class_docstr: Class to test the shape of the Grad/Jacobian/Hessian with different return types and shot vectors.
docstr: For a multi dimensional measurement (probs), check that a single array is returned with the correct
  dimension
docstr_tok: ["For","a","multi","dimensional","measurement","(","probs",")",",","check","that","a","single","array","is","returned","with","the","correct","dimension"]
code: def test_jacobian_single_measurement_param_probs(
      self,
      dev,
      diff_method,
      gradient_kwargs,
      shots,
      num_copies,
      interface,
  ):
      """For a multi dimensional measurement (probs), check that a single array is returned with the correct
      dimension"""
  
      @qnode(
          dev,
          diff_method=diff_method,
          interface=interface,
          **gradient_kwargs,
      )
      def circuit(a):
          qml.RY(a, wires=0)
          qml.RX(0.2, wires=0)
          return qml.probs(wires=[0, 1])
  
      a = tf.Variable(0.1)
  
      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, 4)
  
imports: import pytest
  import pennylane
  from pennylane import numpy
  from pennylane import qnode
  from pennylane.devices import DefaultQubit
label_desc: Use image node_id 4 for calling the TestReturnWithShotVectors obj's underlying member method code with example usage: obj.test_jacobian_single_measurement_param_probs(dev, diff_method, gradient_kwargs, shots, num_copies, interface) and returns: qml