code: def test_fitting_complete_display_test_with_progress_bar_no_coloring(
      self,
  ):
      _ = self.model.fit_generator(
          self.train_generator,
          self.valid_generator,
          epochs=1,
          steps_per_epoch=ModelFittingTestCaseProgress.num_steps,
          validation_steps=ModelFittingTestCaseProgress.num_steps,
          callbacks=[self.mock_callback],
          progress_options=dict(coloring=False, progress_bar=True),
      )
  
      # We split per step update
      steps_update = self.test_out.getvalue().strip().split("\r")
  
      # we don't validate the templating of metrics since tested before
      template_format = (
          r".*Epoch:.*{}\/1.*Step:.*{}\/5.*{:6.2f}\%.*|{}|.*ETA:"
      )
      epoch = 1
      # the 5 train steps
      for step, step_update in enumerate(
          steps_update[: ModelFittingTestCaseProgress.num_steps]
      ):
          step += 1
          progress_Bar = "\u2588" * step * 2 + " " * (20 - step * 2)
          regex_filled = template_format.format(
              epoch,
              step,
              step / ModelFittingTestCaseProgress.num_steps * 100,
              progress_Bar,
          )
          self.assertRegex(step_update, regex_filled)
  
      # The 5 val steps
      for step, step_update in enumerate(
          steps_update[ModelFittingTestCaseProgress.num_steps : -1]
      ):
          step += 1
          progress_Bar = "\u2588" * step * 2 + " " * (20 - step * 2)
          regex_filled = template_format.format(
              epoch,
              step,
              step / ModelFittingTestCaseProgress.num_steps * 100,
              progress_Bar,
          )
          self.assertRegex(step_update, regex_filled)
  
      # last print update templating different
      last_print_regex = (
          r".*Train steps:.*5.*Val steps:.*5.*"
          + ModelFittingTestCaseProgress.TIME_REGEX
      )
      self.assertRegex(steps_update[-1], last_print_regex)
  
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 32 for calling the ModelFittingTestCaseProgress obj's underlying member method code with example usage: obj.test_fitting_complete_display_test_with_progress_bar_no_coloring() without return types