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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)
The text was updated successfully, but these errors were encountered:
TMS-Namespace
changed the title
knot_weights function requires a numpy int (but not a tensor) as a parameterknot_weights function requires a numpyint (but not a tensor) as a parameter
Dec 2, 2022
TMS-Namespace
changed the title
knot_weights function requires a numpyint (but not a tensor) as a parameterknot_weights function expects only a numpyint (but not a tensor) as a parameter
Dec 2, 2022
TMS-Namespace
changed the title
knot_weights function expects only a numpyint (but not a tensor) as a parameterknot_weights function expects only a int (but not a tensor) as a parameter
Dec 2, 2022
The
knot_weights
function, from:tensorflow_graphics.math.interpolation.bspline
requires an
int
for thenumber of knots
and thedegree
parameters (it is mentioned in the documentation), and if atf.constant
is passed, theunhashable 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)The text was updated successfully, but these errors were encountered: