class_docstr: Indexed entropy model model which implements Universal Quantization.
  
  In contrast to the base class, which uses rounding for quantization, here
  "quantization" is performed additive uniform noise, which is implemented with
  Universal Quantization.
  
  This is described in Sec. 3.2. in the paper
  > "Universally Quantized Neural Compression"<br />
  > Eirikur Agustsson & Lucas Theis<br />
  > https://arxiv.org/abs/2006.09952
class_docstr_tok: ["Indexed","entropy","model","model","which","implements","Universal","Quantization",".","In","contrast","to","the","base","class",",","which","uses","rounding","for","quantization",",","here","''","quantization","''","is","performed","additive","uniform","noise",",","which","is","implemented","with","Universal","Quantization",".","This","is","described","in","Sec",".","3.2.","in","the","paper",">","``","Universally","Quantized","Neural","Compression","''","<","br","\/",">",">","Eirikur","Agustsson","&","Lucas","Theis","<","br","\/",">",">","https",":","\/\/arxiv.org\/abs\/2006.09952"]
docstr: Class or factory function returning a `Distribution` object.
docstr_tok: ["Class","or","factory","function","returning","a","`","Distribution","`","object","."]
code: def prior_fn(self):
      """Class or factory function returning a `Distribution` object."""
      return self._prior_fn
  
imports: import functools
  import tensorflow
  from tensorflow_compression.python.entropy_models import continuous_base
  from tensorflow_compression.python.ops import gen_ops
  from tensorflow_compression.python.ops import math_ops
label_desc: Use image node_id 5 for calling the UniversalIndexedEntropyModel obj's underlying member method code with example usage: obj.prior_fn() and returns: self