code: def normalized_mean_squared_error(
      reconstruction: torch.Tensor,
      original_input: torch.Tensor,
  ) -> torch.Tensor:
      """
      :param reconstruction: output of Autoencoder.decode (shape: [batch, n_inputs])
      :param original_input: input of Autoencoder.encode (shape: [batch, n_inputs])
      :return: normalized mean squared error (shape: [1])
      """
      return (
          ((reconstruction - original_input) ** 2).mean(dim=1)
          / (original_input**2).mean(dim=1)
      ).mean()
  
imports: import torch
label_desc: Use image node_id 2 for calling a global function with example usage: normalized_mean_squared_error(reconstruction, original_input) and returns: unknown