docstr: Test that if any tensor passed to operators is on the GPU then CUDA
  is set internally as a device option for 'default.qubit.torch'.
docstr_tok: ["Test","that","if","any","tensor","passed","to","operators","is","on","the","GPU","then","CUDA","is","set","internally","as","a","device","option","for","'default.qubit.torch","'","."]
code: def test_torch_device_cuda_if_tensors_on_cuda(self):
      """Test that if any tensor passed to operators is on the GPU then CUDA
      is set internally as a device option for 'default.qubit.torch'."""
  
      n_qubits = 3
      n_layers = 1
  
      dev = qml.device("default.qubit", wires=n_qubits)
  
      @qml.qnode(dev)
      def circuit(inputs, weights):
          qml.templates.AngleEmbedding(inputs, wires=range(n_qubits))
          qml.templates.BasicEntanglerLayers(
              weights, wires=range(n_qubits)
          )
          return [
              qml.expval(qml.PauliZ(wires=i)) for i in range(n_qubits)
          ]
  
      weight_shapes = {"weights": (n_layers, n_qubits)}
  
      qlayer = qml.qnn.TorchLayer(circuit, weight_shapes)
  
      x = torch.rand((5, n_qubits), dtype=torch.float64).to(
          torch.device("cuda")
      )
      res = qlayer(x)
      assert circuit.device.short_name == "default.qubit.torch"
      assert "cuda" in circuit.device._torch_device
      assert res.is_cuda
  
      loss = torch.sum(res).squeeze()
      loss.backward()
      assert loss.is_cuda
  
file_path: pennylane/tests/gpu/test_gpu_torch.py
imports: import pytest
  import pennylane
label_desc: Use image node_id 1 for calling the TestqnnTorchLayer obj's underlying member method code with example usage: obj.test_torch_device_cuda_if_tensors_on_cuda() and returns: unknown