class_docstr: Unit tests for the batch_transform class
class_docstr_tok: ["Unit","tests","for","the","batch_transform","class"]
docstr: Test that a transform that returns None for a processing function applies
  the identity as the processing function
docstr_tok: ["Test","that","a","transform","that","returns","None","for","a","processing","function","applies","the","identity","as","the","processing","function"]
code: def test_none_processing(self):
      """Test that a transform that returns None for a processing function applies
      the identity as the processing function"""
  
      @qml.batch_transform
      def my_transform(tape):
          tape1 = tape.copy()
          tape2 = tape.copy()
          return [tape1, tape2], None
  
      with qml.queuing.AnnotatedQueue() as q:
          qml.Hadamard(wires=0)
          qml.expval(qml.PauliX(0))
  
      tape = qml.tape.QuantumScript.from_queue(q)
      _, fn = my_transform(tape)
      assert fn(5) == 5
  
      qs = qml.tape.QuantumScript(tape.operations, tape.measurements)
      _, fn = my_transform(qs)
      assert fn(5) == 5
  
imports: import functools
  import pytest
  import pennylane
  from pennylane import numpy
label_desc: Use image node_id 7 for calling the TestBatchTransform obj's underlying member method code with example usage: obj.test_none_processing() and returns: list,  None