code: def normalized_L1_loss(
      latent_activations: torch.Tensor,
      original_input: torch.Tensor,
  ) -> torch.Tensor:
      """
      :param latent_activations: output of Autoencoder.encode (shape: [batch, n_latents])
      :param original_input: input of Autoencoder.encode (shape: [batch, n_inputs])
      :return: normalized L1 loss (shape: [1])
      """
      return (
          latent_activations.abs().sum(dim=1)
          / original_input.norm(dim=1)
      ).mean()
  
imports: import torch
label_desc: Use image node_id 3 for calling a global function with example usage: normalized_L1_loss(latent_activations, original_input) and returns: unknown