code: def test_film():
      layer = FiLM(50, 76)
      inp = torch.rand(32, 50, 100)
      nl = torch.rand(32)
      shift, scale = layer(inp, nl)
  
      assert shift.shape[0] == 32
      assert shift.shape[1] == 76
      assert shift.shape[2] == 100
      assert isinstance(shift, torch.FloatTensor)
  
      assert scale.shape[0] == 32
      assert scale.shape[1] == 76
      assert scale.shape[2] == 100
      assert isinstance(scale, 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 2 for calling a global function with example usage: test_film() without return types