code: def test_reset_metrics_multimodal(multimodal_model, dataset):
      """Test if the model is resetting the metrics in the multimodal case."""
      y_pred = dataset["output"]["multimodal"]["y_pred"]
      y_true = dataset["output"]["multimodal"]["y_true"]
  
      for i in range(2):
          key = f"output_{i + 1}"
          multimodal_model.metrics[key].compute_metric(
              y_true=y_true[i], y_pred=y_pred[i]
          )
  
      multimodal_model._reset_metrics()
  
      for i in range(2):
          key = f"output_{i + 1}"
          assert np.isclose(multimodal_model.metrics[key].total, 0)
          assert np.isclose(multimodal_model.metrics[key].count, 0)
  
imports: from typing import List
  import numpy
  import pytest
  import torch
  import torch.nn
  import torch.optim
  from torch.utils.data import DataLoader, TensorDataset
  from alibi.models.pytorch.metrics import AccuracyMetric, LossContainer
  from alibi.models.pytorch.model import Model
label_desc: Use image node_id 23 for calling a global function with example usage: test_reset_metrics_multimodal(multimodal_model, dataset) without return types