class_docstr: This should raise an error because it does not return the same length for data_inputs and expected_outputs
class_docstr_tok: ["This","should","raise","an","error","because","it","does","not","return","the","same","length","for","data_inputs","and","expected_outputs"]
code: def transform(self, data_inputs):
      ids, data_inputs, expected_outputs = data_inputs
      return (
          ids,
          data_inputs[0 : int(len(data_inputs) / 2)],
          expected_outputs,
      )
  
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 2 for calling the ChangeLenDataInputs obj's underlying member method code with example usage: obj.transform(data_inputs) and returns: ids,  data_inputs,  expected_outputs