

from math import pow, sqrt







def 		_lowercase (     *lowercase__						):
      __lowerCAmelCase					:						Dict					=					len(lowercase__						) > 0 and all(value > 0.0 for value in values						)
      return result







def 		_lowercase (     lowercase__   ,	lowercase__						):
      return (
          round(sqrt(molar_mass_a / molar_mass_a						)   ,	6						)
          if validate(lowercase__   ,	lowercase__						)
          else ValueError('''Input Error: Molar mass values must greater than 0.'''						)
      )







def 		_lowercase (     lowercase__   ,	lowercase__   ,	lowercase__						):
      return (
          round(effusion_rate * sqrt(molar_mass_a / molar_mass_a						)   ,	6						)
          if validate(lowercase__   ,	lowercase__   ,	lowercase__						)
          else ValueError(
              '''Input Error: Molar mass and effusion rate values must greater than 0.'''						)
      )







def 		_lowercase (     lowercase__   ,	lowercase__   ,	lowercase__						):
      return (
          round(effusion_rate / sqrt(molar_mass_a / molar_mass_a						)   ,	6						)
          if validate(lowercase__   ,	lowercase__   ,	lowercase__						)
          else ValueError(
              '''Input Error: Molar mass and effusion rate values must greater than 0.'''						)
      )







def 		_lowercase (     lowercase__   ,	lowercase__   ,	lowercase__						):
      return (
          round(molar_mass / pow(effusion_rate_a / effusion_rate_a   ,	2						)   ,	6						)
          if validate(lowercase__   ,	lowercase__   ,	lowercase__						)
          else ValueError(
              '''Input Error: Molar mass and effusion rate values must greater than 0.'''						)
      )







def 		_lowercase (     lowercase__   ,	lowercase__   ,	lowercase__						):
      return (
          round(pow(effusion_rate_a / effusion_rate_a   ,	2						) / molar_mass   ,	6						)
          if validate(lowercase__   ,	lowercase__   ,	lowercase__						)
          else ValueError(
              '''Input Error: Molar mass and effusion rate values must greater than 0.'''						)
      )





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


_UpperCamelCase 			=		logging.get_logger(__name__)

_UpperCamelCase 			=		{
    "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   __lowercase      (_UpperCAmelCase ):
 _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      ,							A_=100      ,							A_=5      ,							A_=1      ,							A_=1      ,							A_=249      ,							A_=6      ,							A_=17      ,							A_=25      ,							A_=4      ,							A_=4      ,							A_=128      ,							A_=0.1      ,							A_=0.1      ,							A_=0.1      ,							A_=0.0_006      ,							A_=512      ,							A_=0.02      ,							A_=1e-12      ,							A_=1      ,							A_=True      ,							A_=1      ,							A_=5_0256      ,							A_=5_0256      ,							**A_      ,							)					->int:



       '''simple docstring'''





       __lowerCAmelCase					:						Any					=					vocab_size
       __lowerCAmelCase					:						Tuple					=					action_weight
       __lowerCAmelCase					:						Tuple					=					reward_weight
       __lowerCAmelCase					:						Union[str, Any]					=					value_weight
       __lowerCAmelCase					:						List[str]					=					max_position_embeddings
       __lowerCAmelCase					:						str					=					block_size
       __lowerCAmelCase					:						Optional[Any]					=					action_dim
       __lowerCAmelCase					:						Union[str, Any]					=					observation_dim
       __lowerCAmelCase					:						Union[str, Any]					=					transition_dim
       __lowerCAmelCase					:						Dict					=					learning_rate
       __lowerCAmelCase					:						Any					=					n_layer
       __lowerCAmelCase					:						Any					=					n_head
       __lowerCAmelCase					:						Optional[int]					=					n_embd
       __lowerCAmelCase					:						str					=					embd_pdrop
       __lowerCAmelCase					:						Dict					=					attn_pdrop
       __lowerCAmelCase					:						Optional[int]					=					resid_pdrop
       __lowerCAmelCase					:						Union[str, Any]					=					initializer_range
       __lowerCAmelCase					:						Optional[int]					=					layer_norm_eps
       __lowerCAmelCase					:						Any					=					kaiming_initializer_range
       __lowerCAmelCase					:						List[str]					=					use_cache
       super().__init__(pad_token_id=A_      ,							bos_token_id=A_      ,							eos_token_id=A_      ,							**A_					)


