class_docstr: Softplus gradient function.
class_docstr_tok: ["Softplus","gradient","function","."]
code: def __init__(self, inputs):
      super(SoftplusGrad, self).__init__()
      self.beta = inputs[0]
  
imports: import numpy
  from chainer.backends import cuda
  from chainer import function_node
  import chainer.functions
  from chainer import utils
  from chainer.utils import type_check
label_desc: Use image node_id 1 to create a new SoftplusGrad object from inherited base classes: function_node with example: obj = SoftplusGrad(inputs)