class_docstr: Logistic sigmoid function.
class_docstr_tok: ["Logistic","sigmoid","function","."]
code: def forward_gpu(self, inputs):
      x = inputs[0]
      if chainer.should_use_cudnn("==always") and x.flags.c_contiguous:
          y = cudnn.activation_forward(x, _mode)
          self.retain_inputs((0,))
          self._use_cudnn = True
      else:
          y = cuda.elementwise(
              "T x",
              "T y",
              "y = tanh(x * 0.5) * 0.5 + 0.5",
              "sigmoid_fwd",
          )(x)
          self._use_cudnn = False
  
      self.retain_outputs((0,))
      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 3 for calling the Sigmoid obj's underlying member method code with example usage: obj.forward_gpu(inputs) and returns: y