




"""simple docstring"""





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


A				=							logging.get_logger(__name__)

A				=							{
    """tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
        """https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json"""
    ),
}



class   a__					(						__magic_name__ ):
			lowercase_		=						"gptsan-japanese"
			lowercase_		=						[
			    "past_key_values",
			]
			lowercase_		=						{
			    "hidden_size": "d_model",
			    "num_attention_heads": "num_heads",
			    "num_hidden_layers": "num_layers",
			}


			def __init__(   self   :     Any   ,	UpperCamelCase_   :     List[Any]=36000   ,	UpperCamelCase_   :     Optional[Any]=1280   ,	UpperCamelCase_   :     Optional[int]=1024   ,	UpperCamelCase_   :     Dict=8192   ,	UpperCamelCase_   :     Optional[int]=4096   ,	UpperCamelCase_   :     Union[str, Any]=128   ,	UpperCamelCase_   :     Dict=10   ,	UpperCamelCase_   :     Optional[Any]=0   ,	UpperCamelCase_   :     Union[str, Any]=16   ,	UpperCamelCase_   :     List[Any]=16   ,	UpperCamelCase_   :     List[str]=128   ,	UpperCamelCase_   :     List[str]=0.0   ,	UpperCamelCase_   :     str=1e-5   ,	UpperCamelCase_   :     Tuple=False   ,	UpperCamelCase_   :     Dict=0.0   ,	UpperCamelCase_   :     Tuple="float32"   ,	UpperCamelCase_   :     Optional[Any]=False   ,	UpperCamelCase_   :     Optional[Any]=False   ,	UpperCamelCase_   :     Optional[int]=False   ,	UpperCamelCase_   :     int=0.002   ,	UpperCamelCase_   :     List[str]=False   ,	UpperCamelCase_   :     Optional[int]=True   ,	UpperCamelCase_   :     List[Any]=35998   ,	UpperCamelCase_   :     str=35995   ,	UpperCamelCase_   :     Optional[int]=35999   ,	**UpperCamelCase_   :     Dict   ,	):


						"""simple docstring"""




						__UpperCAmelCase						:			Tuple												=       vocab_size
						__UpperCAmelCase						:			Union[str, Any]												=       max_position_embeddings
						__UpperCAmelCase						:			str												=       d_model
						__UpperCAmelCase						:			Optional[Any]												=       d_ff
						__UpperCAmelCase						:			Optional[Any]												=       d_ext
						__UpperCAmelCase						:			Any												=       d_spout
						__UpperCAmelCase						:			Dict												=       num_switch_layers
						__UpperCAmelCase						:			Any												=       num_ext_layers
						__UpperCAmelCase						:			List[str]												=       num_switch_layers + num_ext_layers
						__UpperCAmelCase						:			List[str]												=       num_heads
						__UpperCAmelCase						:			Optional[int]												=       num_experts
						__UpperCAmelCase						:			List[Any]												=       expert_capacity
						__UpperCAmelCase						:			List[str]												=       dropout_rate
						__UpperCAmelCase						:			Union[str, Any]												=       layer_norm_epsilon
						__UpperCAmelCase						:			List[Any]												=       router_bias
						__UpperCAmelCase						:			Tuple												=       router_jitter_noise
						__UpperCAmelCase						:			Any												=       router_dtype
						__UpperCAmelCase						:			List[str]												=       router_ignore_padding_tokens
						__UpperCAmelCase						:			int												=       output_hidden_states
						__UpperCAmelCase						:			Dict												=       output_attentions
						__UpperCAmelCase						:			List[Any]												=       initializer_factor
						__UpperCAmelCase						:			Dict												=       output_router_logits
						__UpperCAmelCase						:			Optional[int]												=       use_cache

						super().__init__(
						    separator_token_id=UpperCamelCase_   ,	pad_token_id=UpperCamelCase_   ,	eos_token_id=UpperCamelCase_   ,	**UpperCamelCase_   ,	)









'''simple docstring'''




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


_SCREAMING_SNAKE_CASE							     =			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							     =			{
    "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		(			A__	):






     """simple docstring"""






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



     def __init__(   self							:			Optional[Any]   ,       __snake_case							:			int=1_00   ,       __snake_case							:			List[str]=5   ,       __snake_case							:			str=1   ,       __snake_case							:			Union[str, Any]=1   ,       __snake_case							:			Union[str, Any]=2_49   ,       __snake_case							:			List[Any]=6   ,       __snake_case							:			Optional[int]=17   ,       __snake_case							:			Optional[Any]=25   ,       __snake_case							:			Union[str, Any]=4   ,       __snake_case							:			List[Any]=4   ,       __snake_case							:			Optional[int]=1_28   ,       __snake_case							:			Optional[Any]=0.1   ,       __snake_case							:			Any=0.1   ,       __snake_case							:			int=0.1   ,       __snake_case							:			Union[str, Any]=0.00_06   ,       __snake_case							:			Tuple=5_12   ,       __snake_case							:			int=0.02   ,       __snake_case							:			Any=1e-12   ,       __snake_case							:			Optional[Any]=1   ,       __snake_case							:			List[Any]=True   ,       __snake_case							:			Dict=1   ,       __snake_case							:			Dict=5_02_56   ,       __snake_case							:			Union[str, Any]=5_02_56   ,       **__snake_case							:			Tuple   ,       )->	Optional[int]:
        snake_case 						=   vocab_size
        snake_case 						=   action_weight
        snake_case 						=   reward_weight
        snake_case 						=   value_weight
        snake_case 						=   max_position_embeddings
        snake_case 						=   block_size
        snake_case 						=   action_dim
        snake_case 						=   observation_dim
        snake_case 						=   transition_dim
        snake_case 						=   learning_rate
        snake_case 						=   n_layer
        snake_case 						=   n_head
        snake_case 						=   n_embd
        snake_case 						=   embd_pdrop
        snake_case 						=   attn_pdrop
        snake_case 						=   resid_pdrop
        snake_case 						=   initializer_range
        snake_case 						=   layer_norm_eps
        snake_case 						=   kaiming_initializer_range
        snake_case 						=   use_cache
        super().__init__(pad_token_id=__snake_case   ,       bos_token_id=__snake_case   ,       eos_token_id=__snake_case   ,       **__snake_case						)

