Can we remove the version for the dependencies in environment.yaml

autonomousvision / occupancy_networks

This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"

https://avg.is.tuebingen.mpg.de/publications/occupancy-networks

MIT License

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Can we remove the version for the dependencies in environment.yaml #122

Open XiaoyanQian opened 1 year ago

XiaoyanQian commented 1 year ago

Will this work?

environment.yaml

name: mesh_funcspace channels:

conda-forge
pytorch
defaults dependencies:
cython
imageio
numpy
numpy-base
matplotlib
matplotlib-base
pandas
pillow
pyembree
pytest
python
pytorch
pyyaml
scikit-image
scipy
tensorboardx
torchvision
tqdm
trimesh
pip
pip:
- h5py
- plyfile

liu-bohan commented 1 year ago

Don't think so, since PyTorch used in this project, v1.0.0, is such an old version, and newer versions may lead to incompatibility problems. in summary, executable but don't recommend .

XiaoyanQian commented 1 year ago

But I have cuda 11.4; there is also incompatibility of PyTorch of V1.0.0, right？

liu-bohan commented 1 year ago

According to PyTorch.org , Yes. you can try CUDA 10.0 on Ubuntu20.04 as a reference, which worked for me

XiaoyanQian commented 1 year ago

Thank you so much, But I have no cuda 10.0. Could we keep cuda 11.4 and cuda 10.0 in one server?

hahahahahahahap commented 11 months ago

of course. you can keep them in one server