
import warnings

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


lowercase  : List[str]						   =							logging.get_logger(__name__)

lowercase  : Union[str, Any]						   =							{
    """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json""",
}

class __snake_case		(				lowerCAmelCase					):
    _a		:						Any=    "mvp"
    _a		:						Dict=    ["past_key_values"]
    _a		:						Tuple=    {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}
    def __init__(  self		,snake_case=50267		,snake_case=1024		,snake_case=12		,snake_case=4096		,snake_case=16		,snake_case=12		,snake_case=4096		,snake_case=16		,snake_case=0.0		,snake_case=0.0		,snake_case="gelu"		,snake_case=1024		,snake_case=0.1		,snake_case=0.0		,snake_case=0.0		,snake_case=0.02		,snake_case=0.0		,snake_case=False		,snake_case=True		,snake_case=1		,snake_case=0		,snake_case=2		,snake_case=True		,snake_case=2		,snake_case=2		,snake_case=False		,snake_case=100		,snake_case=800		,**snake_case		,):



           '''simple docstring'''







           lowercase							:					Optional[int]	     =				vocab_size
           lowercase							:					Any	     =				max_position_embeddings
           lowercase							:					int	     =				d_model
           lowercase							:					int	     =				encoder_ffn_dim
           lowercase							:					Optional[Any]	     =				encoder_layers
           lowercase							:					Tuple	     =				encoder_attention_heads
           lowercase							:					List[str]	     =				decoder_ffn_dim
           lowercase							:					Any	     =				decoder_layers
           lowercase							:					Union[str, Any]	     =				decoder_attention_heads
           lowercase							:					List[str]	     =				dropout
           lowercase							:					Any	     =				attention_dropout
           lowercase							:					Dict	     =				activation_dropout
           lowercase							:					List[str]	     =				activation_function
           lowercase							:					int	     =				init_std
           lowercase							:					int	     =				encoder_layerdrop
           lowercase							:					str	     =				decoder_layerdrop
           lowercase							:					List[Any]	     =				classifier_dropout
           lowercase							:					Union[str, Any]	     =				use_cache
           lowercase							:					Optional[Any]	     =				encoder_layers
           lowercase							:					Optional[int]	     =				scale_embedding  # scale factor will be sqrt(d_model) if True
           lowercase							:					Union[str, Any]	     =				use_prompt
           lowercase							:					Optional[int]	     =				prompt_length
           lowercase							:					Tuple	     =				prompt_mid_dim

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

           if self.forced_bos_token_id is None and kwargs.get("""force_bos_token_to_be_generated"""		,snake_case				):
                  lowercase							:					Dict	     =				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 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   int:
       assert (
           isinstance(SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    ) and number_of_steps > 0
       ), f"number_of_steps needs to be positive integer, your input {number_of_steps}"
       if number_of_steps == 1:
              return 1
       lowercase     ,      lowercase							:					Tuple	     =				1, 1
       for _ in range(number_of_steps - 1    ):
              lowercase     ,      lowercase							:					str	     =				current + previous, current
       return current


if __name__ == "__main__":
  import doctest

  doctest.testmod()
