class_docstr: Test integration of the gradient transform decorator
class_docstr_tok: ["Test","integration","of","the","gradient","transform","decorator"]
docstr: Test that setting the number of shots works correctly for
  a gradient transform
docstr_tok: ["Test","that","setting","the","number","of","shots","works","correctly","for","a","gradient","transform"]
code: def test_setting_shots(self):
      """Test that setting the number of shots works correctly for
      a gradient transform"""
  
      dev = qml.device("default.qubit", wires=1, shots=1000)
  
      @qml.qnode(dev)
      def circuit(x):
          qml.RX(x, wires=0)
          return qml.expval(qml.PauliZ(0))
  
      x = np.array(0.543, requires_grad=True)
  
      # the gradient function can be called with different shot values
      grad_fn = qml.gradients.param_shift(circuit)
      assert grad_fn(x).shape == ()
      assert len(grad_fn(x, shots=[(1, 1000)])) == 1000
  
      # the original QNode is unaffected
      assert circuit(x).shape == tuple()
      assert circuit(x, shots=1000).shape == tuple()
  
imports: import pytest
  import pennylane
  from pennylane import numpy
  from pennylane.gradients.gradient_transform import _find_gradient_methods, _validate_gradient_methods, choose_trainable_params
label_desc: Use image node_id 18 for calling the TestGradientTransformIntegration obj's underlying member method code with example usage: obj.test_setting_shots() and returns: qml