feat(cnn_v3): add infer_cnn_v3.py + rewrite cnn_test for v3 parity

- cnn_v3/training/infer_cnn_v3.py: PyTorch inference tool; simple mode
  (single PNG, zeroed geometry) and full mode (sample directory); supports
  --identity-film (γ=1 β=0) to match C++ default, --cond for FiLM MLP,
  --blend, --debug-hex for pixel comparison
- tools/cnn_test.cc: full rewrite, v3 only; packs 20-channel features
  on CPU (training format: [0,1] oct normals, pyrdown mip), uploads to
  GPU, runs CNNv3Effect, reads back RGBA16Float, saves PNG; --sample-dir
  for full G-buffer input, --weights for .bin override, --debug-hex
- cmake/DemoTests.cmake: add cnn_v3/src include path, drop unused
  offscreen_render_target.cc from cnn_test sources
- cnn_v3/docs/HOWTO.md: new §10 documenting both tools, comparison
  workflow, and feature-format convention (training vs runtime)

handoff(Gemini): cnn_test + infer_cnn_v3.py ready for parity testing.
Run both with --identity-film / --debug-hex on same image to compare.

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