Add files using upload-large-folder tool

.gitattributes

@@ -138,3 +138,4 @@ finetune/fomo_tune_baseline/output/task5/task5.sif filter=lfs diff=lfs merge=lfs
 finetune/fomo_tune_baseline/output/task3/task3.sif filter=lfs diff=lfs merge=lfs -text
 finetune/fomo_tune_baseline/output/task6_and_7/task6_and_7.sif filter=lfs diff=lfs merge=lfs -text
 finetune/fomo_tune_baseline/output/task2/task2.sif filter=lfs diff=lfs merge=lfs -text
+finetune/fomo_tune_v2/output/task1/task1.sif filter=lfs diff=lfs merge=lfs -text

finetune/fomo_tune_v2/build.sh

@@ -0,0 +1,35 @@
+#!/usr/bin/env bash
+# Package each trained run into its challenge .sif. Run on the login node, after launch.sh:
+# apptainer lives there and on a couple of compute nodes only, and a build needs no GPU driver.
+#
+# Slow. Apptainer always re-runs %post, so each run re-downloads ~3G of wheels.
+
+set -euo pipefail
+
+ROOT="$(git rev-parse --show-toplevel)"
+cd $ROOT
+
+set -a
+source .env
+set +a
+
+EXP_DIR="experiments/fomo_tune_v2"
+OUT_DIR="${EXP_DIR}/output"
+
+runs=(task1)
+
+for name in "${runs[@]}"; do
+    # build.py names the sif after `task` in the run's saved config, which is the run name here
+    sif="${OUT_DIR}/${name}/${name}.sif"
+
+    if [[ -f "${sif}" ]]; then
+        echo "sif ${sif} exists; skipping"
+        continue
+    fi
+
+    echo "=== ${name} ==="
+    uv run --no-sync python -m fomo_tune.build "${OUT_DIR}/${name}"
+done
+
+echo "=== sifs ==="
+ls -lh "${OUT_DIR}"/*/*.sif

finetune/fomo_tune_v2/launch.sh

@@ -0,0 +1,44 @@
+#!/usr/bin/env bash
+#SBATCH --job-name=fomo_tune_v2
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=1
+#SBATCH --cpus-per-task=16
+#SBATCH --gpus-per-task=1
+#SBATCH --time=2:00:00
+#SBATCH --partition=main
+#SBATCH --output=slurms/slurm-%j.out
+#SBATCH --account=sophont
+#SBATCH --qos=high
+
+set -euo pipefail
+
+ROOT="$(git rev-parse --show-toplevel)"
+cd $ROOT
+
+set -a
+source .env
+set +a
+
+EXP_DIR="experiments/fomo_tune_v2"
+OUT_DIR="${EXP_DIR}/output"
+
+runs=(
+    "task1 main_task1"
+)
+
+for run in "${runs[@]}"; do
+    read -r name module <<<"${run}"
+
+    if [[ -f "${OUT_DIR}/${name}/metrics.json" ]]; then
+        echo "result ${name} exists; skipping"
+        continue
+    fi
+
+    echo "=== ${name} ==="
+    uv run --no-sync python -m "fomo_tune.${module}" train \
+        output_root="${OUT_DIR}" \
+        name="${name}"
+done
+
+echo "=== results ==="
+cat "${OUT_DIR}"/*/metrics.json

finetune/fomo_tune_v2/output/task1/config.yaml

@@ -0,0 +1,14 @@
+task: task1
+ckpt_path: hf://medarc/walnut/checkpoints/walnut-v0-1/vitl/sub-52k/checkpoint-last.pth
+modalities:
+- dwi_b1000
+output_root: experiments/fomo_tune_v2/output
+name: task1
+device: cuda
+seed: 4466
+pooling: ensemble
+sweet_k: 8
+top_k: 32
+masking: zero
+normalize_volume: true
+normalize_test_volume: true

