class_docstr: Class to test the shape of the Grad/Jacobian/Hessian with different return types and shot vectors.
class_docstr_tok: ["Class","to","test","the","shape","of","the","Grad\/Jacobian\/Hessian","with","different","return","types","and","shot","vectors","."]
docstr: The jacobian of multiple measurements with a multiple params array return a single array.
docstr_tok: ["The","jacobian","of","multiple","measurements","with","a","multiple","params","array","return","a","single","array","."]
code: def test_jacobian_expval_expval_multiple_params_array(
      self,
      dev_name,
      diff_method,
      gradient_kwargs,
      shots,
      num_copies,
      decorator,
      interface,
  ):
      """The jacobian of multiple measurements with a multiple params array return a single array."""
      dev = qml.device(dev_name, wires=2, shots=shots)
  
      @decorator
      @qnode(
          dev,
          diff_method=diff_method,
          interface=interface,
          **gradient_kwargs,
      )
      def circuit(a):
          qml.RY(a[0], wires=0)
          qml.RX(a[1], wires=0)
          qml.RY(a[2], wires=0)
          return qml.expval(qml.PauliZ(0) @ qml.PauliX(1)), qml.expval(
              qml.PauliZ(0)
          )
  
      a = tf.Variable([0.7, 0.9, 1.1], dtype=tf.float64)
  
      with tf.GradientTape() as tape:
          res = circuit(a)
          res = qml.math.stack([qml.math.stack(r) for r in res])
  
      jac = tape.jacobian(res, a)
  
      assert isinstance(jac, tf.Tensor)
      assert jac.shape == (num_copies, 2, 3)
  
imports: import pytest
  import pennylane
  from pennylane import numpy
  from pennylane import qnode
label_desc: Use image node_id 8 for calling the TestReturnWithShotVectors obj's underlying member method code with example usage: obj.test_jacobian_expval_expval_multiple_params_array(dev_name, diff_method, gradient_kwargs, shots, num_copies, decorator, interface) and returns: qml,  qml