- Add unified experiment tracker (W&B + TensorBoard) with graceful fallback - Add gradient norm monitoring per param group (MONA, LoRA, MLP, gates, tau) - Add Grad-CAM visualization for DINOv3 drone/satellite encoders - Add PyTorch Profiler wrapper + torchinfo model summary - Add gin-config support to train_gtauav.py with CLI overrides - Add v3 gin configs: gtauav_balanced, gtauav_baseline, gtauav_text_heavy, gtauav_image_heavy - Generate metric plots every epoch (not just on eval) - Set default epochs to 10 - Update README and CLAUDE.md with new tooling and usage docs Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Plaintext
9 lines
269 B
Plaintext
# GTA-UAV Image-heavy: gate initialized high (more image weight).
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# query = sigma(0.9) * drone + 0.1 * text
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# Minimal text contribution test.
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include 'conf/gtauav_balanced.gin'
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TrainConfigGTAUAV.init_gate = 0.9
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TrainConfigGTAUAV.output_dir = "out/gtauav/image_heavy"
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