finetune/fomo_tune_v2/output/task1/log.txt

@@ -0,0 +1,39 @@
+20:23:13 run task1 (git 5e078be)
+20:23:13 config:
+task: task1
+ckpt_path: hf://medarc/walnut/checkpoints/walnut-v0-1/vitl/sub-52k/checkpoint-last.pth
+modalities:
+- dwi_b1000
+output_root: experiments/fomo_tune_v2/output
+name: task1
+device: cuda
+seed: 4466
+pooling: ensemble
+sweet_k: 8
+top_k: 32
+masking: zero
+normalize_volume: true
+normalize_test_volume: true
+20:23:16 dataset: 21 subjects, 13 positive
+20:23:27 fold 1/21 sub-01 y=1 p=0.491 (6s)
+20:23:28 fold 2/21 sub-02 y=1 p=0.609 (8s)
+20:23:30 fold 3/21 sub-03 y=0 p=0.291 (9s)
+20:23:31 fold 4/21 sub-04 y=1 p=0.556 (11s)
+20:23:33 fold 5/21 sub-05 y=1 p=0.690 (12s)
+20:23:35 fold 6/21 sub-06 y=1 p=0.570 (14s)
+20:23:36 fold 7/21 sub-07 y=0 p=0.375 (16s)
+20:23:38 fold 8/21 sub-08 y=0 p=0.171 (17s)
+20:23:40 fold 9/21 sub-09 y=1 p=0.598 (19s)
+20:23:41 fold 10/21 sub-10 y=1 p=0.439 (21s)
+20:23:43 fold 11/21 sub-11 y=0 p=0.218 (22s)
+20:23:45 fold 12/21 sub-12 y=0 p=0.163 (24s)
+20:23:46 fold 13/21 sub-13 y=1 p=0.683 (25s)
+20:23:48 fold 14/21 sub-14 y=1 p=0.735 (27s)
+20:23:49 fold 15/21 sub-15 y=0 p=0.376 (29s)
+20:23:51 fold 16/21 sub-16 y=0 p=0.356 (30s)
+20:23:53 fold 17/21 sub-17 y=1 p=0.820 (32s)
+20:23:54 fold 18/21 sub-18 y=1 p=0.613 (33s)
+20:23:56 fold 19/21 sub-19 y=1 p=0.548 (35s)
+20:23:57 fold 20/21 sub-20 y=1 p=0.697 (37s)
+20:23:59 fold 21/21 sub-21 y=0 p=0.442 (38s)
+20:24:03 result: auroc=0.9904  auroc_ci_low=0.9423  auroc_ci_high=1.0000  (38s)

finetune/fomo_tune_v2/output/task1/metrics.json

@@ -0,0 +1 @@
+{"name": "task1", "auroc": 0.9903846153846154, "auroc_ci_low": 0.9423076923076923, "auroc_ci_high": 1.0, "run_time": 38.3}

finetune/fomo_tune_v2/output/task1/model/config.yaml

@@ -0,0 +1,14 @@
+task: task1
+ckpt_path: hf://medarc/walnut/checkpoints/walnut-v0-1/vitl/sub-52k/checkpoint-last.pth
+modalities:
+- dwi_b1000
+output_root: experiments/fomo_tune_v2/output
+name: task1
+device: cuda
+seed: 4466
+pooling: ensemble
+sweet_k: 8
+top_k: 32
+masking: zero
+normalize_volume: true
+normalize_test_volume: true

finetune/fomo_tune_v2/output/task1/model/head.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c9fd56b28f2a61e495313bfd26299a0586591803829cde6423f0204854f9c8ce
+size 451042

