Add g2q eval metrics and asymmetric MONA-24 configs
- _evaluate: compute R@K + AP for both directions (q2g and g2q) via inverted ground truth; g2q denominator counts only sat-tiles with at least one positive drone in the (sub)sampled query set. Surfaces in train.csv, val.csv, train_recall.csv, W&B summary, and final log. - conf/gtauav_balanced_asym.gin: asymmetric WEB+SAT encoders, MONA in all 24 ViT blocks (~17.6M trainable / ~733M total). - conf/gtauav_baseline_asym.gin: same architecture, baseline_mode=True for Δ R@1 against balanced_asym. - CLAUDE.md / README.md: document new configs, clarify that g2q is now computed (was claimed but missing). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
16
conf/gtauav_balanced_asym.gin
Normal file
16
conf/gtauav_balanced_asym.gin
Normal file
@@ -0,0 +1,16 @@
|
||||
# GTA-UAV Balanced (asymmetric, full MONA): WEB drone encoder + SAT satellite encoder.
|
||||
# MONA injected into all 24 ViT blocks of each encoder.
|
||||
# Same loss/sampling/optimizer as gtauav_balanced.gin; differs only in model arch.
|
||||
#
|
||||
# Trainable: ~17.6M (MONA 2× × 24 blocks + LoRA + TextFusionMLP + gates + tau)
|
||||
# Total params: ~733M (2× DINOv3-L + DGTRS-CLIP)
|
||||
# VRAM target (RTX 4090, 24 GB): ~16-20 GB at batch=8 with gradient checkpointing.
|
||||
|
||||
include 'conf/gtauav_balanced.gin'
|
||||
|
||||
# ---- Model overrides: asymmetric + full MONA ----
|
||||
TrainConfigGTAUAV.shared_encoder = False # WEB for drone, SAT for satellite
|
||||
TrainConfigGTAUAV.mona_last_n_blocks = 24 # MONA in all 24 ViT blocks (was 12)
|
||||
|
||||
# ---- Output ----
|
||||
TrainConfigGTAUAV.output_dir = "out/gtauav/balanced_asym"
|
||||
Reference in New Issue
Block a user