class_docstr: Initializes weights as bilinear upsampling kernel.
  
  Example
  -------
  >>> # Given 'module', an instance of 'mxnet.module.Module',
  initialize weights to bilinear upsample...
  >>> init = mx.initializer.BilinearUpSample()
  >>> module.init_params(init)
  >>> for dictionary in module.get_params():
  ...     for key in dictionary:
  ...         print(key)
  ...         print(dictionary[key].asnumpy())
  ...
  fullyconnected0_weight
  [[ 0.  0.  0.]]
code: def __init__(self):
      super(BilinearUpSample, self).__init__()
  
imports: from __future__ import absolute_import
  import warnings
  import math
  import mxnet
  from mxnet.context import cpu
  from mxnet.gluon import nn
  from mxnet.gluon import contrib
  from ..model_zoo import get_model
label_desc: Use image node_id 1 to create a new BilinearUpSample object from inherited base classes: mx.init with example: obj = BilinearUpSample()