foxhunt/AGENT_248_QUICK_REFERENCE.md

Agent 248: Quick Reference - Background Training Status

Date: 2025-10-15 Status: ❌ TRAINING FAILED - PROCESS TERMINATED

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TL;DR

❌ TRAINING FAILED: Matrix dimension bug in MAMBA-2 forward pass 🔴 URGENT FIX NEEDED: Add .t()? to B matrix matmul in ml/src/mamba/mod.rs ⏱️ ETA: 15-25 minutes (fix + test + validate)

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Status Summary

Aspect	Status	Details
Process Status	❌ Dead	All PIDs terminated (1106938, 1108510, 1258069)
Compilation	✅ Success	45.34s (warnings only)
Data Loading	✅ Success	7,223 messages, 72 sequences
Model Init	✅ Success	211,200 parameters
Training	❌ Failed	Matrix shape mismatch
Error	🔴 Critical	[32, 60, 512] @ [512, 16] incompatible

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Root Cause

Error Message:

Model error: Candle error: shape mismatch in matmul, lhs: [32, 60, 512], rhs: [512, 16]

Problem: B matrix initialized as [16, 512], needs transpose to [512, 16] for matmul

Location: ml/src/mamba/mod.rs → Mamba2SSM::forward_with_gradients()

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Fix Required

File: /home/jgrusewski/Work/foxhunt/ml/src/mamba/mod.rs

Method: forward_with_gradients()

Change:

// OLD (broken):
let b_proj = x.matmul(&self.b)?;

// NEW (fixed):
let b_proj = x.matmul(&self.b.t()?)?; // Transpose [16, 512] → [512, 16]

Alternative Fix (if transpose doesn't work):

let (batch_size, seq_len, features) = x.dims3()?;
let x_flat = x.reshape(&[batch_size * seq_len, features])?; // [1920, 512]
let b_proj_flat = x_flat.matmul(&self.b.t()?)?; // [1920, 16]
let b_proj = b_proj_flat.reshape(&[batch_size, seq_len, self.n])?; // [32, 60, 16]

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Testing Commands

# Step 1: Fix code
vim ml/src/mamba/mod.rs  # Add .t()? to B matrix matmul

# Step 2: Compile
cargo build -p ml --release

# Step 3: Unit test
cargo test -p ml mamba::tests --release

# Step 4: Integration test (1 epoch)
cargo run -p ml --example train_mamba2_dbn --release -- --epochs 1

# Step 5: If successful, run full training
nohup cargo run -p ml --example train_mamba2_dbn --release -- --epochs 200 > mamba2_training.log 2>&1 &
echo $! > mamba2_training.pid

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Key Findings

What Worked ✅

• CUDA device initialization (RTX 3050 Ti)
• DBN data loading (4 files, 0.01s per file)
• Feature extraction (7,223 messages → 72 sequences)
• Data splitting (80/20 train/val)
• Model initialization (211,200 parameters)
• Hardware detection (AVX2, AVX512)
• B matrix initialization (6 layers × [16, 512])

What Failed ❌

• First training batch execution
• Matrix multiplication in forward pass
• Training loop never started

What's Needed 🔴

• B matrix transpose fix
• Shape validation tests
• Gradient flow verification

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Recommendation

DO NOT RESTART TRAINING YET

1. Fix B matrix transpose bug (5 minutes)
2. Test with 1 epoch (10 minutes)
3. Verify gradient flow (5 minutes)
4. Then restart full 200 epoch training

Priority: 🔴 URGENT (blocks MAMBA-2 training) Blocking: ✅ NO (DQN, PPO, TFT can train independently)

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Next Agent

Agent 249: Fix MAMBA-2 B matrix dimension bug

Tasks:

1. Add .t()? to B matrix matmul
2. Test with 1 epoch
3. Verify shapes match expected dimensions
4. Add shape validation tests
5. Document fix in code comments