code: def compute_loss(self, embeddings):
      return {
          "loss": {
              "losses": torch.abs(torch.sum(embeddings, dim=1)),
              "indices": c_f.torch_arange_from_size(embeddings),
              "reduction_type": "element",
          }
      }
  
imports: import torch
  from ..utils import common_functions
  from .base_regularizer import BaseRegularizer
label_desc: Use image node_id 1 for calling the ZeroMeanRegularizer obj's underlying member method code with example usage: obj.compute_loss(embeddings) and returns: dict