code: def _xexp_delta_squared(u, delta):
      """Applies `u * exp(u^2 * delta / 2)` transformation to the input `u`.
  
      Args:
        u: Input of the transformation.
        delta: Parameter delta of the transformation. For `delta=0` it reduces to
          the identity function.
  
      Returns:
        The transformed tensor with same shape and same dtype as `u`.
      """
      delta = tf.convert_to_tensor(delta, dtype=u.dtype)
      u = tf.broadcast_to(
          u, ps.broadcast_shape(ps.shape(u), ps.shape(delta))
      )
      return u * tf.math.exp(0.5 * delta * u**2)
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import special
label_desc: Use image node_id 1 for calling a global function with example usage: _xexp_delta_squared(u, delta) and returns: unknown