code: def test_conv_upsample(num_layers):
      num_upsample = num_layers if num_layers > 0 else 0
      num_layers = num_layers if num_layers > 0 else 1
      layer = ConvUpsample(
          10,
          5,
          num_layers=num_layers,
          num_upsample=num_upsample,
          conv_cfg=None,
          norm_cfg=None,
      )
  
      size = 5
      x = torch.randn((1, 10, size, size))
      size = size * pow(2, num_upsample)
      x = layer(x)
      assert x.shape[-2:] == (size, size)
  
imports: import pytest
  import torch
  from mmdet.models.layers import ConvUpsample
label_desc: Use image node_id 1 for calling a global function with example usage: test_conv_upsample(num_layers) without return types