tensorflow / tensorflow/probability
Feature request: Computing gradients wrt op 'Placeholder' inside while loop
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Description
I am using the BFGS optimizer and the used loss if a function of gradients with respect to a Placeholder. I am running into this problem:
ValueError: Cannot compute gradient inside while loop with respect to op 'Placeholder'. We do not support taking the gradient wrt or through the initial value of a loop variable. Gradients can be computed through loop invariants or wrt the input parameters to the loop body.
Could this be easily fixed?
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
Start by reproducing the reported ValueError with the BFGS optimizer and a loss that depends on gradients with respect to a Placeholder inside a while loop. Investigate the loop-gradient limitation described in the error; done means gradients can be computed for that case without breaking the existing supported loop-gradient behavior.
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Assessment
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100