tensorflow / tensorflow/probability
hypergeometric series unreliable for simple values
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Description
The current implementation of hyp2f1 outputs wrong results for certain basic values, for example:
import tensorflow_probability as tfp
hyp2f1 = tfp.math.hypergeometric.hyp2f1_small_argument
H = 1
hyp2f1(1.0, 0.5 - H, H + 1.5, 9/10) # NaN
This happens under tensorflow_probability==0.24.0 and tensorflow==2.17.1 (e.g. under the current image used by Colab)
The correct result is
from scipy import special
hyp2f1 = special.hyp2f1
hyp2f1(1.0, 0.5 - H, H + 1.5, 9/10) # 0.7836799547024426
Contributor guide
First steps
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Research direction
Start by reproducing the reported call to hyp2f1_small_argument with TensorFlow Probability 0.24.0 and TensorFlow 2.17.1, then trace that entry point to its implementation and existing tests. Compare the result with scipy.special.hyp2f1 for the supplied values; done means the basic case returns the expected finite value without breaking other cases.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- backend
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100