

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 		__SCREAMING_SNAKE_CASE       ( lowercase__			):
				lowerCamelCase_							=						'mvp'
				lowerCamelCase_							=						['past_key_values']
				lowerCamelCase_							=						{'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}







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








'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase_							=					{"""configuration_plbart""": ["""PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PLBartConfig"""]}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_							=					["""PLBartTokenizer"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_							=					[
							    """PLBART_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """PLBartForCausalLM""",
							    """PLBartForConditionalGeneration""",
							    """PLBartForSequenceClassification""",
							    """PLBartModel""",
							    """PLBartPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_plbart import PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP, PLBartConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_plbart import PLBartTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_plbart import (
														    PLBART_PRETRAINED_MODEL_ARCHIVE_LIST,
														    PLBartForCausalLM,
														    PLBartForConditionalGeneration,
														    PLBartForSequenceClassification,
														    PLBartModel,
														    PLBartPreTrainedModel,
														)


else:
							import sys

							UpperCamelCase_							=					_LazyModule(__name__, globals()["""__file__"""], _import_structure)





