

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


__a						:int            = logging.get_logger(__name__)

__a						:int            = {
    'facebook/opt-125m': 'https://huggingface.co/facebook/opt-125m/blob/main/config.json',
    'facebook/opt-350m': 'https://huggingface.co/facebook/opt-350m/blob/main/config.json',
    'facebook/opt-1.3b': 'https://huggingface.co/facebook/opt-1.3b/blob/main/config.json',
    'facebook/opt-2.7b': 'https://huggingface.co/facebook/opt-2.7b/blob/main/config.json',
    'facebook/opt-6.7b': 'https://huggingface.co/facebook/opt-6.7b/blob/main/config.json',
    'facebook/opt-13b': 'https://huggingface.co/facebook/opt-13b/blob/main/config.json',
}

class      _a				( snake_case_							):




      """simple docstring"""

      _lowerCamelCase					: int					=					'opt'
      _lowerCamelCase					: Tuple					=					['past_key_values']





      def __init__(      self       :							Optional[int]	, UpperCAmelCase       :							Any=50272	, UpperCAmelCase       :							Union[str, Any]=768	, UpperCAmelCase       :							Tuple=12	, UpperCAmelCase       :							Tuple=3072	, UpperCAmelCase       :							List[str]=2048	, UpperCAmelCase       :							int=True	, UpperCAmelCase       :							int=False	, UpperCAmelCase       :							str=None	, UpperCAmelCase       :							int=0.1	, UpperCAmelCase       :							Optional[Any]=0.0	, UpperCAmelCase       :							Dict=12	, UpperCAmelCase       :							Tuple="relu"	, UpperCAmelCase       :							List[Any]=0.0	, UpperCAmelCase       :							Dict=0.02	, UpperCAmelCase       :							Dict=True	, UpperCAmelCase       :							List[Any]=1	, UpperCAmelCase       :							Dict=2	, UpperCAmelCase       :							Optional[int]=2	, UpperCAmelCase       :							int=True	, UpperCAmelCase       :							List[str]=True	, **UpperCAmelCase       :							Any	, ):
            super().__init__(
                pad_token_id=UpperCAmelCase	, bos_token_id=UpperCAmelCase	, eos_token_id=UpperCAmelCase	, **UpperCAmelCase	, )
            A_	     =							vocab_size
            A_	     =							max_position_embeddings
            A_	     =							num_attention_heads
            A_	     =							word_embed_proj_dim if word_embed_proj_dim is not None else hidden_size
            A_	     =							ffn_dim
            A_	     =							hidden_size
            A_	     =							num_hidden_layers
            A_	     =							dropout
            A_	     =							attention_dropout
            A_	     =							activation_function
            A_	     =							init_std
            A_	     =							layerdrop
            A_	     =							use_cache
            A_	     =							do_layer_norm_before
            # We keep these variables at `True` for backward compatibility.
            A_	     =							enable_bias
            A_	     =							layer_norm_elementwise_affine

            # Note that the only purpose of `_remove_final_layer_norm` is to keep backward compatibility
            # with checkpoints that have been fine-tuned before transformers v4.20.1
            # see https://github.com/facebookresearch/metaseq/pull/164
            A_	     =							_remove_final_layer_norm


import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


__a						:Optional[int]            = logging.get_logger(__name__)

class      _a				( snake_case_							):




      """simple docstring"""

      def __init__(      self       :							List[Any]	, *UpperCAmelCase       :							Any	, **UpperCAmelCase       :							int  ):
            warnings.warn(
                "The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
                " Please use MobileNetV2ImageProcessor instead."	, UpperCAmelCase	, )
            super().__init__(*UpperCAmelCase	, **UpperCAmelCase  )