class_docstr: Initialize the weight with coefficients for bilinear interpolation.
  
  A common use case is with the DeconvolutionLayer acting as upsampling.
  The variable tensor passed in the init function should have 5 dimensions
  of format [nGroup, nInput, nOutput, kH, kW], and kH should be equal to kW
class_docstr_tok: ["Initialize","the","weight","with","coefficients","for","bilinear","interpolation",".","A","common","use","case","is","with","the","DeconvolutionLayer","acting","as","upsampling",".","The","variable","tensor","passed","in","the","init","function","should","have","5","dimensions","of","format","[","nGroup",",","nInput",",","nOutput",",","kH",",","kW","]",",","and","kH","should","be","equal","to","kW"]
code: def __init__(self, bigdl_type="float"):
      JavaValue.__init__(self, None, bigdl_type)
  
imports: import sys
  from bigdl.dllib.utils.common import JavaValue
label_desc: Use image node_id 1 to create a new BilinearFiller object from inherited base classes: InitializationMethod with example: obj = BilinearFiller(bigdl_type)