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| # reasons you might want to use `environment.yaml` instead of `requirements.txt`: | |
| # - pip installs packages in a loop, without ensuring dependencies across all packages | |
| # are fulfilled simultaneously, but conda achieves proper dependency control across | |
| # all packages | |
| # - conda allows for installing packages without requiring certain compilers or | |
| # libraries to be available in the system, since it installs precompiled binaries | |
| name: myenv | |
| channels: | |
| - pytorch | |
| - conda-forge | |
| - defaults | |
| # it is strongly recommended to specify versions of packages installed through conda | |
| # to avoid situation when version-unspecified packages install their latest major | |
| # versions which can sometimes break things | |
| # current approach below keeps the dependencies in the same major versions across all | |
| # users, but allows for different minor and patch versions of packages where backwards | |
| # compatibility is usually guaranteed | |
| dependencies: | |
| - pytorch=2.* | |
| - torchvision=0.* | |
| - lightning=2.* | |
| - torchmetrics=0.* | |
| - hydra-core=1.* | |
| - rich=13.* | |
| - pre-commit=3.* | |
| - pytest=7.* | |
| # --------- loggers --------- # | |
| # - wandb | |
| # - neptune-client | |
| # - mlflow | |
| # - comet-ml | |
| # - aim>=3.16.2 # no lower than 3.16.2, see https://github.com/aimhubio/aim/issues/2550 | |
| - pip>=23 | |
| - pip: | |
| - hydra-optuna-sweeper | |
| - hydra-colorlog | |
| - pyrootutils | |