class_docstr: Add bias to `Convolution` in BatchNormalization folding case if it doesn't have bias.
  
  Supported folding functions: `Convolution`, `Deconvolution`, `Affine`.
  
  Examples:
  
  .. code-block:: python
  
     pred = Model(...)
  
     import nnabla.experimental.graph_converters as GC
  
     modifiers = [GC.AddBiasModifier()]
     gc = GC.GraphConverter(modifiers)
     pred = gc.convert(pred)
class_docstr_tok: ["Add","bias","to","`","Convolution","`","in","BatchNormalization","folding","case","if","it","does","n't","have","bias",".","Supported","folding","functions",":","`","Convolution","`",",","`","Deconvolution","`",",","`","Affine","`",".","Examples",":","..","code-block",":",":","python","pred","=","Model","(","...",")","import","nnabla.experimental.graph_converters","as","GC","modifiers","=","[","GC.AddBiasModifier","(",")","]","gc","=","GC.GraphConverter","(","modifiers",")","pred","=","gc.convert","(","pred",")"]
code: def __init__(self):
      super(AddBiasModifier, self).__init__()
  
imports: import nnabla
  import nnabla.functions
  import numpy
  from nnabla.initializer import ConstantInitializer
  from nnabla.parameter import get_parameter_or_create
  from .graph_converter import FunctionModifier
label_desc: Use image node_id 1 to create a new AddBiasModifier object from inherited base classes: FunctionModifier, BatchNormBase with example: obj = AddBiasModifier()