Add deep training acceptance checks

README.md

@@ -64,6 +64,12 @@ weight discovery. MMSeg full-model readiness is validated in
 `SEG_MMSEG_CONDA_ENV` by importing `mmcv._ext` and building a local MMSeg
 `EncoderDecoder` from the existing config tree.
 
+For stronger runtime proof, `POST /api/acceptance/deep` runs minimal training
+loops for the three model families: one SegModel optimizer step, one YOLO
+segmentation epoch on a synthetic 64x64 dataset, and one MMSeg optimizer step
+through the full `mmcv._ext` runtime. The latest report is available from
+`GET /api/acceptance/deep/latest` and is surfaced in the coverage panel.
+
 Current `seg_smp` uses `mmcv-lite` because no `torch 2.6/cu124` full `mmcv`
 wheel is available on this machine and `nvcc` is not installed for source
 builds. A dedicated `seg_mmcv` environment is used for MMSeg tasks and has
@@ -138,4 +144,5 @@ The validation agent checks catalog coverage, the `seg_smp` task env, the
 `seg_mmcv` MMSeg env, GPU visibility, no-weight Git safety, backend tests,
 frontend build, and live backend/frontend endpoints when the services are
 running. With live validation enabled it also runs the lightweight acceptance
-smoke above.
+smoke above. By default it also runs the deep training acceptance; set
+`SEG_VALIDATE_DEEP=0` when a quick non-training validation pass is needed.