code: def test_dl_attr_with_reduce_and_to_metric(self) -> None:
      forward = sum_forward
      func_call_counts = {
          "reduce": 0,
          "to_metric": 0,
      }
  
      def reduce(accum, cur_output, cur_inputs):
          func_call_counts["reduce"] += 1
  
          accum = {"sum": 0, "count": 0} if accum is None else accum
  
          accum["sum"] += cur_output.sum()
          accum["count"] += len(cur_output)
  
          return accum
  
      def to_metric(accum):
          func_call_counts["to_metric"] += 1
  
          self.assertEqual(isinstance(accum, dict), True)
          return torch.tensor(
              [
                  accum["sum"] / accum["count"],
                  accum["sum"],
              ]
          )
  
      fa = FeatureAblation(forward)
      dl_fa = DataLoaderAttribution(fa)
  
      batch_size = 2
      dataloader = DataLoader(mock_dataset, batch_size=batch_size)
  
      dl_attribution = dl_fa.attribute(
          dataloader,
          reduce=reduce,
          to_metric=to_metric,
          return_input_shape=False,
      )
  
      n_iters = len(dataloader)
  
      n_features = 7
      # after support other attr methods, this can be diff from n_features
      n_perturbations = 7
      n_passes = (
          n_perturbations + 1
      )  # +1 for base forward without perturbation
      n_outputs = 2  # [mean, sum]
  
      self.assertEqual(func_call_counts["reduce"], n_iters * n_passes)
      self.assertEqual(func_call_counts["to_metric"], n_passes)
  
      expected_attr_shape = (n_outputs, n_features)
  
      self.assertEqual(type(dl_attribution), Tensor)
      dl_attribution = cast(Tensor, dl_attribution)
      self.assertEqual(dl_attribution.shape, expected_attr_shape)
  
imports: import math
  from typing import cast
  from unittest.mock import Mock, patch
  import torch
  from captum.attr._core.dataloader_attr import DataLoaderAttribution, InputRole
  from captum.attr._core.feature_ablation import FeatureAblation
  from parameterized import parameterized
  from tests.helpers.basic import assertAttributionComparision, assertTensorAlmostEqual, BaseTest
  from torch import Tensor
  from torch.utils.data import DataLoader, TensorDataset
label_desc: Use image node_id 4 for calling the Test obj's underlying member method code with example usage: obj.test_dl_attr_with_reduce_and_to_metric() and returns: accum, torch