class_docstr: RDFT reparameterization of a convolution kernel.
  
  This uses the real-input discrete Fourier transform (RDFT) of a kernel as
  its parameterization. The inverse RDFT is applied to the variable to produce
  the kernel.
  
  (see https://en.wikipedia.org/wiki/Discrete_Fourier_transform)
  
  Attributes:
    shape: `tf.TensorShape`. The shape of the convolution kernel.
    real: `tf.Variable`. The real part of the RDFT of the kernel.
    imag: `tf.Variable`. The imaginary part of the RDFT of the kernel.
code: def shape(self) -> tf.TensorShape:
      return self._shape
  
imports: import abc
  from typing import Any, Dict
  import tensorflow
  from tensorflow_compression.python.ops import math_ops
label_desc: Use image node_id 3 for calling the RDFTParameter obj's underlying member method code with example usage: obj.shape() and returns: self