| --- |
| license: mit |
| tags: |
| - counter-strike |
| - behavioural-cloning |
| - imitation-learning |
| - pytorch |
| - onnx |
| library_name: pytorch |
| --- |
| |
| # CSBC — PyTorch port of the Counter-Strike Behavioural Cloning model |
|
|
| A faithful PyTorch/ONNX conversion of Tim Pearce's |
| [Counter-Strike Behavioural Cloning](https://github.com/TeaPearce/Counter-Strike_Behavioural_Cloning) |
| model (`ak47_sub_55k_drop_d4_dmexpert_28`, stateful variant), produced for the |
| [Kairos](https://github.com/) GUI-agent project. |
|
|
| The original model is Keras / TensorFlow 2.3 (CUDA 10.1, won't use a 40-series |
| GPU). This port runs on any modern CUDA via PyTorch: EfficientNet-B0 trunk |
| (ONNX → onnx2torch) + a hand-written stateful ConvLSTM head. Verified numerically |
| equal to Keras (zero-state max diff ~5e-7, 3-frame stateful sequence ~2e-6), |
| ~3 ms/forward on a 4090. |
|
|
| ## Files |
|
|
| | file | what | |
| |---|---| |
| | `csbc_backbone.onnx` | feedforward EfficientNet-B0 trunk (loaded via onnx2torch) | |
| | `csbc_head_weights.npz` | ConvLSTM2D(256) + 5 dense-head weights (applied in torch) | |
| | `csbc_ref.npz` | Keras reference outputs on fixed inputs (for the torch self-test) | |
|
|
| ## Usage (Kairos) |
|
|
| ```bash |
| python examples/csbc_agent/scripts/download_torch_weights.py --repo-id JamesK2W/csbc-pytorch |
| python examples/csbc_agent/run.py --backend torch --model-dir examples/csbc_agent/models |
| ``` |
|
|
| ## I/O contract |
|
|
| - **Input:** one RGB frame → BGR → `cv2.resize` to 280×150 → float32 (no `/255`; |
| EfficientNet rescales internally). Tensor shape `(1, 150, 280, 3)`. |
| - **Output:** 52-vector — `[0:11]` keys (w a s d space ctrl shift 1 2 3 r), |
| `[11:13]` mouse L/R, `[13:36]` mouse-x argmax (23 buckets), `[36:51]` mouse-y |
| argmax (15 buckets), `[51]` value (ignored). |
| - **Stateful:** the ConvLSTM state persists across frames; call `reset_state()` |
| per episode and feed one frame at a time. |
|
|
| ## License & provenance |
|
|
| Weights derive from the upstream CSBC release (MIT). Academic / offline use only. |
|
|
