



"""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   UpperCAmelCase__		(   UpperCamelCase  ):
		lowerCAmelCase_							:						Dict							=  """prophetnet"""
		lowerCAmelCase_							:						str							=  ["""past_key_values"""]
		lowerCAmelCase_							:						Optional[int]							=  {
		    """num_attention_heads""": """num_encoder_attention_heads""",
		}



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






									'''simple docstring'''

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

									# parameters for prophetnet
									A    =       ngram
									A    =       num_buckets
									A    =       relative_max_distance
									A    =       disable_ngram_loss
									A    =       eps

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

									A    =       use_cache

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



		@property
		def        A_		(			self	:     int					)      ->    int:






									'''simple docstring'''

									return self.num_encoder_layers + self.num_decoder_layers



		@num_hidden_layers.setter
		def        A_		(			self	:     str   ,				snake_case	:     Tuple					)      ->    Tuple:






									'''simple docstring'''

									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 collections import namedtuple

A     =      namedtuple('from_to', 'from_ to')

A     =      {
    'millimeter': 'mm',
    'centimeter': 'cm',
    'meter': 'm',
    'kilometer': 'km',
    'inch': 'in',
    'inche': 'in',  # Trailing 's' has been stripped off
    'feet': 'ft',
    'foot': 'ft',
    'yard': 'yd',
    'mile': 'mi',
}

A     =      {
    'mm': from_to(0.001, 1_0_0_0),
    'cm': from_to(0.01, 1_0_0),
    'm': from_to(1, 1),
    'km': from_to(1_0_0_0, 0.001),
    'in': from_to(0.0254, 39.3701),
    'ft': from_to(0.3048, 3.2_8084),
    'yd': from_to(0.9144, 1.0_9361),
    'mi': from_to(1609.34, 0.0_0062_1371),
}

def 	lowerCAmelCase__      (  lowerCamelCase__					,   lowerCamelCase__					,   lowerCamelCase__      )			->				float:
							A    =       from_type.lower().rstrip('s'      )
							A    =       TYPE_CONVERSION.get(lowerCamelCase__					,   lowerCamelCase__      )
							A    =       to_type.lower().rstrip('s'      )
							A    =       TYPE_CONVERSION.get(lowerCamelCase__					,   lowerCamelCase__      )
							if new_from not in METRIC_CONVERSION:
														A    =       (
														    f"""Invalid 'from_type' value: {from_type!r}.\n"""
														    f"""Conversion abbreviations are: {', '.join(lowerCamelCase__      )}"""
														)
														raise ValueError(lowerCamelCase__      )
							if new_to not in METRIC_CONVERSION:
														A    =       (
														    f"""Invalid 'to_type' value: {to_type!r}.\n"""
														    f"""Conversion abbreviations are: {', '.join(lowerCamelCase__      )}"""
														)
														raise ValueError(lowerCamelCase__      )
							return value * METRIC_CONVERSION[new_from].from_ * METRIC_CONVERSION[new_to].to


if __name__ == "__main__":
							import doctest

							doctest.testmod()



