class_docstr: Zips together minibatch outputs, i.e. returns a DataContainer where the first
  element is a tuple of every minibatches first element and so on.
class_docstr_tok: ["Zips","together","minibatch","outputs",",","i.e",".","returns","a","DataContainer","where","the","first","element","is","a","tuple","of","every","minibatches","first","element","and","so","on","."]
code: def join_transform(
      self, step: TruncableSteps, data_container: DACT, context: CX
  ) -> ZipDataContainer:
      context = context.push(step)
      data_container_batches = data_container.minibatches(
          batch_size=self.batch_size,
          keep_incomplete_batch=self.keep_incomplete_batch,
          default_value_data_inputs=self.default_value_data_inputs,
          default_value_expected_outputs=self.default_value_expected_outputs,
      )
  
      output_data_container = []
      for data_container_batch in data_container_batches:
          output_data_container.append(
              step._transform_data_container(
                  data_container_batch, context
              )
          )
  
      return ZipDataContainer.create_from(*output_data_container)
  
imports: import warnings
  from abc import ABC, abstractmethod
  from typing import Any, List, Tuple, Union
  from neuraxle.base import BaseStep
  from neuraxle.base import ExecutionContext
  from neuraxle.base import ExecutionMode, ForceHandleMixin, Identity, NamedStepsList, TruncableSteps, _CustomHandlerMethods, _TruncableServiceWithBodyMixin
  from neuraxle.data_container import DataContainer
  from neuraxle.data_container import ListDataContainer, StripAbsentValues, ZipDataContainer
  from neuraxle.logging.warnings import warn_deprecated_arg
label_desc: Use image node_id 1 for calling the ZipMinibatchJoiner obj's underlying member method code with example usage: obj.join_transform(step, data_container, context) and returns: ZipDataContainer