code: def test_data_doubler():
      p = IdsInputAndOutputTransformerWrapper(DoubleData())
      ids, data_inputs, expected_outputs = _create_data_source(
          (10, 10), with_ids=True
      )
  
      out = p.handle_transform(
          DACT(
              ids=ids,
              data_inputs=data_inputs,
              expected_outputs=expected_outputs,
          ),
          CX(),
      )
  
      doubled_length = len(out.data_inputs)
      assert doubled_length == 2 * len(data_inputs)
      assert doubled_length == len(out.expected_outputs)
      assert doubled_length == len(out.ids)
  
imports: import numpy
  import pytest
  from neuraxle.base import BaseTransformer
  from neuraxle.base import ExecutionContext
  from neuraxle.base import ForceHandleMixin
  from neuraxle.data_container import EOT
  from neuraxle.data_container import DataContainer
  from neuraxle.hyperparams.space import HyperparameterSamples
  from neuraxle.pipeline import Pipeline
  from neuraxle.steps.misc import FitCallbackStep, TapeCallbackFunction
  from neuraxle.steps.numpy import MultiplyByN
  from neuraxle.steps.output_handlers import IdsInputAndOutputTransformerWrapper, OutputTransformerWrapper
label_desc: Use image node_id 9 for calling a global function with example usage: test_data_doubler() without return types