Add new regression and ensemble experiment configurations for V2-M and OrthoBridge
- Introduced multiple regression experiment configurations targeting vf_md, including: - cd_solo_reg_set.json: CD tower only regression setup. - img_solo_reg_set.json: Image tower only regression setup. - reg_head_epoch_sweep.json: Baseline regression sweeps at different epochs (50, 75, 100). - reg_head_set.json: Various regression setups including baseline and OrthoBridge configurations. - single_eye_reg.json: Single-eye regression setup for worst-eye aggregation analysis. - Added ensemble configurations for OrthoBridge with different inner bridges: - ortho_alts_ensemble.json: Ensemble tests with ConcatBridge, PairwiseAdditiveBridge, and GatedAdditiveBridge. - ortho_alts_tritower.json: Tritower tests with the same inner bridges. - Created V2-M specific configurations: - baseline_reg_nt50.json: Regression baseline with V2-M backbone. - geom_vec_gt.json and geom_vec_unet.json: Geometry vector injection experiments with V2-M. - single_l1_bridges.json: Single-eye ensemble experiments with various bridge types. - tritower_geom_gt.json: Tritower setup with GT contour-rasterized masks. - Promoted existing experiments to higher repetitions for robustness.
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{
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"_notes": [
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"Single-rep checkpointed run of the production bilateral img+cd ensemble",
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"at the refuge_efficientnet_v2_m backbone. Per-fold tower and stage_models",
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"state_dicts are saved under {output_root}/{run_name}/binary/checkpoints/",
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"fold{N}/ for downstream explainability (Grad-CAM, attribution, etc.).",
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"",
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"Same architecture as ensemble_fused.json — only changes are:",
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" • img.args.backbone = refuge_efficientnet_v2_m",
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" • save_checkpoints = true",
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" • run_name = experiments/explainability/ensemble_v2m_ckpt"
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],
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"run_name": "experiments/explainability/ensemble_v2m_ckpt",
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"num_classes": 2,
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"label_filter": [0, 1],
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"split_identity_level": 1,
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"eval_stage": "hb",
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"save_predictions": true,
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"save_checkpoints": true,
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"seed": 1234,
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"folds": 5,
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"fold_seed": 100,
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"output_root": "v4/results",
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"out_dir_tags": ["binary"],
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"data": {
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"module": "v4.classes.profiles.v4papila",
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"args": {
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"image_dir": "Papila/FundusImages",
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"clinical_dir": "Papila/ClinicalData",
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"label_col": "Diagnosis",
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"iop_corr_method": "ratio",
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"iop_drop_raw": true,
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"exclude_cols": ["Axial_Length"],
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"in_memory_cache": true
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}
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},
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"towers": [
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{
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"name": "img",
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"module": "v4.classes.towers.image_tower",
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"class": "ImageEncoder",
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"data_source": "image",
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"args": {
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"backbone": "refuge_efficientnet_v2_m",
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"freeze_ratio": 0.0,
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"augment": true
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}
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},
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{
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"name": "cd",
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"module": "v4.classes.towers.clinical_tower",
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"class": "ClinicalEncoder",
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"data_source": "matrix",
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"args": { "hidden_dim": 128 }
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}
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],
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"stages": [
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{ "name": "cd_warm", "type": "warm", "tower": "cd", "head_name": "cd_aux", "level": "eye", "epochs": 40 },
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{ "name": "img_aux", "type": "head", "input": "img", "train_with": "nt", "bcd": true },
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{ "name": "cd_aux", "type": "head", "input": "cd", "train_with": "nt", "bcd": true },
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{
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"name": "nt",
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"type": "fusion",
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"module": "v4.classes.bridges.fusion_bridge",
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"class": "FusionBridge",
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"inputs": ["img", "cd"],
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"level": "eye",
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"epochs": 36,
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"train_towers": true,
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"warmup": { "tower_epochs": 3, "fused_epochs": 3 },
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"args": { "fusion_dim": 256 }
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},
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{ "name": "nt_head", "type": "head", "input": "nt", "train_with": "nt" },
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{
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"name": "hb",
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"type": "fusion",
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"module": "v4.classes.bridges.hyperbridge",
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"class": "HyperBridge",
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"inputs": { "a": "nt", "b": "nt" },
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"level": "patient",
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"epochs": 10,
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"args": { "hidden_dim": 256, "mode": "embedding_mlp" }
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},
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{ "name": "hb_head", "type": "head", "input": "hb", "train_with": "hb", "args": { "dropout": 0.3 } }
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],
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"training": {
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"lr": 1e-4,
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"batch_size": 8,
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"bcd_prob": 0.5,
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"tune_binary_threshold": true
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}
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}
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