code: def test_visualize_random_filters_from_one_layer(
      conv_layer, g_ascent
  ):
      num_subplots = 3
  
      output = g_ascent.visualize(
          conv_layer,
          num_iter=2,
          num_subplots=num_subplots,
          return_output=True,
      )
  
      assert len(output) == num_subplots
      assert len(output[0]) == 2  # num_iter
      assert output[0][-1].shape == (
          1,
          3,
          g_ascent.img_size,
          g_ascent.img_size,
      )
  
imports: import inspect
  import pytest
  from os import path
  import numpy
  import torchvision.models
  from flashtorch.activmax import GradientAscent
  from flashtorch.utils import apply_transforms
label_desc: Use image node_id 18 for calling a global function with example usage: test_visualize_random_filters_from_one_layer(conv_layer, g_ascent) without return types