code: def test_transducer_loss(device):
      # Make this its own test since it can only be run
      # if numba is installed and a GPU is available
      pytest.importorskip("numba")
      if torch.cuda.device_count() == 0:
          pytest.skip("This test can only be run if a GPU is available")
  
      from speechbrain.nnet.losses import transducer_loss
  
      device = torch.device("cuda")
      log_probs = (
          torch.Tensor(
              [
                  [
                      [
                          [0.1, 0.6, 0.1, 0.1, 0.1],
                          [0.1, 0.1, 0.6, 0.1, 0.1],
                          [0.1, 0.1, 0.2, 0.8, 0.1],
                      ],
                      [
                          [0.1, 0.6, 0.1, 0.1, 0.1],
                          [0.1, 0.1, 0.2, 0.1, 0.1],
                          [0.7, 0.1, 0.2, 0.1, 0.1],
                      ],
                  ]
              ]
          )
          .to(device)
          .requires_grad_()
          .log_softmax(dim=-1)
      )
      targets = torch.Tensor([[1, 2]]).to(device).int()
      probs_length = torch.Tensor([1.0]).to(device)
      target_length = torch.Tensor([1.0]).to(device)
      out_cost = transducer_loss(
          log_probs,
          targets,
          probs_length,
          target_length,
          blank_index=0,
          use_torchaudio=False,
      )
      out_cost.backward()
      assert out_cost.item() == pytest.approx(2.2478, 0.0001)
  
file_path: speechbrain/tests/unittests/test_losses.py
imports: import torch
  import pytest
label_desc: Use image node_id 7 for calling a global function with example usage: test_transducer_loss(device) without return types