code: def test_ublock():
      inp1 = torch.rand(32, 50, 100)
      inp2 = torch.rand(32, 50, 50)
      nl = torch.rand(32)
  
      layer_film = FiLM(50, 100)
      layer = UBlock(50, 100, 2, [1, 2, 4, 8])
  
      scale, shift = layer_film(inp1, nl)
      o = layer(inp2, shift, scale)
  
      assert o.shape[0] == 32
      assert o.shape[1] == 100
      assert o.shape[2] == 100
      assert isinstance(o, torch.FloatTensor)
  
      layer.apply_weight_norm()
      layer.remove_weight_norm()
  
file_path: TTS/tests/test_wavegrad_layers.py
imports: import torch
  from TTS.vocoder.layers.wavegrad import PositionalEncoding, FiLM, UBlock, DBlock
  from TTS.vocoder.models.wavegrad import Wavegrad
label_desc: Use image node_id 3 for calling a global function with example usage: test_ublock() without return types