From 87a27bf022d7fba68e3a945ee29c854c6e1ae2d7 Mon Sep 17 00:00:00 2001
From: skal <pascal.massimino@gmail.com>
Date: Fri, 13 Feb 2026 23:32:32 +0100
Subject: CNN v2: Add debugging tools for mismatch investigation

Add identity weight generator and composited layer save for debugging
HTML/C++ output differences.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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 doc/CNN_V2_DEBUG_TOOLS.md | 126 ++++++++++++++++++++++++++++++++++++++++++++++
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+# CNN v2 Debugging Tools
+
+Tools for investigating CNN v2 mismatch between HTML tool and cnn_test.
+
+---
+
+## Identity Weight Generator
+
+**Purpose:** Generate trivial .bin files with identity passthrough for debugging.
+
+**Script:** `training/gen_identity_weights.py`
+
+**Usage:**
+```bash
+# 1×1 identity (default)
+./training/gen_identity_weights.py workspaces/main/weights/cnn_v2_identity.bin
+
+# 3×3 identity
+./training/gen_identity_weights.py workspaces/main/weights/cnn_v2_identity_3x3.bin --kernel-size 3
+
+# Custom mip level
+./training/gen_identity_weights.py output.bin --kernel-size 1 --mip-level 2
+```
+
+**Output:**
+- Single layer, 12D→4D (4 input channels + 8 static features)
+- Identity matrix: Output Ch{0,1,2,3} = Input Ch{0,1,2,3}
+- Static features (Ch 4-11) are zeroed
+- Minimal file size (~136 bytes for 1×1, ~904 bytes for 3×3)
+
+**Validation:**
+Load in HTML tool or cnn_test - output should match input (RGB only, ignoring static features).
+
+---
+
+## Composited Layer Visualization
+
+**Purpose:** Save current layer view as single composited image (4 channels side-by-side, grayscale).
+
+**Location:** HTML tool - "Layer Visualization" panel
+
+**Usage:**
+1. Load image + weights in HTML tool
+2. Select layer to visualize (Static 0-3, Static 4-7, Layer 0, Layer 1, etc.)
+3. Click "Save Composited" button
+4. Downloads PNG: `composited_layer{N}_{W}x{H}.png`
+
+**Output:**
+- 4 channels stacked horizontally
+- Grayscale representation
+- Useful for comparing layer activations across tools
+
+---
+
+## Debugging Strategy
+
+### Track a) Binary Conversion Chain
+
+**Hypothesis:** Conversion error in .bin ↔ base64 ↔ Float32Array
+
+**Test:**
+1. Generate identity weights:
+   ```bash
+   ./training/gen_identity_weights.py workspaces/main/weights/test_identity.bin
+   ```
+
+2. Load in HTML tool - output should match input RGB
+
+3. If mismatch:
+   - Check Python export: f16 packing in `export_cnn_v2_weights.py` line 105
+   - Check HTML parsing: `unpackF16()` in `index.html` line 805-815
+   - Check weight indexing: `get_weight()` shader function
+
+**Key locations:**
+- Python: `np.float16` → `view(np.uint32)` (line 105 of export script)
+- JS: `DataView` → `unpackF16()` → manual f16 decode (line 773-803)
+- WGSL: `unpack2x16float()` built-in (line 492 of shader)
+
+### Track b) Layer Visualization
+
+**Purpose:** Confirm layer outputs match between HTML and C++
+
+**Method:**
+1. Run identical input through both tools
+2. Save composited layers from HTML tool
+3. Compare with cnn_test output
+4. Use identity weights to isolate weight loading from computation
+
+### Track c) Trivial Test Case
+
+**Use identity weights to test:**
+- Weight loading (binary parsing)
+- Feature generation (static features)
+- Convolution (should be passthrough)
+- Output packing
+
+**Expected behavior:**
+- Input RGB → Output RGB (exact match)
+- Static features ignored (all zeros in identity matrix)
+
+---
+
+## Known Issues
+
+**Current mismatch:** HTML tool and cnn_test produce different outputs for same input/weights.
+
+**Suspects:**
+1. F16 unpacking difference (CPU vs GPU vs JS)
+2. Static feature generation (RGBD, UV, sin encoding)
+3. Convolution kernel iteration order
+4. Output packing/unpacking
+
+**Next steps:**
+1. Test with identity weights (eliminates weight loading)
+2. Compare composited layer outputs
+3. Add debug visualization for static features
+4. Hex dump comparison (first 8 pixels) - use `--debug-hex` flag in cnn_test
+
+---
+
+## Related Documentation
+
+- `doc/CNN_V2.md` - CNN v2 architecture
+- `doc/CNN_V2_WEB_TOOL.md` - HTML tool documentation
+- `doc/CNN_TEST_TOOL.md` - cnn_test CLI tool
+- `training/export_cnn_v2_weights.py` - Binary export format
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