


"""simple docstring"""







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


a__    :							int            =					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 			UpperCamelCase_     (			UpperCamelCase):

	"""simple docstring"""





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




	def __init__(			self      :    List[Any]      ,      UpperCAmelCase__      :    Tuple=1_0_0      ,      UpperCAmelCase__      :    Optional[int]=5      ,      UpperCAmelCase__      :    Optional[Any]=1      ,      UpperCAmelCase__      :    Dict=1      ,      UpperCAmelCase__      :    List[str]=2_4_9      ,      UpperCAmelCase__      :    int=6      ,      UpperCAmelCase__      :    Any=1_7      ,      UpperCAmelCase__      :    Any=2_5      ,      UpperCAmelCase__      :    Dict=4      ,      UpperCAmelCase__      :    Tuple=4      ,      UpperCAmelCase__      :    Optional[int]=1_2_8      ,      UpperCAmelCase__      :    List[str]=0.1      ,      UpperCAmelCase__      :    Optional[Any]=0.1      ,      UpperCAmelCase__      :    List[Any]=0.1      ,      UpperCAmelCase__      :    Union[str, Any]=0.0_006      ,      UpperCAmelCase__      :    Dict=5_1_2      ,      UpperCAmelCase__      :    int=0.02      ,      UpperCAmelCase__      :    Tuple=1E-12      ,      UpperCAmelCase__      :    List[Any]=1      ,      UpperCAmelCase__      :    List[str]=True      ,      UpperCAmelCase__      :    int=1      ,      UpperCAmelCase__      :    Optional[Any]=5_0_2_5_6      ,      UpperCAmelCase__      :    Dict=5_0_2_5_6      ,      **UpperCAmelCase__      :    int      ,      )	->     Optional[Any]:
						__SCREAMING_SNAKE_CASE						       =    vocab_size
						__SCREAMING_SNAKE_CASE						       =    action_weight
						__SCREAMING_SNAKE_CASE						       =    reward_weight
						__SCREAMING_SNAKE_CASE						       =    value_weight
						__SCREAMING_SNAKE_CASE						       =    max_position_embeddings
						__SCREAMING_SNAKE_CASE						       =    block_size
						__SCREAMING_SNAKE_CASE						       =    action_dim
						__SCREAMING_SNAKE_CASE						       =    observation_dim
						__SCREAMING_SNAKE_CASE						       =    transition_dim
						__SCREAMING_SNAKE_CASE						       =    learning_rate
						__SCREAMING_SNAKE_CASE						       =    n_layer
						__SCREAMING_SNAKE_CASE						       =    n_head
						__SCREAMING_SNAKE_CASE						       =    n_embd
						__SCREAMING_SNAKE_CASE						       =    embd_pdrop
						__SCREAMING_SNAKE_CASE						       =    attn_pdrop
						__SCREAMING_SNAKE_CASE						       =    resid_pdrop
						__SCREAMING_SNAKE_CASE						       =    initializer_range
						__SCREAMING_SNAKE_CASE						       =    layer_norm_eps
						__SCREAMING_SNAKE_CASE						       =    kaiming_initializer_range
						__SCREAMING_SNAKE_CASE						       =    use_cache
						super().__init__(pad_token_id=UpperCAmelCase__      ,      bos_token_id=UpperCAmelCase__      ,      eos_token_id=UpperCAmelCase__      ,      **UpperCAmelCase__       )




"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import _LazyModule


a__    :							Optional[int]            =					{'''tokenization_byt5''': ['''ByT5Tokenizer''']}


if TYPE_CHECKING:
		from .tokenization_byta import ByTaTokenizer
else:
		import sys

		a__    :							Any            =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
