# SPDX-License-Identifier: Apache-2.0
"""CPU reference of FRNet (Autoware lidar_frnet) -- the ground truth every PCC / output-agreement gate compares
against (PLAN.md 0.3 item 1). It runs where ttnn is absent (the research venv) and never imports ttnn.

- ``config.py``    the Autoware parameters this port reproduces (``ml_package_frnet_<variant>.param.yaml`` of the
                   weights, ``frnet.param.yaml`` node parameters) and the COMPILE constants, each with its source line;
- ``weights.py``   the deployed ONNX read as data with the vendored ``ttaw.weights.OnnxWeights`` (initializers by
                   consuming node; structure and every wiring assumption checked on the graph; BN folded in float64
                   into the point layers, ``pre_norm`` kept as the host's scale / shift) -- the loader the TT port
                   uses too;
- ``model.py``     fp32 torch rebuild of the deployed graph with per-module taps (``ttaw.golden.TapRegistry``; names
                   in ``weights.MODULE_TAPS`` / ``OPT_IN_TAPS``), ported from research/frnet/scripts/frnet_torch_ref.py;
- ``rewrites.py``  the TT device dataflow (sorted + padded points, gather-form scatters with a zero sentinel row, the
                   exact log-step segmented max, K-split convs and point layers, interpolation-matrix up-sampling)
                   proven equal to ``model.py`` on the CPU, and a first-order precision emulation;
- ``ort.py``       ONNX Runtime golden of the deployed ONNX with matching intermediates (research / tests only:
                   onnxruntime is not in the image);
- ``pipeline.py``  the reference end to end: ``host/`` pre-processing -> torch / ORT / plan network -> ``host/``
                   post-processing -> ``FRNetSegmentation``.

Pre- and post-processing are not duplicated here: they live in ``tt_frnet.host`` (shared with the device path, so
TT and CPU see identical network inputs) and are tested against the research scripts.

The reduced ``to_dict()`` of the ORT reference on a sample is stored per variant next to it as
``samples/synthetic_<variant>.<variant>.reference.json``: ``server/smoke_test.py`` compares the served output with it.
"""