tensorflow / tensorflow/graphics
`tensorflow_graphics.shape.check_static(...)` throwing error in TF2
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Description
I was writing a data augmentation layer for a PointNet implementation and ran into what appears to be a bug in tensorflow_graphics.shape.check_static(...), as seen on this line.
Offending layer:
class RandomRot(Layer):
def __init__(self):
super(RandomRot, self).__init__()
def build(self, input_shape):
self.s = tf.constant([input_shape[-1],])
def call(self, inputs, training=None):
if not training: return inputs
r = tf.random.uniform(
shape=self.s,
minval=0,
maxval=6.28,
)
return tf.linalg.matmul(inputs,from_euler(r))
Error message:
AttributeError: in user code:
<ipython-input-135-d11754641da6>:81 call *
self.x = self.r(self.x,training)
<ipython-input-130-07bfe7ac5ab9>:25 call *
return tf.linalg.matmul(inputs,from_euler(r))
/usr/local/lib/python3.6/dist-packages/tensorflow_graphics/geometry/transformation/rotation_matrix_3d.py:201 from_euler *
shape.check_static(
/usr/local/lib/python3.6/dist-packages/tensorflow_graphics/util/shape.py:206 check_static *
if _get_dim(tensor, axis) != value:
/usr/local/lib/python3.6/dist-packages/tensorflow_graphics/util/shape.py:135 _get_dim *
return tensor.shape[axis].value
AttributeError: 'int' object has no attribute 'value'
It appears that check_static is expecting each element from .shape to be a tensor, but in TF2 they're just ints. If I comment out check_static from from_euler, the function works fine. Strangely enough, it seems to work fine for tensors in eager execution, and only seems to throw errors when using Dataset objects with graph compilation.
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- Open a pull request that references the issue number.
Research direction
Start by reproducing the TensorFlow 2 graph-mode failure with the reported RandomRot layer and Dataset usage. Read tensorflow_graphics/geometry/transformation/rotation_matrix_3d.py around from_euler and tensorflow_graphics/util/shape.py around check_static and _get_dim; done means the same graph-compilation path no longer raises the reported AttributeError.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- computer-graphics, machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100