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We use conda to install required packages:
conda env create -f env/equiformer_v2_torch1_ocp2.yml
This will create a new environment called
equiformer_v2_torch1_ocp2
. -
We activate the environment:
export PYTHONNOUSERSITE=True # prevent using packages from base conda activate equiformer_v2_torch1_ocp2
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Clone OC20 GitHub repository and install
ocpmodels
:git clone https://github.com/Open-Catalyst-Project/ocp.git cd ocp git checkout be0f727a515582b01e6c51672a08f5b693f015e9 pip install -e .
The corresponding version of OCP (FAIR Chemistry) is here.
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Since we reuse the original codebase of OCP (FAIR Chemistry) and provide a new trainer adding DeNS as an auxiliary task, we need to put this repository under the
ocp
codebase cloned above and rename toexperimental
:cd ocp git clone https://github.com/atomicarchitects/DeNS experimental
In this way, when we launch training under
ocp
, the OCP codebase will look intoexperimental
directory and find the new trainer and models contained in this DeNS repository.