

'''simple docstring'''

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


lowercase__			    =			logging.get_logger(__name__)

lowercase__			    =			{
    "CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
        "https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json"
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}




class        A_ (				_UpperCAmelCase							):






     '''simple docstring'''



     UpperCAmelCase_						:	Any  		=  """trajectory_transformer"""
     UpperCAmelCase_						:	List[str]  		=  ["""past_key_values"""]
     UpperCAmelCase_						:	Optional[int]  		=  {
         """hidden_size""": """n_embd""",
         """num_attention_heads""": """n_head""",
         """num_hidden_layers""": """n_layer""",
     }


     def __init__(		self :     Union[str, Any]     ,			lowercase_ :     Dict=100     ,			lowercase_ :     Union[str, Any]=5     ,			lowercase_ :     Dict=1     ,			lowercase_ :     List[Any]=1     ,			lowercase_ :     Union[str, Any]=249     ,			lowercase_ :     Union[str, Any]=6     ,			lowercase_ :     Union[str, Any]=17     ,			lowercase_ :     List[str]=25     ,			lowercase_ :     str=4     ,			lowercase_ :     Dict=4     ,			lowercase_ :     List[Any]=128     ,			lowercase_ :     Optional[int]=0.1     ,			lowercase_ :     Union[str, Any]=0.1     ,			lowercase_ :     List[str]=0.1     ,			lowercase_ :     Tuple=0.0006     ,			lowercase_ :     int=512     ,			lowercase_ :     int=0.02     ,			lowercase_ :     Optional[Any]=1E-12     ,			lowercase_ :     Any=1     ,			lowercase_ :     Optional[int]=True     ,			lowercase_ :     Optional[int]=1     ,			lowercase_ :     Union[str, Any]=50_256     ,			lowercase_ :     Optional[Any]=50_256     ,			**lowercase_ :     Tuple     ,			)						->	int:
      UpperCAmelCase       :	Optional[Any]											= vocab_size
      UpperCAmelCase       :	int											= action_weight
      UpperCAmelCase       :	Tuple											= reward_weight
      UpperCAmelCase       :	str											= value_weight
      UpperCAmelCase       :	List[Any]											= max_position_embeddings
      UpperCAmelCase       :	Optional[int]											= block_size
      UpperCAmelCase       :	List[Any]											= action_dim
      UpperCAmelCase       :	Union[str, Any]											= observation_dim
      UpperCAmelCase       :	int											= transition_dim
      UpperCAmelCase       :	Union[str, Any]											= learning_rate
      UpperCAmelCase       :	Any											= n_layer
      UpperCAmelCase       :	List[str]											= n_head
      UpperCAmelCase       :	Any											= n_embd
      UpperCAmelCase       :	Dict											= embd_pdrop
      UpperCAmelCase       :	Any											= attn_pdrop
      UpperCAmelCase       :	List[str]											= resid_pdrop
      UpperCAmelCase       :	List[Any]											= initializer_range
      UpperCAmelCase       :	int											= layer_norm_eps
      UpperCAmelCase       :	List[str]											= kaiming_initializer_range
      UpperCAmelCase       :	List[Any]											= use_cache
      super().__init__(pad_token_id=UpperCAmelCase_     ,			bos_token_id=UpperCAmelCase_     ,			eos_token_id=UpperCAmelCase_     ,			**UpperCAmelCase_       )






import random






def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_		)		->		tuple:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__						, SCREAMING_SNAKE_CASE__						, SCREAMING_SNAKE_CASE__													= [], [], []
					for element in data:
										if element < pivot:
															less.append(UpperCamelCase_		)
										elif element > pivot:
															greater.append(UpperCamelCase_		)
										else:
															equal.append(UpperCamelCase_		)
					return less, equal, greater






def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_		)		->		Any:
					'''simple docstring'''


					if index >= len(UpperCamelCase_		) or index < 0:
										return None

					SCREAMING_SNAKE_CASE__													= items[random.randint(0	,	len(UpperCamelCase_		) - 1		)]
					SCREAMING_SNAKE_CASE__													= 0
					SCREAMING_SNAKE_CASE__						, SCREAMING_SNAKE_CASE__						, SCREAMING_SNAKE_CASE__													= _partition(UpperCamelCase_	,	UpperCamelCase_		)
					SCREAMING_SNAKE_CASE__													= len(UpperCamelCase_		)
					SCREAMING_SNAKE_CASE__													= len(UpperCamelCase_		)

					# index is the pivot
					if m <= index < m + count:
										return pivot
					# must be in smaller
					elif m > index:
										return quick_select(UpperCamelCase_	,	UpperCamelCase_		)
					# must be in larger
					else:
										return quick_select(UpperCamelCase_	,	index - (m + count)		)





