Hi! I'm trying to run the project, but I'm having problems setting u

Can not run the project about buddi HOT 1 OPEN

muelea commented on September 6, 2024

Can not run the project

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AndresCasado commented on September 6, 2024

Hi again.

I've managed to progress a bit in my attempt to run BUDDI. I had to install some additional packages.

  # Eventually update conda 
  # conda update conda
  conda create -n hhcenv39 python=3.9
  conda activate hhcenv39
  conda install -c pytorch pytorch=1.9.1 torchvision cudatoolkit=10.2
  conda install -c fvcore -c iopath -c conda-forge fvcore iopath
  conda install -c bottler nvidiacub
  conda install pytorch3d -c pytorch3d
  conda install -c conda-forge tensorboard
  pip install opencv-python smplx scipy scikit-image loguru omegaconf ipdb einops chumpy trimesh setuptools==58.2.0
+ conda install -c conda-forge gcc==12.3.0
+ conda install -c conda-forge gxx==12.3.0
  conda run -n hhcenv39 --live-stream pip install 'git+https://github.com/facebookresearch/detectron2.git' 
  pip install mmcv==1.3.9 timm
  pip install -v -e third-party/ViTPose/
  pip install simple_romp==1.1.3
+ pip install pyrender
+ pip install wandb

gxx was needed for the install of detectron2 to work. I'm not fully sure about gcc though.

pyrender and wandb dependencies arose when trying to run the script as stated below.

Then I tried running the script as stated in the README

python llib/methods/hhc_diffusion/evaluation/sample.py --exp-cfg essentials/buddi/buddi_unconditional.yaml --output-folder demo/diffusion/samples/ --checkpoint-name essentials/buddi/buddi_unconditional.pt --max-images-render=100 --num-samples 100 --max-t 1000 --skip-steps 10 --log-steps=100 --save-vis

However, the environment is still not correct.

First, it complains about some NumPy problem:

A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.0.0 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.

If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.

Then, another problem arises, some kind of incompatibility between my GPU, my CUDA install and the installed PyTorch version:

Traceback (most recent call last):  File "/home/my_linux_user/buddienv/buddi/llib/methods/hhc_diffusion/evaluation/sample.py", line 12, in <module>
    import torch
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/__init__.py", line 629, in <module>
    from .functional import *  # noqa: F403
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/functional.py", line 6, in <module>
    import torch.nn.functional as F
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/nn/__init__.py", line 1, in <module>
    from .modules import *  # noqa: F403
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/nn/modules/__init__.py", line 2, in <module>
    from .linear import Identity, Linear, Bilinear, LazyLinear
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 6, in <module>
    from .. import functional as F
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/nn/functional.py", line 11, in <module>
    from .._jit_internal import boolean_dispatch, _overload, BroadcastingList1, BroadcastingList2, BroadcastingList3
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/_jit_internal.py", line 26, in <module>
    import torch.package._mangling as package_mangling
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/package/__init__.py", line 12, in <module>
    from .package_importer import PackageImporter
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/package/package_importer.py", line 26, in <module>
    from ._mock_zipreader import MockZipReader
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/package/_mock_zipreader.py", line 17, in <module>
    _dtype_to_storage = {data_type(0).dtype: data_type for data_type in _storages}
  File "/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/package/_mock_zipreader.py", line 17, in <dictcomp>
    _dtype_to_storage = {data_type(0).dtype: data_type for data_type in _storages}
/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/package/_mock_zipreader.py:17: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at  /opt/conda/conda-bld/pytorch_1631630797748/work/torch/csrc/utils/tensor_numpy.cpp:67.)
  _dtype_to_storage = {data_type(0).dtype: data_type for data_type in _storages}
FOUND 0 matches for demo/diffusion/samples/generate_1000_10
/home/my_linux_user/.conda/envs/hhcenv39/lib/python3.9/site-packages/torch/cuda/__init__.py:106: UserWarning: 
NVIDIA GeForce RTX 3080 Ti with CUDA capability sm_86 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_61 sm_70 sm_75 compute_37.
If you want to use the NVIDIA GeForce RTX 3080 Ti GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/

  warnings.warn(incompatible_device_warn.format(device_name, capability, " ".join(arch_list), device_name))

I hope this helps in fixing/updating the dependencies.

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Can not run the project about buddi HOT 1 OPEN

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