code: def forward_gpu(self, inputs):
      self.retain_inputs((0, 1))
      y, gy = inputs
      if (
          chainer.should_use_cudnn("==always")
          and self.x is not None
          and gy.flags.c_contiguous
      ):
          gx = cudnn.activation_backward(self.x, y, gy, _mode)
      else:
          gx = cuda.elementwise(
              "T y, T gy", "T gx", "gx = gy * (1 - y * y)", "tanh_bwd"
          )(y, gy)
      return (gx,)
  
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
  import chainerx
label_desc: Use image node_id 3 for calling the TanhGrad obj's underlying member method code with example usage: obj.forward_gpu(inputs) and returns: gx