code: def map_triplet_to_action(
      triplet: Tuple[torch.Tensor, torch.Tensor, torch.Tensor],
      base: int,
      n_steps: int,
      add_bias: bool = True,
  ):
      """Maps a triplet of tensors to an action.
  
      Args:
          triplet (Tuple[torch.Tensor, torch.Tensor, torch.Tensor]): Triplet of
          tensors u, v, and w.
          base (int): Base used for the conversion.
          n_steps (int): Number of steps in the action.
          add_bias (bool, optional): Whether to add a bias to the action.
      """
      # map the triplet to an action. First, we concatenate the three tensors and
      # then we convert it to an action using the given base representation. Each
      # element is converted using the formula:
      #   action += element * base^(element_index)
      u, v, w = triplet
      n_dim = u.ndim
      action = torch.cat((u, v, w), dim=-1)
      action = action.reshape(-1, n_steps, action.shape[-1] // n_steps)
      if n_dim == 1:
          action = action.squeeze(0)
      if add_bias:
          action = action + base // 2
      action = action * torch.tensor(
          [base**i for i in range(action.shape[-1])]
      )
      action = action.sum(dim=-1)
      return action
  
imports: from typing import Tuple
  import torch
label_desc: Use image node_id 2 for calling a global function with example usage: map_triplet_to_action(triplet, base, n_steps, add_bias) and returns: action