docstr: Test if TorchLayer can be run on GPU
docstr_tok: ["Test","if","TorchLayer","can","be","run","on","GPU"]
code: def test_qnn_torchlayer(self):
      """Test if TorchLayer can be run on GPU"""
  
      n_qubits = 4
      dev = qml.device("default.qubit", wires=n_qubits)
  
      @qml.qnode(dev, interface="torch")
      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)
          ]
  
      n_layers = 1
      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 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 2 for calling the TestqnnTorchLayer obj's underlying member method code with example usage: obj.test_qnn_torchlayer() and returns: unknown