code: def test_evaluate_generator_with_progress_bar_coloring(self):
      generator = some_data_tensor_generator(
          ModelFittingTestCase.batch_size
      )
  
      _, _ = self.model.evaluate_generator(
          generator,
          steps=ModelFittingTestCaseProgress.num_steps,
          verbose=True,
      )
  
      self.assertStdoutContains(
          ["%", "[32m", "[35m", "[36m", "[94m", "\u2588"]
      )
  
imports: from unittest import skipIf
  import torch
  import torch.nn
  from torch.utils.data import DataLoader
  from poutyne import Model, TensorDataset
  from tests.framework.model.base import ModelFittingTestCase
  from tests.framework.tools import SomeConstantMetric, SomeDataGeneratorUsingStopIteration, repeat_batch_metric, repeat_batch_metric_value, some_batch_metric_1, some_batch_metric_2, some_constant_metric_value, some_data_tensor_generator, some_metric_1_value, some_metric_2_value
label_desc: Use image node_id 29 for calling the ModelFittingTestCaseProgress obj's underlying member method code with example usage: obj.test_evaluate_generator_with_progress_bar_coloring() without return types