RuntimeError: OpenGL 4.4 or later is required / WSL2 Ubuntu 20.04

[adevra]

I am able to build and run in windows 11 without problems,
Now trying to build in WSL2 Ubuntu20.04 but having this error,

I did nvdiffrasts basic triangle.py test to see if it gives any errors,
with --cuda flag, it outputs tri.png
with --opengl it gives error and thats the same error I get after running demo

(deep3d) adunix@DESKTOP-JH0UJT1:~/Deep3DFaceRecon_pytorch/nvdiffrast/samples/torch$ python triangle.py --cuda
Saving to 'tri.png'.
(deep3d) adunix@DESKTOP-JH0UJT1:~/Deep3DFaceRecon_pytorch/nvdiffrast/samples/torch$ python triangle.py --opengl
Traceback (most recent call last):
  File "triangle.py", line 21, in <module>
    glctx = dr.RasterizeGLContext()
  File "/home/adunix/anaconda3/envs/deep3d/lib/python3.6/site-packages/nvdiffrast/torch/ops.py", line 221, in __init__
    self.cpp_wrapper = _get_plugin(gl=True).RasterizeGLStateWrapper(output_db, mode == 'automatic', cuda_device_idx)
RuntimeError: OpenGL 4.4 or later is required
Segmentation fault
(deep3d) adunix@DESKTOP-JH0UJT1:~/Deep3DFaceRecon_pytorch/nvdiffrast/samples/torch$

any ideas?
thanks in advance

[adevra]

(deep3d) adunix@DESKTOP-JH0UJT1:~/Deep3DFaceRecon_pytorch$ python test.py --name=ade --epoch=20 --img_folder=./datasets/examples
/home/adunix/anaconda3/envs/deep3d/lib/python3.6/site-packages/kornia/augmentation/augmentation.py:1875: DeprecationWarning: GaussianBlur is no longer maintained and will be removed from the future versions. Please use RandomGaussianBlur instead.
  category=DeprecationWarning,
/home/adunix/anaconda3/envs/deep3d/lib/python3.6/site-packages/torch/utils/cpp_extension.py:4: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
  import imp
----------------- Options ---------------
                add_image: True
               bfm_folder: BFM
                bfm_model: BFM_model_front.mat
                 camera_d: 10.0
                   center: 112.0
          checkpoints_dir: ./checkpoints
             dataset_mode: None
                 ddp_port: 12355
        display_per_batch: True
                    epoch: 20                                   [default: latest]
          eval_batch_nums: inf
                    focal: 1015.0
                  gpu_ids: 0
               img_folder: ./datasets/examples                  [default: examples]
                init_path: checkpoints/init_model/resnet50-0676ba61.pth
                  isTrain: False                                [default: None]
                    model: facerecon
                     name: ade                                  [default: face_recon]
                net_recon: resnet50
                    phase: test
                   suffix:
                  use_ddp: False                                [default: True]
              use_last_fc: False
                  verbose: False
           vis_batch_nums: 1
               world_size: 1
                    z_far: 15.0
                   z_near: 5.0
----------------- End -------------------
model [FaceReconModel] was created
loading the model from ./checkpoints/ade/epoch_20.pth
0 ./datasets/examples/000002.jpg
Traceback (most recent call last):
  File "test.py", line 72, in <module>
    main(0, opt,opt.img_folder)
  File "test.py", line 62, in main
    model.test()           # run inference
  File "/home/adunix/Deep3DFaceRecon_pytorch/models/base_model.py", line 162, in test
    self.forward()
  File "/home/adunix/Deep3DFaceRecon_pytorch/models/facerecon_model.py", line 139, in forward
    self.pred_vertex, self.facemodel.face_buf, feat=self.pred_color)
  File "/home/adunix/anaconda3/envs/deep3d/lib/python3.6/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/adunix/Deep3DFaceRecon_pytorch/util/nvdiffrast.py", line 58, in forward
    self.glctx = dr.RasterizeGLContext(device=device)
  File "/home/adunix/anaconda3/envs/deep3d/lib/python3.6/site-packages/nvdiffrast/torch/ops.py", line 221, in __init__
    self.cpp_wrapper = _get_plugin(gl=True).RasterizeGLStateWrapper(output_db, mode == 'automatic', cuda_device_idx)
RuntimeError: OpenGL 4.4 or later is required
Segmentation fault

[adevra]

I guess this one solves it, recloning now
#108 (comment)

[adevra]

still the same

Transfer BFM09 to BFM_model_front......
model [FaceReconModel] was created
loading the model from ./checkpoints/ade/epoch_20.pth
0 ./datasets/examples/000002.jpg
Traceback (most recent call last):
  File "test.py", line 72, in <module>
    main(0, opt,opt.img_folder)
  File "test.py", line 62, in main
    model.test()           # run inference
  File "/home/adunix/Deep3DFaceRecon_pytorch/models/base_model.py", line 162, in test
    self.forward()
  File "/home/adunix/Deep3DFaceRecon_pytorch/models/facerecon_model.py", line 139, in forward
    self.pred_vertex, self.facemodel.face_buf, feat=self.pred_color)
  File "/home/adunix/anaconda3/envs/deep3d_pytorch/lib/python3.6/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/adunix/Deep3DFaceRecon_pytorch/util/nvdiffrast.py", line 58, in forward
    self.glctx = dr.RasterizeGLContext(device=device)
  File "/home/adunix/anaconda3/envs/deep3d_pytorch/lib/python3.6/site-packages/nvdiffrast/torch/ops.py", line 221, in __init__
    self.cpp_wrapper = _get_plugin(gl=True).RasterizeGLStateWrapper(output_db, mode == 'automatic', cuda_device_idx)
RuntimeError: OpenGL 4.4 or later is required
Segmentation fault

[adevra]

The developer of nvdiffrast answered and solved this issue.
NVlabs/nvdiffrast#90 (comment)