class_docstr: BatchProcessor Class for plug and play fit_batch & evaluate_batch
  
  During training or validation, data are divided into minibatches for processing. This
  class aims at providing hooks of training or validating on a minibatch of data. Users
  may provide customized fit_batch() and evaluate_batch() methods by inheriting from
  this class and overriding class methods.
  
  :py:class:`BatchProcessor` can be used to replace fit_batch() and evaluate_batch()
  in the base estimator class
code: def _get_data_and_label(self, batch, ctx, batch_axis=0):
      data = batch[0]
      label = batch[1]
      data = split_and_load(data, ctx_list=ctx, batch_axis=batch_axis)
      label = split_and_load(label, ctx_list=ctx, batch_axis=batch_axis)
      return data, label
  
file_path: mxnet/python/mxnet/gluon/contrib/estimator/batch_processor.py
imports: from ...utils import split_and_load
  from ....None import autograd
  from ....None import npx
label_desc: Use image node_id 2 for calling the BatchProcessor obj's underlying member method code with example usage: obj._get_data_and_label(batch, ctx, batch_axis) and returns: data,  label