rpotter6298
512ebd13b2
- Introduced `protocol.py` for shared data models used in server/client communication, including request and response schemas for registration, job submission, and status updates. - Implemented `server.py` to manage a SQLite job queue and client registry, handling job polling, status updates, and job completion. - Created a cheat sheet for server usage, detailing commands for starting the server, submitting jobs, and monitoring clients. - Added several experiment configuration files for various training setups, including geometry vector injections and baseline ensembles.
150 lines
3.0 KiB
JSON
150 lines
3.0 KiB
JSON
{
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"_notes": [
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"Shared-weight bilateral architecture + GT geometry injection.",
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"img supplies geometry_vectors via EPC; cd consumes them.",
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"Same shared-weight structure as ensemble_fused.json."
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],
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"run_name": "v4/ensemble_fused_geom_gt",
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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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],
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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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"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": [
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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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"epc_supplies": [
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"geometry_vectors"
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],
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"args": {
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"backbone": "refugelike",
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"freeze_ratio": 0.0,
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"augment": true,
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"geometry_source": "gt",
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"contour_dir": "Papila/ExpertsSegmentations/Contours"
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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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"epc_requests": [
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"geometry_vectors"
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],
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"args": {
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"hidden_dim": 128,
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"geom_dim": 5
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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": "cd_warm",
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"type": "warm",
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"tower": "cd",
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"head_name": "cd_aux",
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"level": "eye",
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"epochs": 40
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},
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{
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"name": "img_aux",
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"type": "head",
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"input": "img",
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"train_with": "nt",
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"bcd": true
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},
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{
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"name": "cd_aux",
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"type": "head",
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"input": "cd",
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"train_with": "nt",
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"bcd": true
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},
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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": [
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"img",
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"cd"
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],
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"level": "eye",
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"epochs": 36,
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"train_towers": true,
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"warmup": {
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"tower_epochs": 3,
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"fused_epochs": 3
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},
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"args": {
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"fusion_dim": 256
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}
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},
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{
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"name": "nt_head",
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"type": "head",
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"input": "nt",
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"train_with": "nt"
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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": "nt",
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"b": "nt"
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},
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"level": "patient",
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"epochs": 10,
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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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"args": {
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"dropout": 0.3
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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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"bcd_prob": 0.5,
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"tune_binary_threshold": true
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}
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}
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