code: def _w_delta_squared_numpy(z, delta):
      """Computes W_delta(z) = sign(z) * (W(delta * z^2) / delta)^(1/2)."""
      if delta == 0:
          return z
  
      return np.where(
          z == 0.0,
          np.zeros_like(z),
          np.sign(z) * (_w0(delta * z**2.0) / delta) ** (0.5),
      )
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import lambertw_transform
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 2 for calling a global function with example usage: _w_delta_squared_numpy(z, delta) and returns: np, z