


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


a : Optional[Any]		=				logging.get_logger(__name__)

a : Optional[int]		=				{
    '''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 	lowerCamelCase_       (				lowerCAmelCase__				):



					'''simple docstring'''







					__UpperCAmelCase            =				"trajectory_transformer"
					__UpperCAmelCase            =				["past_key_values"]
					__UpperCAmelCase            =				{
					    "hidden_size": "n_embd",
					    "num_attention_heads": "n_head",
					    "num_hidden_layers": "n_layer",
					}






					def __init__(				self ,       snake_case_=1_0_0 ,       snake_case_=5 ,       snake_case_=1 ,       snake_case_=1 ,       snake_case_=2_4_9 ,       snake_case_=6 ,       snake_case_=1_7 ,       snake_case_=2_5 ,       snake_case_=4 ,       snake_case_=4 ,       snake_case_=1_2_8 ,       snake_case_=0.1 ,       snake_case_=0.1 ,       snake_case_=0.1 ,       snake_case_=0.0_0_0_6 ,       snake_case_=5_1_2 ,       snake_case_=0.0_2 ,       snake_case_=1e-1_2 ,       snake_case_=1 ,       snake_case_=True ,       snake_case_=1 ,       snake_case_=5_0_2_5_6 ,       snake_case_=5_0_2_5_6 ,       **snake_case_ ,       )   ->			Tuple:







								'''simple docstring'''

								__lowercase 					=   vocab_size
								__lowercase 					=   action_weight
								__lowercase 					=   reward_weight
								__lowercase 					=   value_weight
								__lowercase 					=   max_position_embeddings
								__lowercase 					=   block_size
								__lowercase 					=   action_dim
								__lowercase 					=   observation_dim
								__lowercase 					=   transition_dim
								__lowercase 					=   learning_rate
								__lowercase 					=   n_layer
								__lowercase 					=   n_head
								__lowercase 					=   n_embd
								__lowercase 					=   embd_pdrop
								__lowercase 					=   attn_pdrop
								__lowercase 					=   resid_pdrop
								__lowercase 					=   initializer_range
								__lowercase 					=   layer_norm_eps
								__lowercase 					=   kaiming_initializer_range
								__lowercase 					=   use_cache
								super().__init__(pad_token_id=snake_case_ ,       bos_token_id=snake_case_ ,       eos_token_id=snake_case_ ,       **snake_case_						)






a : Any		=				'''
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

a : Union[str, Any]		=				[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
a : Union[str, Any]		=				{
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}


