code: def lisht(x: TensorLike) -> tf.Tensor:
      r"""LiSHT: Non-Parameteric Linearly Scaled Hyperbolic Tangent Activation Function.
  
      Computes linearly scaled hyperbolic tangent (LiSHT):
  
      $$
      \mathrm{lisht}(x) = x * \tanh(x).
      $$
  
      See [LiSHT: Non-Parameteric Linearly Scaled Hyperbolic Tangent Activation Function for Neural Networks](https://arxiv.org/abs/1901.05894).
  
      Usage:
  
      >>> x = tf.constant([1.0, 0.0, 1.0])
      >>> tfa.activations.lisht(x)
      <tf.Tensor: shape=(3,), dtype=float32, numpy=array([0.7615942, 0.       , 0.7615942], dtype=float32)>
  
      Args:
          x: A `Tensor`. Must be one of the following types:
              `bfloat16`, `float16`, `float32`, `float64`.
      Returns:
          A `Tensor`. Has the same type as `x`.
      """
      x = tf.convert_to_tensor(x)
      return x * tf.math.tanh(x)
  
label_desc: Use image node_id 1 for calling a global function with example usage: lisht(x) and returns: unknown