class_docstr: Tests a basic circuit with one rx gate and two simple expectation values.
docstr: Tests execution and gradients of a simple circuit with torch.
docstr_tok: ["Tests","execution","and","gradients","of","a","simple","circuit","with","torch","."]
code: def test_torch_results_and_backprop(self):
      """Tests execution and gradients of a simple circuit with torch."""
  
      import torch
  
      phi = torch.tensor(-0.526, requires_grad=True)
  
      def f(x):
          qs = qml.tape.QuantumScript(
              [qml.RX(x, wires=0)],
              [qml.expval(qml.PauliY(0)), qml.expval(qml.PauliZ(0))],
          )
          return simulate(qs)
  
      result = f(phi)
      assert qml.math.allclose(result[0], -torch.sin(phi))
      assert qml.math.allclose(result[1], torch.cos(phi))
  
      g = torch.autograd.functional.jacobian(f, phi + 0j)
      assert qml.math.allclose(g[0], -torch.cos(phi))
      assert qml.math.allclose(g[1], -torch.sin(phi))
  
imports: import pytest
  import numpy
  import pennylane
  from pennylane.devices.qubit import simulate, get_final_state, measure_final_state
label_desc: Use image node_id 4 for calling the TestBasicCircuit obj's underlying member method code with example usage: obj.test_torch_results_and_backprop() and returns: simulate