





"""simple docstring"""




import warnings

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


UpperCamelCase_									=logging.get_logger(__name__)

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




class 			_a						(				_lowerCAmelCase    ):
				UpperCamelCase								=   '''mvp'''
				UpperCamelCase								=   ['''past_key_values''']
				UpperCamelCase								=   {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}






				def __init__(			self		:   List[str],			lowerCAmelCase__		:   List[str]=5_0_2_6_7,			lowerCAmelCase__		:   Tuple=1_0_2_4,			lowerCAmelCase__		:   Optional[Any]=1_2,			lowerCAmelCase__		:   Tuple=4_0_9_6,			lowerCAmelCase__		:   Dict=1_6,			lowerCAmelCase__		:   str=1_2,			lowerCAmelCase__		:   Optional[int]=4_0_9_6,			lowerCAmelCase__		:   str=1_6,			lowerCAmelCase__		:   Tuple=0.0,			lowerCAmelCase__		:   List[Any]=0.0,			lowerCAmelCase__		:   Dict="gelu",			lowerCAmelCase__		:   Any=1_0_2_4,			lowerCAmelCase__		:   Dict=0.1,			lowerCAmelCase__		:   Dict=0.0,			lowerCAmelCase__		:   Any=0.0,			lowerCAmelCase__		:   Tuple=0.02,			lowerCAmelCase__		:   int=0.0,			lowerCAmelCase__		:   Optional[int]=False,			lowerCAmelCase__		:   str=True,			lowerCAmelCase__		:   Optional[int]=1,			lowerCAmelCase__		:   str=0,			lowerCAmelCase__		:   List[Any]=2,			lowerCAmelCase__		:   Optional[Any]=True,			lowerCAmelCase__		:   Optional[int]=2,			lowerCAmelCase__		:   Union[str, Any]=2,			lowerCAmelCase__		:   List[Any]=False,			lowerCAmelCase__		:   List[Any]=1_0_0,			lowerCAmelCase__		:   Optional[int]=8_0_0,			**lowerCAmelCase__		:   Dict,			)     ->				Tuple:




										'''simple docstring'''



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




import warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    """The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
    """ StableDiffusionInpaintPipeline` instead."""
)



