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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,48 @@ | ||
| #!/bin/bash -l | ||
| #SBATCH --partition=gpu | ||
| #SBATCH --nodes=1 | ||
| #SBATCH --gpus-per-node=1 | ||
| #SBATCH --cpus-per-task=1 | ||
| #SBATCH --ntasks=1 | ||
| #SBATCH --mem=8GB | ||
| #SBATCH --time=24:00:00 | ||
| #SBATCH --job-name=equireact | ||
| #SBATCH --array=0-9 | ||
| #SBATCH --exclude=i39 | ||
|
|
||
| SEED=$(( $SLURM_ARRAY_TASK_ID + 123 )) | ||
|
|
||
| module purge | ||
| conda activate equireact | ||
| python -c 'import torch; print(torch.cuda.is_available())' | ||
| wandb enabled | ||
|
|
||
| python train.py \ | ||
| --device cuda \ | ||
| --experiment_name final-cv-80 \ | ||
| --CV 1 \ | ||
| --num_epochs 512 \ | ||
| --seed ${SEED} \ | ||
| --logdir /scratch/izar/briling/cv \ | ||
| --dataset cyclo \ | ||
| --train_frac 0.8 \ | ||
| --combine_mode diff \ | ||
| --distance_emb_dim 48 \ | ||
| --dropout_p 0.1 \ | ||
| --graph_mode energy \ | ||
| --lr 0.001 \ | ||
| --max_neighbors 50 \ | ||
| --n_conv_layers 2 \ | ||
| --n_s 64 \ | ||
| --n_v 48 \ | ||
| --radius 2.5 \ | ||
| --sum_mode node \ | ||
| --weight_decay 0.00001 \ | ||
| --two_layers_atom_diff \ | ||
| --atom_mapping \ | ||
| --splitter random \ | ||
| --noH \ | ||
| --wandb_name lc-cv10-cyclo-inv-random-noH-dft-true-ns64-nv48-d48-l2-energy-diff-node \ | ||
| --invariant \ | ||
| --learning_curve \ | ||
|
|
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,47 @@ | ||
| #!/bin/bash -l | ||
| #SBATCH --partition=gpu | ||
| #SBATCH --nodes=1 | ||
| #SBATCH --gpus-per-node=1 | ||
| #SBATCH --cpus-per-task=1 | ||
| #SBATCH --ntasks=1 | ||
| #SBATCH --mem=8GB | ||
| #SBATCH --time=24:00:00 | ||
| #SBATCH --job-name=equireact | ||
| #SBATCH --array=0-9 | ||
| #SBATCH --exclude=i39 | ||
|
|
||
| SEED=$(( $SLURM_ARRAY_TASK_ID + 123 )) | ||
|
|
||
| module purge | ||
| conda activate equireact | ||
| python -c 'import torch; print(torch.cuda.is_available())' | ||
| wandb enabled | ||
|
|
||
| python train.py \ | ||
| --device cuda \ | ||
| --experiment_name final-cv-80 \ | ||
| --CV 1 \ | ||
| --num_epochs 512 \ | ||
| --seed ${SEED} \ | ||
| --logdir /scratch/izar/briling/cv \ | ||
| --dataset cyclo \ | ||
| --train_frac 0.8 \ | ||
| --combine_mode diff \ | ||
| --distance_emb_dim 48 \ | ||
| --dropout_p 0.1 \ | ||
| --graph_mode energy \ | ||
| --lr 0.001 \ | ||
| --max_neighbors 50 \ | ||
| --n_conv_layers 2 \ | ||
| --n_s 64 \ | ||
| --n_v 48 \ | ||
| --radius 2.5 \ | ||
| --sum_mode node \ | ||
| --weight_decay 0.00001 \ | ||
| --two_layers_atom_diff \ | ||
| --atom_mapping \ | ||
| --splitter random \ | ||
| --noH \ | ||
| --wandb_name lc-cv10-cyclo-random-noH-dft-true-ns64-nv48-d48-l2-energy-diff-node \ | ||
| --learning_curve \ | ||
|
|