code: def softplus(x, name="softplus"):
      """Like tf.math.reduce_logsumexp.
  
      This has no functional difference from the regular version, except that it's
      implemented inline here, allowing monkey-patching of the special functions it
      uses (e.g. exp).
  
      Args:
        x: A Tensor.
        name: Name for the op.
  
      Returns:
        y: softplus(x)
      """
      with tf.name_scope(name):
          x = tf.convert_to_tensor(x, dtype_hint=tf.float32)
          return tf.math.log1p(
              tf.math.exp(-tf.math.abs(x))
          ) + tf.math.maximum(x, 0)
  
imports: import contextlib
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import custom_gradient
  from tensorflow_probability.python.internal import dtype_util
label_desc: Use image node_id 2 for calling a global function with example usage: softplus(x, name) and returns: unknown