class_docstr: DataLoaderTransformers are used to transform the output of a DataLoader.
  DataLoader doesn't have easy access to the device or graph, so any
  computation that should happen there should use a DataLoaderTransformer.
code: def __init__(self, dataloader, index=None):
      super(DataLoaderTransformer, self).__init__()
  
      self.dataloader = dataloader
      self.index = index
  
      if self.index is not None:
          # input shape is contiguous
          data_size = np.prod(self.dataloader.shapes()[index])
          self._shape = (data_size, self.be.bsz)
  
imports: from __future__ import division
  import numpy
  from neon import NervanaObject
label_desc: Use image node_id 1 to create a new DataLoaderTransformer object from inherited base classes: NervanaObject with example: obj = DataLoaderTransformer(dataloader, index)