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conda-environment_py38_cu11_old.yml
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conda-environment_py38_cu11_old.yml
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name: work38_cu11
channels:
- pytorch
- fastai
- nvidia
- anaconda
- conda-forge
- defaults
dependencies:
- python>=3.8, <3.9
- cython=0.29.25
- cudatoolkit=11.1.74
- ffmpeg=4.4.1
- ffmpeg-python=0.2.0
- itk>=5.1.2
- itkwidgets>=0.32.0
- jupyter_client=7.0.5
- jupyter_core=4.8.1
- jupyterlab=2.2.9
- jupyterlab_pygments>=0.1.2
- jupyterlab_server>=1.2.0
- jupyterlab_widgets>=1.0.2
- libopencv=4.5.5
- matplotlib-base=3.2.2
- moviepy=1.0.1
- multidict=5.1.0
- murmurhash=1.0.5
# - ninja=1.10.2
- notebook=6.3.0
- numba=0.53.0 ## if numba crashing with a weird error, try installing with:
# LLVM_CONFIG=/usr/local/bin/llvm-config-12 CXXFLAGS=-fPIC pip --no-cache-dir install numba llvmlite
# the error in quesion : RuntimeError: Unable to find target for this triple (no targets are registered) Segfault
- opencv=4.5.5
- pandas=1.1.5
- pip=21.2.4
# - py-opencv=4.5.5
- pytorch=1.9.1=py38_cuda11.1_cudnn8.0.5_0
- pyvista>=0.26.1
- pyvistaqt>=0.2.0
- pywavelets=1.1.1
- pyyaml=5.4.1
- qt>=5.12.9
- resampy=0.2.2
- scikit-image=0.17.2
- scikit-learn=0.24.2
- seaborn=0.11.0
- tqdm=4.62.3
- vtk>=9.0.1
- wheel=0.37.0
- yaml=0.2.5
- yarl=1.6.3
- jiwer=3.0.1
- pip:
# - cython>=0.29.21
- adabound>=0.0.5
# - addict==2.4.0
- alabaster==0.7.12
- albumentations==1.0.2
- antlr4-python3-runtime==4.8
- astunparse==1.6.3
- babel==2.8.0
- beautifulsoup4==4.10.0
- chumpy==0.70
- compress-pickle==1.2.0
- configparser==5.0.1
- deepspeech-gpu==0.9.2
- docker-pycreds==0.4.0
- docutils==0.16
- dominate==2.6.0
- easydict==1.9
- face-alignment>=1.3.3
- facenet-pytorch==2.5.1
- filelock==3.0.12
- flatbuffers==1.12
- freetype-py==2.2.0
- gast==0.3.3
- gdown==4.2.1
- gitdb==4.0.5
- gitpython==3.1.11
- google-pasta==0.2.0
- grpcio==1.32.0
- hydra-core==1.0.5
- imagesize==1.2.0
- imgaug==0.4.0
- importlib-resources==5.1.0
- insightface==0.5.0
- install==1.3.5
- itk-core>=5.1.2
- itk-filtering>=5.1.2
- itk-meshtopolydata>=0.6.2
- itk-numerics>=5.1.2
- itk-registration>=5.1.2
- itk-segmentation>=5.1.2
- kaggle==1.5.12
- keras-preprocessing==1.1.2
- kornia==0.6.1
- lightning-bolts>=0.4.0
- matplotlib==3.3.4
- mediapipe==0.8.9.1
- memory-profiler==0.58.0
- mmcv==1.2.2
- munch==2.5.0
- numpy>=1.19.3
- # nvdiffrast==0.2.7
- omegaconf==2.0.6
- onnx==1.10.2
- onnxruntime-gpu==1.9.0
# - opencv-contrib-python==4.5.5.62
# - opencv-python==4.5.5.62
# - opencv-python-headless==4.5.5.62
- opt-einsum==3.3.0
- pathtools==0.1.2
- pillow==8.1.2
- prettytable==2.4.0
- promise==2.3
- protobuf==3.13.0
- #psbody-mesh==0.4
- psutil==5.7.3
- pyasn1-modules==0.2.8
- pydeprecate==0.3.1
- pyglet==1.5.11
- PyOpengl==3.1.5
# - # pyrender==0.1.39
- python-slugify==5.0.2
- python-speech-features==0.6
- pytorch-lightning==1.4.9
# - # pytorch3d==0.6.0
# - # pytorch3d==0.6.1
- pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py38_cu111_pyt191/download.html
- pyzmq==22.0.3
- scikit-sound==0.2.3
- scikit-video==1.1.11
- scipy==1.5.4
- sentry-sdk==0.19.2
- setuptools==54.2.0
- shapely==1.7.1
- shortuuid==1.0.1
- smmap==3.0.4
- smplx==0.1.26
- snowballstemmer==2.0.0
- soupsieve==2.3.1
- subprocess32==3.5.4
- #tb-nightly==2.5.0a20201210
- #tensorboard-data-server==0.6.1
- #tensorflow-estimator==2.3.0
- text-unidecode==1.3
- #tf-estimator-nightly==2.5.0.dev2020120901
- #tf-nightly==2.5.0.dev20201210
- tensorflow==2.8.0
- timm>=0.4.9
- torchaudio>=0.7.2
- torchfile==0.1.0
- torchgeometry==0.1.2
- torchmetrics==0.5.1
- torchvision==0.10.1
- trimesh==3.6.18
- wandb==0.10.30
- watchdog==0.10.3
- wrapt==1.12.1
- yapf==0.30.0
- youtube-dl==2021.6.6
- phonemizer==3.2.1
prefix: /home/rdanecek/anaconda3/envs/work38_cu11