code: def test_scored_net_with_reduction_none(
      self, scored_net_cls, module_cls, reduction, data
  ):
      X, y = data
      net = scored_net_cls(
          module_cls, lr=0.01, criterion__reduction=reduction
      ).fit(X, y)
      net.set_params(criterion__reduction="sum")
      loss_value = net.score(X, y)
      net.set_params(criterion__reduction="none")
      output = net.score(X, y)
      assert output.shape[0] == X.shape[0]
      assert np.allclose(output.sum(), loss_value)
  
imports: import pytest
  import numpy
  import torch
label_desc: Use image node_id 17 for calling the TestLossScoring obj's underlying member method code with example usage: obj.test_scored_net_with_reduction_none(scored_net_cls, module_cls, reduction, data) without return types