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If you do not know the root cause of the problem / bug, and wish someone to help you, please
post according to this template:
🐛 Bugs / Unexpected behaviors
Instructions To Reproduce the Issue:
- Open the Fit Mesh tutorial page
- Click the Open in Colab link at the top of the page
- Add a cell to install torchvision and pytorch3d as described in the tutorial overview and as corrected in Fix typo in tutorial code markdown #27 (if not yet merged/published)
- Run the cell to install torch vision and pytorch3d
- Run the cell immediately below 0. Import Modules which includes the line
from pytorch3d.structures import Meshes
Expected behavior:
Cell succeeds
Actual behavior:
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-14-d743ebcdab4d> in <module>()
2 import torch
3 from pytorch3d.io import load_obj, save_obj
----> 4 from pytorch3d.structures import Meshes
5 from pytorch3d.utils import ico_sphere
6 from pytorch3d.ops import sample_points_from_meshes
1 frames
/usr/local/lib/python3.6/dist-packages/pytorch3d/structures/meshes.py in <module>()
4 import torch
5
----> 6 from pytorch3d import _C
7
8 from . import utils as struct_utils
ImportError: /usr/local/lib/python3.6/dist-packages/pytorch3d/_C.cpython-36m-x86_64-linux-gnu.so: undefined symbol: _Z24RasterizeMeshesNaiveCudaRKN2at6TensorES2_S2_ifib
---------------------------------------------------------------------------
NOTE: If your import is failing due to a missing package, you can
manually install dependencies using either !pip or !apt.
To view examples of installing some common dependencies, click the
"Open Examples" button below.
---------------------------------------------------------------------------
Please include the following (depending on what the issue is):
- Any changes you made (
git diff
) or code you wrote
<put diff or code here>
- The exact command(s) you ran:
- What you observed (including the full logs):
<put logs here>
Please also simplify the steps as much as possible so they do not require additional resources to
run, such as a private dataset.
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