code: def test_saving(tmp_path):
      """Test saving functionality."""
      model1 = UnimodalModel(input_dim=input_dim, output_dim=output_dim)
      model2 = UnimodalModel(input_dim=input_dim, output_dim=output_dim)
  
      path = tmp_path / "weights.pt"
      model1.save_weights(path)
      model2.load_weights(path)
  
      for params1, params2 in zip(
          model1.parameters(), model2.parameters()
      ):
          assert torch.allclose(params1, params2)
  
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 24 for calling a global function with example usage: test_saving(tmp_path) without return types