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


__lowerCAmelCase     :	int       			=  logging.get_logger(__name__)

__lowerCAmelCase     :	Optional[Any]       			=  {
    'edbeeching/decision-transformer-gym-hopper-medium': (
        'https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json'
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}




class 			UpperCAmelCase_     (					_UpperCamelCase	):


  '''simple docstring'''







  a__       			=						'decision_transformer'
  a__       			=						['past_key_values']
  a__       			=						{
      'max_position_embeddings': 'n_positions',
      'num_attention_heads': 'n_head',
      'num_hidden_layers': 'n_layer',
  }
  def __init__(					self     :					Optional[int]     ,				UpperCamelCase__     :					Tuple=17     ,				UpperCamelCase__     :					Any=4     ,				UpperCamelCase__     :					List[Any]=128     ,				UpperCamelCase__     :					Optional[int]=4096     ,				UpperCamelCase__     :					List[str]=True     ,				UpperCamelCase__     :					List[str]=1     ,				UpperCamelCase__     :					List[Any]=1024     ,				UpperCamelCase__     :					Dict=3     ,				UpperCamelCase__     :					Tuple=1     ,				UpperCamelCase__     :					Any=None     ,				UpperCamelCase__     :					List[str]="relu"     ,				UpperCamelCase__     :					List[str]=0.1     ,				UpperCamelCase__     :					Any=0.1     ,				UpperCamelCase__     :					List[Any]=0.1     ,				UpperCamelCase__     :					Union[str, Any]=1E-5     ,				UpperCamelCase__     :					Dict=0.02     ,				UpperCamelCase__     :					Optional[Any]=True     ,				UpperCamelCase__     :					Optional[Any]=True     ,				UpperCamelCase__     :					List[Any]=5_0256     ,				UpperCamelCase__     :					Optional[int]=5_0256     ,				UpperCamelCase__     :					Tuple=False     ,				UpperCamelCase__     :					List[Any]=False     ,				**UpperCamelCase__     :					Dict     ,				)     ->      Optional[int]:







    """simple docstring"""






    __magic_name__								=			state_dim
    __magic_name__								=			act_dim
    __magic_name__								=			hidden_size
    __magic_name__								=			max_ep_len
    __magic_name__								=			action_tanh
    __magic_name__								=			vocab_size
    __magic_name__								=			n_positions
    __magic_name__								=			n_layer
    __magic_name__								=			n_head
    __magic_name__								=			n_inner
    __magic_name__								=			activation_function
    __magic_name__								=			resid_pdrop
    __magic_name__								=			embd_pdrop
    __magic_name__								=			attn_pdrop
    __magic_name__								=			layer_norm_epsilon
    __magic_name__								=			initializer_range
    __magic_name__								=			scale_attn_weights
    __magic_name__								=			use_cache
    __magic_name__								=			scale_attn_by_inverse_layer_idx
    __magic_name__								=			reorder_and_upcast_attn

    __magic_name__								=			bos_token_id
    __magic_name__								=			eos_token_id

    super().__init__(bos_token_id=_UpperCAmelCase     ,				eos_token_id=_UpperCAmelCase     ,				**_UpperCAmelCase       )






'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


__lowerCAmelCase		     =  logging.get_logger(__name__)

class       __magic_name__		(       _UpperCamelCase  ):







							def __init__(				self   :			Optional[int]      ,*_UpperCAmelCase   :			List[Any]      ,**_UpperCAmelCase   :			Union[str, Any]						):
									warnings.warn(
									    'The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
									    ' use GLPNImageProcessor instead.'      ,_UpperCAmelCase      ,)
									super().__init__(*_UpperCAmelCase      ,**_UpperCAmelCase						)




