class_docstr: Test GPU with cuda for Torch device.
class_docstr_tok: ["Test","GPU","with","cuda","for","Torch","device","."]
docstr: Test that the padding capability of amplitude embedding works with
  GPUs.
docstr_tok: ["Test","that","the","padding","capability","of","amplitude","embedding","works","with","GPUs","."]
code: def test_amplitude_embedding(self):
      """Test that the padding capability of amplitude embedding works with
      GPUs."""
      n_wires = 2
      dev = qml.device("default.qubit", wires=n_wires)
  
      @qml.qnode(dev, interface="torch")
      def circuit_cuda(inputs):
          qml.AmplitudeEmbedding(
              inputs, wires=range(n_wires), pad_with=0, normalize=True
          )
          return qml.expval(qml.PauliZ(0))
  
      inputs = torch.rand(
          n_wires
      )  # embedding shorter than 2 ** n_wires
      res1 = circuit_cuda(inputs)
      assert not res1.is_cuda
  
      inputs = inputs.to(torch.device("cuda"))  # move to GPU
      res2 = circuit_cuda(inputs)
  
      assert res2.is_cuda
  
file_path: pennylane/tests/gpu/test_gpu_torch.py
imports: import pytest
  import pennylane
label_desc: Use image node_id 7 for calling the TestTorchDevice obj's underlying member method code with example usage: obj.test_amplitude_embedding() and returns: qml