message: Adds usage example for log_sigmoid
diff: @@ -3718,6 +3718,27 @@ def log_sigmoid(x, name=None):
  Returns:
  A Tensor with the same type as `x`.
  +
  + Usage Example:
  +
  + If a positive number is large, then its log_sigmoid will approach to 0 since the
  + formula will be `y = log( <large_num> / (1 + <large_num>) )` which approximates to `log 1` which is 0
  +
  + >>> x = tf.constant([0.0, 1.0, 50.0, 100.0])
  + >>> tf.math.log_sigmoid(x)
  + <tf.Tensor: shape=(4,), dtype=float32, numpy=
  + array([-6.9314718e-01, -3.1326169e-01, -1.9287499e-22, -0.0000000e+00],
  + dtype=float32)>
  +
  + If a negative number is large, its log_sigmoid will approach to the number itself since the
  + formula will be `y = log( 1 / (1 + <large_num>) )` which is `log 1 - log ( (1 + <large_num>) )` which
  + approximates to `- <large_num>` that is the number itself.
  +
  + >>> x = tf.constant([-100.0, -50.0, -1.0, 0.0])
  + >>> tf.math.log_sigmoid(x)
  + <tf.Tensor: shape=(4,), dtype=float32, numpy=
  + array([-100. , -50. , -1.3132616, -0.6931472],
  + dtype=float32)>
  """
  with ops.name_scope(name, "LogSigmoid", [x]) as name:
  x = ops.convert_to_tensor(x, name="x")
  