




import warnings

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


__magic_name__  :  List[Any]					=       logging.get_logger(__name__)

__magic_name__  :  str					=       {
    """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json""",
}





class     SCREAMING_SNAKE_CASE__		(_a			):
     lowercase_ :      str				= "mvp"
     lowercase_ :      Any				= ["past_key_values"]
     lowercase_ :      Union[str, Any]				= {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}
     def __init__(						self	:		Optional[Any]       ,						__lowerCamelCase	:		int=5_02_67       ,						__lowerCamelCase	:		List[Any]=10_24       ,						__lowerCamelCase	:		Dict=12       ,						__lowerCamelCase	:		Optional[Any]=40_96       ,						__lowerCamelCase	:		List[str]=16       ,						__lowerCamelCase	:		Optional[Any]=12       ,						__lowerCamelCase	:		Optional[Any]=40_96       ,						__lowerCamelCase	:		int=16       ,						__lowerCamelCase	:		int=0.0       ,						__lowerCamelCase	:		Any=0.0       ,						__lowerCamelCase	:		Optional[Any]="gelu"       ,						__lowerCamelCase	:		Tuple=10_24       ,						__lowerCamelCase	:		str=0.1       ,						__lowerCamelCase	:		int=0.0       ,						__lowerCamelCase	:		Dict=0.0       ,						__lowerCamelCase	:		List[Any]=0.02       ,						__lowerCamelCase	:		int=0.0       ,						__lowerCamelCase	:		Union[str, Any]=False       ,						__lowerCamelCase	:		Dict=True       ,						__lowerCamelCase	:		List[Any]=1       ,						__lowerCamelCase	:		Optional[Any]=0       ,						__lowerCamelCase	:		str=2       ,						__lowerCamelCase	:		Union[str, Any]=True       ,						__lowerCamelCase	:		List[str]=2       ,						__lowerCamelCase	:		Tuple=2       ,						__lowerCamelCase	:		Optional[Any]=False       ,						__lowerCamelCase	:		List[str]=1_00       ,						__lowerCamelCase	:		Dict=8_00       ,						**__lowerCamelCase	:		Dict       ,						):



       """simple docstring"""
       lowerCAmelCase__										=      vocab_size
       lowerCAmelCase__										=      max_position_embeddings
       lowerCAmelCase__										=      d_model
       lowerCAmelCase__										=      encoder_ffn_dim
       lowerCAmelCase__										=      encoder_layers
       lowerCAmelCase__										=      encoder_attention_heads
       lowerCAmelCase__										=      decoder_ffn_dim
       lowerCAmelCase__										=      decoder_layers
       lowerCAmelCase__										=      decoder_attention_heads
       lowerCAmelCase__										=      dropout
       lowerCAmelCase__										=      attention_dropout
       lowerCAmelCase__										=      activation_dropout
       lowerCAmelCase__										=      activation_function
       lowerCAmelCase__										=      init_std
       lowerCAmelCase__										=      encoder_layerdrop
       lowerCAmelCase__										=      decoder_layerdrop
       lowerCAmelCase__										=      classifier_dropout
       lowerCAmelCase__										=      use_cache
       lowerCAmelCase__										=      encoder_layers
       lowerCAmelCase__										=      scale_embedding  # scale factor will be sqrt(d_model) if True
       lowerCAmelCase__										=      use_prompt
       lowerCAmelCase__										=      prompt_length
       lowerCAmelCase__										=      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						):
         lowerCAmelCase__										=      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.'''						)







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__magic_name__  :  Optional[int]					=       {
    """configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
    """tokenization_biogpt""": ["""BioGptTokenizer"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  int					=       [
          """BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """BioGptForCausalLM""",
          """BioGptForTokenClassification""",
          """BioGptForSequenceClassification""",
          """BioGptModel""",
          """BioGptPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
      from .tokenization_biogpt import BioGptTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_biogpt import (
                BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                BioGptForCausalLM,
                BioGptForSequenceClassification,
                BioGptForTokenClassification,
                BioGptModel,
                BioGptPreTrainedModel,
            )


else:
      import sys

      __magic_name__  :  int					=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

