class_docstr: A distribution generated by applying a sequence of transformations to
  a base distribution/
  
  Parameters
  ----------
  base_dist : Distribution
      Base distribution
  transforms : Transformation or List
      Transformation to be applied
docstr: Compute the cumulative distribution function(CDF) p(Y < `value`)
code: def cdf(self, value):
      """
      Compute the cumulative distribution function(CDF) p(Y < `value`)
      """
      sign = np.ones_like(
          value
      )  # pylint: disable=too-many-function-args
      for t in reversed(self._transforms):
          value = t.inv(value)
          sign = sign * t.sign
      value = self._base_dist.cdf(value)
      return sign * (value - 0.5) + 0.5
  
file_path: mxnet/python/mxnet/gluon/probability/distributions/transformed_distribution.py
imports: from ..transformation import Transformation
  from .distribution import Distribution
  from .utils import sum_right_most
  from ....None import np
label_desc: Use image node_id 5 for calling the TransformedDistribution obj's underlying member method code with example usage: obj.cdf(value) and returns: unknown