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env_new.yaml
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name: primekg
channels:
- pytorch
- nvidia
- defaults
- conda-forge
- huggingface
- pyg
dependencies:
- bs4=4.11.1
- cudatoolkit=11.7
- dataclasses=0.8
- gudhi=3.0.0
- ipykernel=6.14.0
- ipython=8.4.0
- ipython_genutils=0.2.0
- joblib=1.2.0
- jupyter_client=7.3.4
- jupyter_core=4.11.1
- jupyter_server=1.18.1
- jupyterlab=3.4.7
- jupyterlab_pygments=0.2.2
- jupyterlab_server=2.15.1
- lxml=4.8.0
- nbclassic=0.4.3
- nbconvert-core=7.0.0
- nbconvert-pandoc=7.0.0
- notebook=6.4.12
- packaging=22
- pillow=9.0.1
- python=3.8.19
- pytorch=1.13.1
- requests=2.28.1
- pip:
- aiohttp==3.10.11
- anndata==0.9.1
- biopython==1.81
- cmappy==4.0.1
- cython==0.29.24
- datasets==2.6.1
- descriptastorus==2.8.0
- dgl==1.1.1
- dgllife==0.3.2
- einops==0.6.0
- h5py==3.7.0
- huggingface-hub==0.11.0
- ipython-genutils==0.2.0
- ipywidgets==7.7.2
- jsonpickle==1.5.2
- matplotlib==3.6.3
- networkx==3.1
- ninja==1.10.2.3
- numba==0.57.0
- numpy==1.24.4
- pandas==2.0.1
- plotly==6.0.0
- pygtop==2.1.5
- python-dotenv==1.0.1
- python-louvain==0.16
- pyyaml==6.0
- rdkit==2022.9.5
- sacred==0.8.4
- scanpy==1.9.3
- scikit-learn==1.2.1
- scipy==1.10.1
- seaborn==0.13.2
- seml==0.3.7
- setuptools==75.3.0
- statsmodels==0.13.5
- tiktoken==0.7.0
- torch-geometric==2.3.1
- pyg-lib @ https://data.pyg.org/whl/torch-1.13.0%2Bcu117/pyg_lib-0.3.1%2Bpt113cu117-cp38-cp38-linux_x86_64.whl
- torch-scatter @ https://data.pyg.org/whl/torch-1.13.0%2Bcu117/torch_scatter-2.0.9-cp38-cp38-linux_x86_64.whl
- torch-cluster @ https://data.pyg.org/whl/torch-1.13.0%2Bcu117/torch_cluster-1.6.0+pt113cu117-cp38-cp38-linux_x86_64.whl
- torchdrug==0.2.1
- torchmetrics==0.11.4
- tqdm==4.64.1
- transformers==4.11.3
- umap-learn==0.5.3
- wandb==0.19.6