finetune/fomo_tune_v2/output/task1/preds.json

@@ -0,0 +1,21 @@
+{"subject": "sub-01", "label": 1, "pred": 0.491472136704304}
+{"subject": "sub-02", "label": 1, "pred": 0.6093199237426591}
+{"subject": "sub-03", "label": 0, "pred": 0.2909684699367543}
+{"subject": "sub-04", "label": 1, "pred": 0.5558893095188939}
+{"subject": "sub-05", "label": 1, "pred": 0.690261512795603}
+{"subject": "sub-06", "label": 1, "pred": 0.570306563352876}
+{"subject": "sub-07", "label": 0, "pred": 0.3748935751485348}
+{"subject": "sub-08", "label": 0, "pred": 0.1709205118398878}
+{"subject": "sub-09", "label": 1, "pred": 0.598045599963261}
+{"subject": "sub-10", "label": 1, "pred": 0.43883673681300184}
+{"subject": "sub-11", "label": 0, "pred": 0.2175847096462739}
+{"subject": "sub-12", "label": 0, "pred": 0.16316933421097388}
+{"subject": "sub-13", "label": 1, "pred": 0.6829394784044932}
+{"subject": "sub-14", "label": 1, "pred": 0.7350728259020902}
+{"subject": "sub-15", "label": 0, "pred": 0.37598677859422797}
+{"subject": "sub-16", "label": 0, "pred": 0.3555539841165052}
+{"subject": "sub-17", "label": 1, "pred": 0.8199131412961741}
+{"subject": "sub-18", "label": 1, "pred": 0.613348945548139}
+{"subject": "sub-19", "label": 1, "pred": 0.5479371701641191}
+{"subject": "sub-20", "label": 1, "pred": 0.6966580161087733}
+{"subject": "sub-21", "label": 0, "pred": 0.4418168239812025}

finetune/fomo_tune_v2/output/task1/task1.sif

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f41f2beaf9a6995502dd5f263f74a5e99c50f0aa9a5659c6e8126326ed57c693
+size 5327015936

finetune/fomo_tune_v2/slurms/slurm-389736.out

@@ -0,0 +1,42 @@
+=== task1 ===
+20:23:13 run task1 (git 5e078be)
+20:23:13 config:
+task: task1
+ckpt_path: hf://medarc/walnut/checkpoints/walnut-v0-1/vitl/sub-52k/checkpoint-last.pth
+modalities:
+- dwi_b1000
+output_root: experiments/fomo_tune_v2/output
+name: task1
+device: cuda
+seed: 4466
+pooling: ensemble
+sweet_k: 8
+top_k: 32
+masking: zero
+normalize_volume: true
+normalize_test_volume: true
+20:23:16 dataset: 21 subjects, 13 positive
+20:23:27 fold 1/21 sub-01 y=1 p=0.491 (6s)
+20:23:28 fold 2/21 sub-02 y=1 p=0.609 (8s)
+20:23:30 fold 3/21 sub-03 y=0 p=0.291 (9s)
+20:23:31 fold 4/21 sub-04 y=1 p=0.556 (11s)
+20:23:33 fold 5/21 sub-05 y=1 p=0.690 (12s)
+20:23:35 fold 6/21 sub-06 y=1 p=0.570 (14s)
+20:23:36 fold 7/21 sub-07 y=0 p=0.375 (16s)
+20:23:38 fold 8/21 sub-08 y=0 p=0.171 (17s)
+20:23:40 fold 9/21 sub-09 y=1 p=0.598 (19s)
+20:23:41 fold 10/21 sub-10 y=1 p=0.439 (21s)
+20:23:43 fold 11/21 sub-11 y=0 p=0.218 (22s)
+20:23:45 fold 12/21 sub-12 y=0 p=0.163 (24s)
+20:23:46 fold 13/21 sub-13 y=1 p=0.683 (25s)
+20:23:48 fold 14/21 sub-14 y=1 p=0.735 (27s)
+20:23:49 fold 15/21 sub-15 y=0 p=0.376 (29s)
+20:23:51 fold 16/21 sub-16 y=0 p=0.356 (30s)
+20:23:53 fold 17/21 sub-17 y=1 p=0.820 (32s)
+20:23:54 fold 18/21 sub-18 y=1 p=0.613 (33s)
+20:23:56 fold 19/21 sub-19 y=1 p=0.548 (35s)
+20:23:57 fold 20/21 sub-20 y=1 p=0.697 (37s)
+20:23:59 fold 21/21 sub-21 y=0 p=0.442 (38s)
+20:24:03 result: auroc=0.9904  auroc_ci_low=0.9423  auroc_ci_high=1.0000  (38s)
+=== results ===
+{"name": "task1", "auroc": 0.9903846153846154, "auroc_ci_low": 0.9423076923076923, "auroc_ci_high": 1.0, "run_time": 38.3}