code: def _SoftplusGradGrad(op: ops.Operation, grad):
      # Let:
      #   y = tf.nn.softplus(x)
      #   dx = gen_nn_ops.softplus_grad(dy, x) = dy / (1 + exp(-x))
      # This op computes (ddy, d2x) from op.inputs == [dy, x] and grad == ddx.
      dy, x = op.inputs
      with ops.control_dependencies([grad]):
          ddy = gen_nn_ops.softplus_grad(grad, x)
          d2x = grad * dy / (math_ops.exp(-x) + 2.0 + math_ops.exp(x))
          return (ddy, d2x)
  
imports: import functools
  import itertools
  import operator
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import math_ops
label_desc: Use image node_id 29 for calling a global function with example usage: _SoftplusGradGrad(op, grad) and returns: ddy,  d2x