class_docstr: Test preprocess produces output that can be executed by the device.
class_docstr_tok: ["Test","preprocess","produces","output","that","can","be","executed","by","the","device","."]
docstr: Test that batch_transform does nothing when batching is required but
  internal PennyLane broadcasting can be used (diff method != adjoint)
docstr_tok: ["Test","that","batch_transform","does","nothing","when","batching","is","required","but","internal","PennyLane","broadcasting","can","be","used","(","diff","method","!","=","adjoint",")"]
code: def test_batch_transform_broadcast_not_adjoint(self):
      """Test that batch_transform does nothing when batching is required but
      internal PennyLane broadcasting can be used (diff method != adjoint)
      """
      ops = [
          qml.Hadamard(0),
          qml.CNOT([0, 1]),
          qml.RX([np.pi, np.pi / 2], wires=1),
      ]
      measurements = [qml.expval(qml.PauliZ(1))]
      tape = qml.tape.QuantumScript(ops=ops, measurements=measurements)
      device = qml.devices.DefaultQubit()
  
      program, _ = device.preprocess()
      tapes, _ = program([tape])
  
      assert len(tapes) == 1
      assert tapes[0].circuit == ops + measurements
  
imports: import pytest
  import numpy
  import pennylane
  from pennylane.devices import DefaultQubit, ExecutionConfig
  from pennylane.devices.default_qubit import stopping_condition
label_desc: Use image node_id 2 for calling the TestPreprocessingIntegration obj's underlying member method code with example usage: obj.test_batch_transform_broadcast_not_adjoint() without return types