tensorflow / tensorflow/probability
Unable to run 'Gaussian Process Regression in TensorFlow Probability' tutorial
Nobody has claimed this yet.
- Dominant language
- Jupyter Notebook
- Stars
- 4.4k
- Forks
- 1.1k
- PR merge metrics
- No merged PRs in 30d
Description
When I open and run the Gaussian Process tutorial on Colab, I get an error: ValueError: No gradients provided for any variable: ['amplitude:0', 'length_scale:0', 'observation_noise_variance_var:0'] in cell 9. The error goes away when I take out the @tf.function decorator on the log prob function. Is there a reason the code doesn't work with a @tf.function decorator?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Open the linked Gaussian Process Regression tutorial in Colab and reproduce the failure in cell 9. Inspect the log prob function and its @tf.function decorator, then compare the decorated and undecorated runs. Done means the tutorial executes successfully with gradients provided for the listed variables.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- tensorflow
- Domain
- documentation, machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 38/100