Add script to run sweeps for all seeds

run_sweep.sh

@@ -0,0 +1,18 @@
+#!/bin/bash -e
+
+dataset=${1:-"pubmed"}
+n_seeds=${2:-5}
+gpu_name=${3:-"gypsum-1080ti"}
+
+for ((i = 1; i <= ${n_seeds}; i++)); do
+  JOB_DESC=${dataset}_sweep${i} && JOB_NAME=${JOB_DESC}_$(date +%s) && \
+  sbatch -J ${JOB_NAME} -e jobs/${JOB_NAME}.err -o jobs/${JOB_NAME}.log \
+    --partition=${gpu_name} --gres=gpu:1 --mem=80G --time=12:00:00 \
+    run_sbatch.sh e2e_scripts/train.py \
+    --dataset="${dataset}" \
+    --dataset_random_seed=${i} \
+    --wandb_sweep_name="main_${dataset}_${i}" \
+    --wandb_sweep_params="wandb_configs/sweeps/e2e_main.json" \
+    --skip_initial_eval --sdp_eps=1e-1
+  echo "    Logs: jobs/${JOB_NAME}.err"
+done

wandb_configs/sweeps/e2e_main.json

@@ -9,6 +9,6 @@
     "dropout_p": {"values": [0, 0.1, 0.2, 0.3, 0.4, 0.5]},
     "use_lr_scheduler": {"values": [true, false]},
     "lr_scheduler": {"values": ["plateau", "step"]},
-    "subsample_sz": {"value": [100]},
+    "subsample_sz": {"value": 100},
     "activation": {"values": ["leaky_relu", "relu"]}
 }