class_docstr: Factorized prior to code a discrete tensor.
class_docstr_tok: ["Factorized","prior","to","code","a","discrete","tensor","."]
code: def compute_output_shape(self, input_shape):
      batch_size = input_shape[0]
      shapes = (
          input_shape,  # decoded
          [2],  # latent_shape = [height, width]
          [],  # total_nbpp
          [],  # total_qbpp
          [batch_size],  # bitstring
      )
      return tuple(tf.TensorShape(x) for x in shapes)
  
imports: import collections
  from compare_gan.architectures import abstract_arch
  from compare_gan.architectures import arch_ops
  import numpy
  import tensorflow.compat.v1
  import tensorflow_compression
  from hific.helpers import ModelMode
label_desc: Use image node_id 2 for calling the FactorizedPriorLayer obj's underlying member method code with example usage: obj.compute_output_shape(input_shape) and returns: tuple