code: def get_used_tokens_for_gbm(
      inputs: Union[torch.Tensor, Dict[str, torch.Tensor]]
  ) -> int:
      """Returns the number of used tokens for a GBM model.
  
      The number of used tokens is:
      1. the size of the input tensor, which corresponds to 1 token for each input feature
      (binary, category, number) in the batch.
      2. batch_size, which corresponds to 1 token for the batch of target features.
  
      Args:
          inputs: The input tensors that are fed to the gbm.forward() method.
      """
      if isinstance(inputs, torch.Tensor):
          # Inputs may be a tensor for evaluation.
          # Use the total number of inputs + the batch size as the number of output tokens.
          return torch.flatten(inputs).shape[0] + inputs.shape[0]
      return len(inputs.keys()) + 1
  
imports: from typing import Dict, Union
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: get_used_tokens_for_gbm(inputs) and returns: unknown, unknown