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: For one measurement and multiple param as a single array params, the gradient is an array.
docstr_tok: ["For","one","measurement","and","multiple","param","as","a","single","array","params",",","the","gradient","is","an","array","."]
code: def test_jacobian_single_measurement_multiple_param_array(
      self,
      dev,
      diff_method,
      gradient_kwargs,
      shots,
      num_copies,
      decorator,
      interface,
  ):
      """For one measurement and multiple param as a single array params, the gradient is an array."""
  
      @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)
          return qml.expval(qml.PauliZ(0))
  
      a = tf.Variable([1.5, 0.7], dtype=tf.float64)
  
      with tf.GradientTape() as tape:
          res = circuit(a, shots=shots)
          res = qml.math.stack(res)
  
      jac = tape.jacobian(res, a)
  
      assert isinstance(jac, tf.Tensor)
      assert jac.shape == (num_copies, 2)
  
imports: import pytest
  import pennylane
  from pennylane import numpy
  from pennylane import qnode
  from pennylane.devices import DefaultQubit
label_desc: Use image node_id 3 for calling the TestReturnWithShotVectors obj's underlying member method code with example usage: obj.test_jacobian_single_measurement_multiple_param_array(dev, diff_method, gradient_kwargs, shots, num_copies, decorator, interface) and returns: qml