ImportError: libtorch_cpu.so: undefined symbol: iJIT_IsProfilingActive about deep3dfacerecon_pytorch

[Megidd]

Looks like this is the underlying problem, I have explained: https://stackoverflow.com/q/78326712/3405291

[Megidd]

PIP errors are resolved now: https://stackoverflow.com/a/78327418/3405291

But the libtorch_cpu.so: undefined symbol: iJIT_IsProfilingActive remains:

(deep3d_pytorch) m3@i7:~/repos/Deep3DFaceRecon_pytorch> python test.py --name=facerecon_20230425 --epoch=20 --img_folder=custom_images
Traceback (most recent call last):
  File "test.py", line 5, in <module>
    from options.test_options import TestOptions
  File "/home/m3/repos/Deep3DFaceRecon_pytorch/options/test_options.py", line 4, in <module>
    from .base_options import BaseOptions
  File "/home/m3/repos/Deep3DFaceRecon_pytorch/options/base_options.py", line 6, in <module>
    from util import util
  File "/home/m3/repos/Deep3DFaceRecon_pytorch/util/util.py", line 5, in <module>
    import torch
  File "/home/m3/anaconda3/envs/deep3d_pytorch/lib/python3.6/site-packages/torch/__init__.py", line 189, in <module>
    from torch._C import *
ImportError: /home/m3/anaconda3/envs/deep3d_pytorch/lib/python3.6/site-packages/torch/lib/libtorch_cpu.so: undefined symbol: iJIT_IsProfilingActive

[Megidd]

Even a simple statement to get the PyTorch version throws the error:

(deep3d_pytorch) m3@i7:~/repos/Deep3DFaceRecon_pytorch> python -c "import torch; print(torch.__version__)"
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/home/m3/anaconda3/envs/deep3d_pytorch/lib/python3.6/site-packages/torch/__init__.py", line 189, in <module>
    from torch._C import *
ImportError: /home/m3/anaconda3/envs/deep3d_pytorch/lib/python3.6/site-packages/torch/lib/libtorch_cpu.so: undefined symbol: iJIT_IsProfilingActive

On both local machine and Google Colab:

Implication

Does it mean the PyTorch installation by Conda is broken?

[Megidd]

The error was resolved by just removing all some of the versions from and replacing the environment.yml file with just conda and pip commands. There were problems with the versions and mismatches between them like this one:

https://discuss.pytorch.org/t/libtorch-cpu-so-undefined-symbol/201101/2?u=megidd

[Megidd]

Google Colab

Our final approach on Google Colab that works just fine is:

# Step 1: Press runtime on the top > Change runtime type > Select T4 GPU

# Step 2: Run this shell

!wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
!bash miniconda.sh -b -u -p /usr/local
!rm miniconda.sh
!conda update -y conda

%cd /content/
!rm -rf Deep3DFaceRecon_pytorch
!git clone https://github.com/sicxu/Deep3DFaceRecon_pytorch.git
%cd Deep3DFaceRecon_pytorch
!git clone https://github.com/NVlabs/nvdiffrast
!git clone https://github.com/deepinsight/insightface.git
!cp -r ./insightface/recognition/arcface_torch ./models/

# Step 3: Mount drive and copy the files mounted in google drive:

!mkdir /content/Deep3DFaceRecon_pytorch/checkpoints
!cp -r /content/drive/MyDrive/Deep3D/facerecon_20230425 /content/Deep3DFaceRecon_pytorch/checkpoints/facerecon_20230425
!cp /content/drive/MyDrive/Deep3D/01_MorphableModel.mat /content/Deep3DFaceRecon_pytorch/BFM/
!cp /content/drive/MyDrive/Deep3D/Exp_Pca.bin /content/Deep3DFaceRecon_pytorch/BFM/

# Step 4: Install the graphics related stuff

!sudo apt-get install libegl1-mesa-dev
!nvidia-smi
!sudo apt-get install libnvidia-gl-535

# Step 5: Run this shell to install everything

%%shell
eval "$(conda shell.bash hook)"
conda create --name deep3d_pytorch python=3.6 -y
conda activate deep3d_pytorch
conda config --env --add channels pytorch
conda config --env --add channels conda-forge
conda config --env --add channels defaults
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.2 -c pytorch -y
conda install numpy scikit-image=0.16.2 scipy=1.4.1 pillow=6.2.1 pip ipython=7.13.0 yaml=0.1.7 -y
pip install matplotlib==2.2.5 opencv-python==3.4.9.33 tensorboard==1.15.0 tensorflow==1.15.0 kornia==0.5.5 dominate==2.6.0 trimesh==3.9.20
pip install ./nvdiffrast/.

# Step 6: Run this shell to test the program

%%shell
eval "$(conda shell.bash hook)"
conda activate deep3d_pytorch
python test.py --name=facerecon_20230425 --epoch=20 --img_folder=./datasets/examples

# Step 7: Copy test results to Google Drive

!ls /content/Deep3DFaceRecon_pytorch/checkpoints/facerecon_20230425/results/examples/epoch_20_000000/
!cp /content/Deep3DFaceRecon_pytorch/checkpoints/facerecon_20230425/results/examples/epoch_20_000000/* /content/drive/MyDrive/Deep3D/results/

# Step 8: prepare custom images along with their facial landmarks

!cp -r /content/drive/MyDrive/Deep3D/custom_images /content/Deep3DFaceRecon_pytorch/
%cd /content/Deep3DFaceRecon_pytorch/custom_images/
!python -m venv virtual_env
!source virtual_env/bin/activate && which pip
!source virtual_env/bin/activate && pip install mtcnn
!source virtual_env/bin/activate && pip install tensorflow
!source virtual_env/bin/activate && which python
!source virtual_env/bin/activate && python facial_landmarks.py # This Python script source code can be found here: https://github.com/sicxu/Deep3DFaceRecon_pytorch/issues/85#issuecomment-2069302718
%cd /content/Deep3DFaceRecon_pytorch/

# Step 9: run with custom images

%%shell
eval "$(conda shell.bash hook)"
conda activate deep3d_pytorch
python test.py --name=facerecon_20230425 --epoch=20 --img_folder=./custom_images

# Step 10: copy the results back to Google Drive

!ls /content/Deep3DFaceRecon_pytorch/checkpoints/facerecon_20230425/results/custom_images/epoch_20_000000/
!cp /content/Deep3DFaceRecon_pytorch/checkpoints/facerecon_20230425/results/custom_images/epoch_20_000000/* /content/drive/MyDrive/Deep3D/results/