code: def cdf(value, loc, scale, skewness):
      """Compute cumulative distribution function of Two-Piece Normal distribution.
  
      Note that scale and skewness can be negative.
  
      Args:
        value: Floating-point tensor; where to compute the cdf.
        loc: Floating-point tensor; the location(s) of the distribution(s).
        scale: Floating-point tensor; the scale(s) of the distribution(s).
        skewness: Floating-point tensor; the skewness(es) of the distribution(s).
  
      Returns:
        A tensor with shape broadcast according to the arguments.
      """
      value = tf.convert_to_tensor(value)
      loc = tf.convert_to_tensor(loc)
      scale = tf.convert_to_tensor(scale)
      skewness = tf.convert_to_tensor(skewness)
      dtype = value.dtype
  
      one = tf.constant(1.0, dtype=dtype)
      two = tf.constant(2.0, dtype=dtype)
  
      z = standardize(value, loc=loc, scale=scale, skewness=skewness)
      normal_cdf = _numpy_cast(special_math.ndtr(z), dtype)
  
      squared_skewness = tf.math.square(skewness)
      return tf.math.reciprocal(one + squared_skewness) * tf.where(
          z < 0.0,
          two * normal_cdf,
          one - squared_skewness + two * squared_skewness * normal_cdf,
      )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import custom_gradient
  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 reparameterization
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import special_math
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import special
  from tensorflow_probability.python.math.numeric import log1psquare
label_desc: Use image node_id 3 for calling a global function with example usage: cdf(value, loc, scale, skewness) and returns: unknown