code: def test_draw_mpl():
      """Test that a TorchLayer can be drawn using qml.draw_mpl"""
  
      dev = qml.device("default.qubit", wires=2)
      weight_shapes = {"w1": 1, "w2": (3, 2, 3)}
  
      @qml.qnode(dev, interface="torch")
      def circuit(inputs, w1, w2):
          qml.templates.AngleEmbedding(inputs, wires=[0, 1])
          qml.RX(w1, wires=0)
          qml.templates.StronglyEntanglingLayers(w2, wires=[0, 1])
          return qml.expval(qml.PauliZ(0)), qml.expval(qml.PauliZ(1))
  
      qlayer = TorchLayer(circuit, weight_shapes)
  
      # make the rotation angle positive to prevent the extra minus sign messing up the alignment
      qlayer.qnode_weights["w1"] = torch.abs(qlayer.qnode_weights["w1"])
  
      batch_size = 5
      x = torch.Tensor(np.random.uniform(0, 1, (batch_size, 2)))
  
      _, ax = qml.draw_mpl(qlayer)(x)
  
      assert len(ax.patches) == 9  # 3 boxes, 3 patches for each measure
      assert len(ax.lines) == 2  # 2 wires
      assert len(ax.texts) == 5  # 2 wire labels, 3 box labels
  
      assert ax.texts[0].get_text() == "0"
      assert ax.texts[1].get_text() == "1"
      assert ax.texts[2].get_text() == "AngleEmbedding"
      assert ax.texts[3].get_text() == "RX"
      assert ax.texts[4].get_text() == "StronglyEntanglingLayers"
  
imports: from unittest import mock
  import math
  from collections import defaultdict
  import numpy
  import pytest
  import pennylane
  from pennylane.qnn.torch import TorchLayer
label_desc: Use image node_id 8 for calling a global function with example usage: test_draw_mpl() and returns: qml,  qml