


import warnings

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


_snake_case	:						Tuple         =							logging.get_logger(__name__)

_snake_case	:						Optional[int]         =							{
    "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json",
}

class 							a						(_lowerCAmelCase ):




							"""simple docstring"""


							__UpperCAmelCase       :				Optional[int]	    =    "mvp"
							__UpperCAmelCase       :				Optional[int]	    =    ["past_key_values"]
							__UpperCAmelCase       :				Optional[Any]	    =    {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}

							def __init__(				self			:    Union[str, Any]       ,      lowerCamelCase			:    str=50267       ,      lowerCamelCase			:    str=1024       ,      lowerCamelCase			:    Any=12       ,      lowerCamelCase			:    List[str]=4096       ,      lowerCamelCase			:    Dict=16       ,      lowerCamelCase			:    Optional[Any]=12       ,      lowerCamelCase			:    List[Any]=4096       ,      lowerCamelCase			:    Dict=16       ,      lowerCamelCase			:    Any=0.0       ,      lowerCamelCase			:    List[str]=0.0       ,      lowerCamelCase			:    Dict="gelu"       ,      lowerCamelCase			:    Optional[Any]=1024       ,      lowerCamelCase			:    Optional[int]=0.1       ,      lowerCamelCase			:    List[Any]=0.0       ,      lowerCamelCase			:    str=0.0       ,      lowerCamelCase			:    Any=0.02       ,      lowerCamelCase			:    Any=0.0       ,      lowerCamelCase			:    Dict=False       ,      lowerCamelCase			:    Optional[Any]=True       ,      lowerCamelCase			:    List[Any]=1       ,      lowerCamelCase			:    Tuple=0       ,      lowerCamelCase			:    Optional[int]=2       ,      lowerCamelCase			:    Union[str, Any]=True       ,      lowerCamelCase			:    Any=2       ,      lowerCamelCase			:    Union[str, Any]=2       ,      lowerCamelCase			:    Tuple=False       ,      lowerCamelCase			:    str=100       ,      lowerCamelCase			:    int=800       ,      **lowerCamelCase			:    Optional[int]       ,      )      ->       Any:
														__snake_case						:     Tuple									=  vocab_size
														__snake_case						:     Union[str, Any]									=  max_position_embeddings
														__snake_case						:     Union[str, Any]									=  d_model
														__snake_case						:     List[str]									=  encoder_ffn_dim
														__snake_case						:     Tuple									=  encoder_layers
														__snake_case						:     Dict									=  encoder_attention_heads
														__snake_case						:     str									=  decoder_ffn_dim
														__snake_case						:     Optional[int]									=  decoder_layers
														__snake_case						:     Optional[int]									=  decoder_attention_heads
														__snake_case						:     List[str]									=  dropout
														__snake_case						:     Dict									=  attention_dropout
														__snake_case						:     int									=  activation_dropout
														__snake_case						:     Optional[int]									=  activation_function
														__snake_case						:     Any									=  init_std
														__snake_case						:     Any									=  encoder_layerdrop
														__snake_case						:     Optional[int]									=  decoder_layerdrop
														__snake_case						:     Dict									=  classifier_dropout
														__snake_case						:     Union[str, Any]									=  use_cache
														__snake_case						:     List[Any]									=  encoder_layers
														__snake_case						:     List[Any]									=  scale_embedding  # scale factor will be sqrt(d_model) if True
														__snake_case						:     List[str]									=  use_prompt
														__snake_case						:     Union[str, Any]									=  prompt_length
														__snake_case						:     int									=  prompt_mid_dim

														super().__init__(
														    pad_token_id=lowerCamelCase       ,      bos_token_id=lowerCamelCase       ,      eos_token_id=lowerCamelCase       ,      is_encoder_decoder=lowerCamelCase       ,      decoder_start_token_id=lowerCamelCase       ,      forced_eos_token_id=lowerCamelCase       ,      **lowerCamelCase       ,      )

														if self.forced_bos_token_id is None and kwargs.get("force_bos_token_to_be_generated"       ,      lowerCamelCase							):
																					__snake_case						:     Any									=  self.bos_token_id
																					warnings.warn(
																					    F'Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. '
																					    "The config can simply be saved and uploaded again to be fixed."							)



def 				SCREAMING_SNAKE_CASE_   (      UpperCamelCase__			,		UpperCamelCase__ = " "		):
      UpperCamelCase__     : Optional[int]											=					[]

      UpperCamelCase__     : int											=					0
      for index, char in enumerate(UpperCamelCase__		):
            if char == separator:
                  split_words.append(string[last_index:index]		)
                  UpperCamelCase__     : int											=					index + 1
            elif index + 1 == len(UpperCamelCase__		):
                  split_words.append(string[last_index : index + 1]		)
      return split_words


if __name__ == "__main__":
    from doctest import testmod

    testmod()


