tensorflow / tensorflow/graphics
`knot_weights` function expects only a `int` (but not a `tensor`) as a parameter
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Description
The knot_weights function, from:
tensorflow_graphics.math.interpolation.bspline
requires an int for the number of knots and the degree parameters (it is mentioned in the documentation), and if a tf.constant is passed, the unhashable tensor exception will occur.
Although it is not really a bug, this seems to be a design flaw, and not expected at all (especially that other parameters are expecting tensors), since it breaks graph generation with @tf.function, unless I will convert it explicitly to int, as pointed here: https://github.com/tensorflow/tensorflow/issues/27491#issuecomment-890887810
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Research direction
Start at tensorflow_graphics.math.interpolation.bspline.knot_weights and reproduce the reported failure by passing tf.constant values, especially inside @tf.function. Determine the intended handling of tensor inputs and verify the chosen behavior with focused tests; done means graph generation no longer raises the unhashable-tensor exception.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100