class_docstr: Logistic sigmoid function.
class_docstr_tok: ["Logistic","sigmoid","function","."]
code: def forward_cpu(self, inputs):
      x = inputs[0]
      half = x.dtype.type(0.5)
      y = utils.force_array(numpy.tanh(x * half) * half + half)
      self.retain_outputs((0,))
      self._use_cudnn = False
      return (y,)
  
imports: import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import function_node
  from chainer import utils
  from chainer.utils import type_check
label_desc: Use image node_id 2 for calling the Sigmoid obj's underlying member method code with example usage: obj.forward_cpu(inputs) and returns: y