Dose anyone meet the numda problem? there is a lot of warning when i running the pointpillar code.

[wangx1996]

Compilation is falling back to object mode WITH looplifting enabled because Function "points_in_convex_polygon_jit" failed type inference due to: Invalid use of Function() with argument(s) of type(s): (array(float32, 3d, C), (slice, list(int64), slice))

• parameterized In definition 0: All templates rejected with literals. In definition 1: All templates rejected without literals. In definition 2: All templates rejected with literals. In definition 3: All templates rejected without literals. In definition 4: All templates rejected with literals. In definition 5: All templates rejected without literals. In definition 6: All templates rejected with literals. In definition 7: All templates rejected without literals. In definition 8: All templates rejected with literals. In definition 9: All templates rejected without literals. In definition 10: TypeError: unsupported array index type list(int64) in (slice, list(int64), slice) raised from /home/wx/anaconda3/envs/pointpillars/lib/python3.7/site-packages/numba/typing/arraydecl.py:71 In definition 11: TypeError: unsupported array index type list(int64) in (slice, list(int64), slice) raised from /home/wx/anaconda3/envs/pointpillars/lib/python3.7/site-packages/numba/typing/arraydecl.py:71 This error is usually caused by passing an argument of a type that is unsupported by the named function. [1] During: typing of intrinsic-call at /home/wx/Downloads/second.pytorch-master/second/core/geometry.py (153)

File "../../second.pytorch-master/second/core/geometry.py", line 153: def points_in_convex_polygon_jit(points, polygon, clockwise=True):

    vec1 = polygon - polygon[:, [num_points_of_polygon - 1] +
                             list(range(num_points_of_polygon - 1)), :]

[Disfish9527]

These warnings don't seem to have any impact and the network can be trained and tested properly. If you're in trouble, you can block these warnings.

[wangx1996]

These warnings don't seem to have any impact and the network can be trained and tested properly. If you're in trouble, you can block these warnings.

Yes,you r right. These warnings don't impact the training. Thank you.

[micjabbour]

numba 0.44 started showing some deprecation warnings that mostly help users identify more rooms for optimization, see here for more details.

You can use numba 0.43.1 if you don't want to see these warnings.