





from typing import List, Union

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


_UpperCamelCase    =	logging.get_logger(__name__)

_UpperCamelCase    =	{
    '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/config.json''',
    # See all LED models at https://huggingface.co/models?filter=led
}




class 			_lowerCamelCase	(      a      ):



      """simple docstring"""






      UpperCAmelCase_  : str				      ="led"
      UpperCAmelCase_  : List[Any]				      ={
          "num_attention_heads": "encoder_attention_heads",
          "hidden_size": "d_model",
          "attention_probs_dropout_prob": "attention_dropout",
          "initializer_range": "init_std",
      }







      def __init__(	self			,  UpperCAmelCase=50265			,  UpperCAmelCase=16384			,  UpperCAmelCase=1024			,  UpperCAmelCase=12			,  UpperCAmelCase=4096			,  UpperCAmelCase=16			,  UpperCAmelCase=12			,  UpperCAmelCase=4096			,  UpperCAmelCase=16			,  UpperCAmelCase=0.0			,  UpperCAmelCase=0.0			,  UpperCAmelCase=True			,  UpperCAmelCase=True			,  UpperCAmelCase="gelu"			,  UpperCAmelCase=1024			,  UpperCAmelCase=0.1			,  UpperCAmelCase=0.0			,  UpperCAmelCase=0.0			,  UpperCAmelCase=0.02			,  UpperCAmelCase=2			,  UpperCAmelCase=0.0			,  UpperCAmelCase=1			,  UpperCAmelCase=0			,  UpperCAmelCase=2			,  UpperCAmelCase = 512			,  **UpperCAmelCase			,  )    ->				List[Any]:






        '''simple docstring'''






        __snake_case				:			Any            =    vocab_size
        __snake_case				:			str            =    max_encoder_position_embeddings
        __snake_case				:			str            =    max_decoder_position_embeddings
        __snake_case				:			Union[str, Any]            =    d_model
        __snake_case				:			Tuple            =    encoder_ffn_dim
        __snake_case				:			List[str]            =    encoder_layers
        __snake_case				:			List[Any]            =    encoder_attention_heads
        __snake_case				:			str            =    decoder_ffn_dim
        __snake_case				:			List[Any]            =    decoder_layers
        __snake_case				:			int            =    decoder_attention_heads
        __snake_case				:			Optional[Any]            =    dropout
        __snake_case				:			Tuple            =    attention_dropout
        __snake_case				:			Union[str, Any]            =    activation_dropout
        __snake_case				:			List[str]            =    activation_function
        __snake_case				:			Optional[int]            =    init_std
        __snake_case				:			Dict            =    encoder_layerdrop
        __snake_case				:			int            =    decoder_layerdrop
        __snake_case				:			Tuple            =    classifier_dropout
        __snake_case				:			Any            =    use_cache
        __snake_case				:			List[Any]            =    encoder_layers
        __snake_case				:			Any            =    attention_window

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








import warnings

from ...utils import logging
from .image_processing_maskformer import MaskFormerImageProcessor


_UpperCamelCase    =	logging.get_logger(__name__)




class 			_lowerCamelCase	(      a      ):



      """simple docstring"""






      def __init__(	self			,  *UpperCAmelCase			,  **UpperCAmelCase				)    ->				None:






        '''simple docstring'''






        warnings.warn(
            "The class MaskFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
            " Please use MaskFormerImageProcessor instead."			,  UpperCAmelCase			,  )
        super().__init__(*UpperCAmelCase			,  **UpperCAmelCase				)

