rpotter6298
280060db82
- 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.
115 lines
2.5 KiB
JSON
115 lines
2.5 KiB
JSON
{
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"_notes": [
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"Smoke test: convnextv2_tiny backbone, single fold, few epochs.",
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"Goal is to verify the new ConvNeXt-V2 path works end-to-end (load weights,",
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"forward, backward, save summary). Not for measuring quality."
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],
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"run_name": "smoke/convnextv2_tiny",
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"num_classes": 2,
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"label_filter": [
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0,
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1,
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2
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],
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"split_identity_level": 1,
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"eval_stage": "hb",
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"save_predictions": false,
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"seed": 1234,
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"folds": 3,
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"fold_seed": 100,
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"output_root": "v4/results",
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"out_dir_tags": [
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"binary"
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],
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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": [
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"Axial_Length"
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],
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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": "convnextv2_tiny",
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"freeze_ratio": 0.6,
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"augment": true
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}
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}
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],
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"stages": [
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{
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"name": "img_fuse",
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"type": "fusion",
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"module": "v4.classes.bridges.mono_bridge",
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"class": "MonoBridge",
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"inputs": [
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"img"
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],
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"level": "eye",
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"epochs": 2,
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"train_towers": true,
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"args": {
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"use_ln": false
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}
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},
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{
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"name": "img_fuse_head",
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"type": "head",
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"input": "img_fuse",
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"train_with": "img_fuse",
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"module": "v4.classes.heads.regression",
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"class": "RegressionHead",
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"args": {
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"dropout": 0.3,
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"target_key": "vf_md",
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"loss": "mse"
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}
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},
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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": {
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"a": "img_fuse",
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"b": "img_fuse"
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},
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"level": "patient",
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"epochs": 2,
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"args": {
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"hidden_dim": 256,
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"mode": "embedding_mlp"
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}
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},
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{
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"name": "hb_head",
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"type": "head",
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"input": "hb",
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"train_with": "hb",
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"module": "v4.classes.heads.regression",
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"class": "RegressionHead",
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"args": {
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"dropout": 0.3,
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"target_key": "vf_md",
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"loss": "mse"
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}
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}
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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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"tune_binary_threshold": true
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}
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} |