code: def test_set_custom_img_size(conv_layer, g_ascent):
      custom_img_size = 64
      g_ascent.img_size = custom_img_size
      assert g_ascent.img_size == custom_img_size
  
      output = g_ascent.optimize(conv_layer, 0, num_iter=2)
  
      assert output[0].shape == (1, 3, custom_img_size, custom_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 7 for calling a global function with example usage: test_set_custom_img_size(conv_layer, g_ascent) without return types