





from typing import Callable, Optional, Union

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


snake_case_				=      logging.get_logger(__name__)

snake_case_				=      {
    '''microsoft/prophetnet-large-uncased''': (
        '''https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json'''
    ),
}
class 							snake_case_		(      _A):
		lowerCamelCase     :Tuple							=  "prophetnet"
		lowerCamelCase     :str							=  ["past_key_values"]
		lowerCamelCase     :Optional[Any]							=  {
		    "num_attention_heads": "num_encoder_attention_heads",
		}







		def __init__(		self      ,  __lowercase = 0.1      ,  __lowercase = "gelu"      ,  __lowercase = 3_0_5_2_2      ,  __lowercase = 1_0_2_4      ,  __lowercase = 4_0_9_6      ,  __lowercase = 1_2      ,  __lowercase = 1_6      ,  __lowercase = 4_0_9_6      ,  __lowercase = 1_2      ,  __lowercase = 1_6      ,  __lowercase = 0.1      ,  __lowercase = 0.1      ,  __lowercase = 5_1_2      ,  __lowercase = 0.0_2      ,  __lowercase = True      ,  __lowercase = True      ,  __lowercase = 0      ,  __lowercase = 2      ,  __lowercase = 3_2      ,  __lowercase = 1_2_8      ,  __lowercase = False      ,  __lowercase = 0.0      ,  __lowercase = True      ,  __lowercase = 0      ,  __lowercase = 1      ,  __lowercase = 2      ,  **__lowercase      ,  )					-> Union[str, Any]:
				lowerCamelCase :			Union[str, Any]    		=vocab_size
				lowerCamelCase :			Optional[Any]    		=hidden_size
				lowerCamelCase :			List[str]    		=encoder_ffn_dim
				lowerCamelCase :			Tuple    		=num_encoder_layers
				lowerCamelCase :			Any    		=num_encoder_attention_heads
				lowerCamelCase :			List[str]    		=decoder_ffn_dim
				lowerCamelCase :			Any    		=num_decoder_layers
				lowerCamelCase :			Tuple    		=num_decoder_attention_heads
				lowerCamelCase :			Optional[Any]    		=max_position_embeddings
				lowerCamelCase :			Dict    		=init_std  # Normal(0, this parameter)
				lowerCamelCase :			Optional[Any]    		=activation_function

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

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

				lowerCamelCase :			List[Any]    		=use_cache

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







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







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








def        A__						(							SCREAMING_SNAKE_CASE_ = 1_0_0_0		) ->  int:
		lowerCamelCase :			Dict    		=[]
		lowerCamelCase :			Dict    		=[]
		lowerCamelCase :			Union[str, Any]    		=3
		lowerCamelCase :			List[str]    		=5
		lowerCamelCase :			Union[str, Any]    		=1
		while True:
				lowerCamelCase :			Dict    		=z * temp
				if result < n:
						zmulti.append(SCREAMING_SNAKE_CASE_		)
						temp += 1
				else:
						lowerCamelCase :			List[Any]    		=1
						break
		while True:
				lowerCamelCase :			Optional[Any]    		=x * temp
				if result < n:
						xmulti.append(SCREAMING_SNAKE_CASE_		)
						temp += 1
				else:
						break
		lowerCamelCase :			str    		=list(set(xmulti + zmulti		)		)
		return sum(SCREAMING_SNAKE_CASE_		)


if __name__ == "__main__":
				print(F"""{solution() = }""")

