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knot_weights function expects only a int (but not a tensor) as a parameter #707

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TMS-Namespace opened this issue Dec 2, 2022 · 0 comments

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@TMS-Namespace
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TMS-Namespace commented Dec 2, 2022

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: tensorflow/tensorflow#27491 (comment)

@TMS-Namespace TMS-Namespace changed the title knot_weights function requires a numpy int (but not a tensor) as a parameter knot_weights function requires a numpy int (but not a tensor) as a parameter Dec 2, 2022
@TMS-Namespace TMS-Namespace changed the title knot_weights function requires a numpy int (but not a tensor) as a parameter knot_weights function expects only a numpy int (but not a tensor) as a parameter Dec 2, 2022
@TMS-Namespace TMS-Namespace changed the title knot_weights function expects only a numpy int (but not a tensor) as a parameter knot_weights function expects only a int (but not a tensor) as a parameter Dec 2, 2022
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