





'''simple docstring'''

import warnings

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


__lowerCAmelCase							:     Optional[Any]		     =    logging.get_logger(__name__)

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






class        UpperCAmelCase     (	UpperCamelCase__    ):
 __lowercase       		=    """mvp"""
 __lowercase       		=    ["""past_key_values"""]
 __lowercase       		=    {"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}
 def __init__(    self				:List[str]						,	lowercase_				:Optional[int]=5_02_67						,	lowercase_				:str=10_24						,	lowercase_				:Dict=12						,	lowercase_				:List[Any]=40_96						,	lowercase_				:Dict=16						,	lowercase_				:Any=12						,	lowercase_				:Union[str, Any]=40_96						,	lowercase_				:Optional[Any]=16						,	lowercase_				:List[str]=0.0						,	lowercase_				:int=0.0						,	lowercase_				:Optional[Any]="gelu"						,	lowercase_				:Dict=10_24						,	lowercase_				:List[Any]=0.1						,	lowercase_				:Optional[Any]=0.0						,	lowercase_				:Dict=0.0						,	lowercase_				:Optional[Any]=0.0_2						,	lowercase_				:Dict=0.0						,	lowercase_				:Union[str, Any]=False						,	lowercase_				:Optional[int]=True						,	lowercase_				:Dict=1						,	lowercase_				:Dict=0						,	lowercase_				:List[str]=2						,	lowercase_				:Optional[Any]=True						,	lowercase_				:Optional[Any]=2						,	lowercase_				:Any=2						,	lowercase_				:List[str]=False						,	lowercase_				:Optional[int]=1_00						,	lowercase_				:List[str]=8_00						,	**lowercase_				:Dict						,	)->							List[str]:
     A__    =      vocab_size
     A__    =      max_position_embeddings
     A__    =      d_model
     A__    =      encoder_ffn_dim
     A__    =      encoder_layers
     A__    =      encoder_attention_heads
     A__    =      decoder_ffn_dim
     A__    =      decoder_layers
     A__    =      decoder_attention_heads
     A__    =      dropout
     A__    =      attention_dropout
     A__    =      activation_dropout
     A__    =      activation_function
     A__    =      init_std
     A__    =      encoder_layerdrop
     A__    =      decoder_layerdrop
     A__    =      classifier_dropout
     A__    =      use_cache
     A__    =      encoder_layers
     A__    =      scale_embedding  # scale factor will be sqrt(d_model) if True
     A__    =      use_prompt
     A__    =      prompt_length
     A__    =      prompt_mid_dim

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

     if self.forced_bos_token_id is None and kwargs.get("force_bos_token_to_be_generated"						,	_lowercase							):
         A__    =      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."							)










'''simple docstring'''

__lowerCAmelCase							:     Dict		     ="\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"

__lowerCAmelCase							:     Optional[Any]		     =[{"type": "code", "content": INSTALL_CONTENT}]
__lowerCAmelCase							:     Tuple		     ={
    "{processor_class}": "FakeProcessorClass",
    "{model_class}": "FakeModelClass",
    "{object_class}": "FakeObjectClass",
}



