rpotter6298
88 lines
3.3 KiB
JSON
88 lines
3.3 KiB
JSON
{
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"_notes": [
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"Phase 5 — Full HyperTower: bilateral + clinical data + aggregation strategy comparison.",
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"Goal: show the effect of a dual CNN + clinical data, and compare ensemble vs fused-head.",
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"Best settings from all prior phases: refugelike, iop_ratio_drop_raw, bcd_p05.",
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"Best bilateral architecture from phase 4 should be used — update tower-mode accordingly.",
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"common_args are prepended to every run's args list.",
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"NOTE: update --tower-mode in groups below once phase 4 winner is known.",
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"Placeholder uses 'bilateral' — change to 'siamese' if that wins phase 4."
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],
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"common_args": [
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"--eval-mode", "binary",
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"--bridge-mode", "fused",
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"--epochs", "30",
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"--in-memory-cache",
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"--augment",
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"--tune-binary-threshold",
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"--backbone", "refugelike",
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"--iop-corr-method", "ratio",
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"--iop-drop-raw",
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"--exclude-cols", "Axial_Length",
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"--output-root", "v3/results"
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],
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"_common_args_implicit_defaults": {
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"--tower-loss-mode": "bcd",
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"--bcd-prob": "0.5",
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"--warmup-cd-epochs": "40",
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"--single-warmup-tower-epochs": "3",
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"--single-warmup-fused-epochs": "3",
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"--bilat-warmup-tower-epochs": "3",
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"--bilat-warmup-fused-epochs": "3"
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},
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"baseline": {
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"run_name": "phase5/single_fused",
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"description": "Single-eye + clinical data — phase 3 best config, re-run as direct comparison baseline for phase 5.",
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"extra_args": ["--hypertower-mode", "single"]
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},
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"groups": [
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{
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"name": "bilateral_clinical",
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"description": "Add clinical data to bilateral architectures.",
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"runs": [
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{
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"run_name": "phase5/ensemble_fused",
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"description": "Ensemble (independent OD+OS) + clinical data via fused bridge.",
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"extra_args": ["--hypertower-mode", "ensemble"]
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},
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{
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"run_name": "phase5/bilateral_fused",
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"description": "BilateralHT + clinical data — full canonical HyperTower.",
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"extra_args": ["--hypertower-mode", "bilateral"]
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},
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{
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"run_name": "phase5/siamese_fused",
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"description": "SiameseHT + clinical data — siamese mean+delta with fused clinical bridge.",
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"extra_args": ["--hypertower-mode", "siamese"]
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}
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]
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},
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{
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"name": "aggregation",
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"description": "Compare patient-level prediction aggregation strategies on top of ensemble.",
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"runs": [
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{
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"run_name": "phase5/ensemble_fused_head",
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"description": "Ensemble + clinical data + attention scorer head (Linear(C→1) per eye, softmax-weighted average).",
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"extra_args": ["--hypertower-mode", "ensemble", "--fused-head"]
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},
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{
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"run_name": "phase5/logit_mlp_head",
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"description": "Ensemble + clinical data + logit-level MLP head (cat([logit_od, logit_os]) → FC(64) → FC(C)).",
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"extra_args": ["--hypertower-mode", "ensemble", "--fused-head", "--head-type", "logit_mlp"]
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},
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{
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"run_name": "phase5/embedding_mlp_head",
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"description": "Ensemble + clinical data + embedding-level MLP head (cat([z_od, z_os]) → FC(256) → FC(C)).",
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"extra_args": ["--hypertower-mode", "ensemble", "--fused-head", "--head-type", "embedding_mlp"]
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}
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]
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}
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]
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}
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