| |
| """CPU fp32 reference of METEOR (TIER IV, AutowareFoundation/meteor v1.0, ``meteor_v157c3Z.onnx``): the ground truth |
| every PCC / output-agreement gate compares against (PLAN.md 0.3 item 1; research/meteor/SPEC.md section 6). |
| |
| Layout (importable without ttnn; torch / onnx are imported inside the functions that need them): |
| |
| - ``config.py`` the compile-time constants of the deployed graph (cameras, sizes, bins, crops, class lists) and |
| the load-time options (``input_norm``, ``depth_mean_bins``), each with its source. |
| - ``weights.py`` ``MeteorWeights``: the ONNX parsed as data with the vendored ``ttaw.weights`` (parameters |
| addressed by their consuming node; conv attributes from the graph; BN already folded by the |
| export), plus a graph check that the file is the deployed network. |
| - ``model.py`` ``MeteorNet``: the whole graph in torch fp32 (a node-by-node transliteration) with per-module taps. |
| - ``port_form.py`` the TT port's exact rewrites (input scale fold, merged heads, paint fold, tgate + tfuse merge, |
| traj_stem without the zero history channels, the lift from host tables) with CPU proofs. |
| - ``pipeline.py`` ``MeteorReference``: the end-to-end frame (network + the shared host pre / post-processing), |
| stateless ``run_frame`` and the API-equivalent ``__call__``. |
| - ``ort.py`` the ONNX Runtime oracle with any internal tensor as a named tap (research and tests only; |
| onnxruntime is NOT a runtime dependency of the image). |
| |
| There is no Autoware package for METEOR: the pre- and post-processing reproduced in ``tt_meteor.host`` are METEOR's own |
| runtimes (tier4/METEOR @ dc193a81e9959de57b751e269127ae9b67e3f300, ``deploy/cpp``). |
| |
| The ``to_dict()`` of this reference's output on the shipped sample is stored as |
| ``samples/<sample stem>.reference.json``: ``server/smoke_test.py`` compares the served output with it. |
| """ |
|
|
