code: def test_compute_loss(self):
      test_loss = self.art_model.compute_loss(
          self.x_test_diabetes[:4].astype(np.float32),
          self.y_test_diabetes[:4].astype(np.float32),
      )
      loss_expected = [3461.6, 5214.4, 3994.9, 9003.6]
      np.testing.assert_array_almost_equal(
          test_loss, loss_expected, decimal=1
      )
  
file_path: adversarial-robustness-toolbox/tests/estimators/regression/test_pytorch_regression.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import unittest
  import numpy
  from torch import nn, optim
  from art.estimators.regression.pytorch import PyTorchRegressor
  from tests.utils import TestBase, master_seed
label_desc: Use image node_id 6 for calling the TestPytorchRegressor obj's underlying member method code with example usage: obj.test_compute_loss() without return types