHeap()
 binary_heap.insert(6)
 binary_heap.insert(10)
 binary_heap.insert(15)
 binary_heap.insert(12)
 # pop root(max-values because it is max heap)
 print(binary_heap.pop())  # 15
 print(binary_heap.pop())  # 12
 # get the list and size after operations
 print(binary_heap.get_list)
 print(len(binary_heap))
