update

backend/Dockerfile

@@ -82,16 +82,18 @@ ARG PYTORCH_MODELS_MIRROR=
 ARG PYTORCH_MODELS_URL=
 ENV PYTORCH_MODELS_MIRROR=${PYTORCH_MODELS_MIRROR} \
     PYTORCH_MODELS_URL=${PYTORCH_MODELS_URL}
+# Optional offline weight (only .gitkeep by default; add swin3d_t-7615ae03.pth before build if needed).
+COPY weights ./weights/
 
 RUN --mount=type=cache,target=/root/.cache/uv \
-    --mount=type=bind,source=weights/swin3d_t-7615ae03.pth,target=/tmp/prebaked/swin3d_t-7615ae03.pth,readonly,required=false \
     uv sync --frozen --no-dev --no-compile --refresh-package numpy --refresh-package mediapipe && \
     .venv/bin/python -c "import alembic" && \
     .venv/bin/python -c "import numpy; import numpy.lib._index_tricks_impl" && \
     .venv/bin/python -c "import mediapipe as mp; print('mediapipe', mp.__version__)" && \
     mkdir -p /app/.cache/ultralytics && \
-    PYTORCH_MODELS_LOCAL_PATH=/tmp/prebaked/swin3d_t-7615ae03.pth \
+    PYTORCH_MODELS_LOCAL_PATH=/app/weights/swin3d_t-7615ae03.pth \
       .venv/bin/python scripts/bake_torch_hub_checkpoint.py && \
+    rm -rf /app/weights && \
     TORCH_HOME=/app/.cache/torch .venv/bin/python -c "from torchvision.models.video import Swin3D_T_Weights, swin3d_t; swin3d_t(weights=Swin3D_T_Weights.KINETICS400_V1); print('swin3d_t cached ok')" && \
     chmod -R a+rX /app/.venv /app/algorithm_subprocesses /app/.cache/torch /app/.cache/ultralytics
 

backend/algorithm_subprocesses/5.15/code/video_clip_cls/scripts/run_haocai_actionformer_consumables_e2e.py

@@ -296,6 +296,12 @@ def run_actionformer_eval(
     src_pkl = ckpt_path.parent / "eval_results.pkl"
     if not src_pkl.is_file():
         raise FileNotFoundError(f"未找到输出: {src_pkl}")
+    try:
+        if src_pkl.samefile(copy_pkl_to):
+            log(f"eval_results.pkl 已在目标路径: {copy_pkl_to}")
+            return
+    except OSError:
+        pass
     shutil.copy2(src_pkl, copy_pkl_to)
     log(f"已复制 eval_results.pkl -> {copy_pkl_to}")
 

backend/algorithm_subprocesses/5.15/src/actionformer_utils.py

@@ -70,10 +70,12 @@ class ActionSegmenter:
         e2e.write_infer_yaml(yaml_path, json_path.resolve(), feat_dir.resolve())
 
         pkl_dest = work / "eval_results.pkl"
+        # Do not resolve(): staged ckpt may symlink into bundle weights; eval.py
+        # writes eval_results.pkl beside ckpt and needs a writable parent dir.
         e2e.run_actionformer_eval(
             python_exe=python_exe,
             yaml_path=yaml_path.resolve(),
-            ckpt_path=actionformer_ckpt.resolve(),
+            ckpt_path=actionformer_ckpt,
             copy_pkl_to=pkl_dest,
         )
 

backend/tests/test_algo_host_batch.py

@@ -104,6 +104,25 @@ def test_stage_actionformer_checkpoint_survives_bundle_config_resolve(tmp_path:
     assert loaded.name == source.name
 
 
+def test_staged_actionformer_ckpt_must_not_resolve_before_eval(tmp_path: Path) -> None:
+    """eval.py writes eval_results.pkl next to ckpt; resolve() breaks staged symlinks."""
+    bundle = tmp_path / "bundle"
+    write_minimal_reference_bundle(bundle)
+    work_dir = tmp_path / "work"
+    work_dir.mkdir()
+    source = bundle / "weights" / "actionformer_epoch_045.pth.tar"
+    staged = stage_actionformer_checkpoint(bundle_dir=bundle, work_dir=work_dir)
+    assert staged.is_symlink() or staged.parent == work_dir
+
+    def eval_pkl_parent(ckpt: Path) -> Path:
+        return ckpt.parent  # mirrors eval.py: dirname(ckpt) / eval_results.pkl
+
+    assert eval_pkl_parent(staged.resolve()) == source.parent
+    assert eval_pkl_parent(staged) == work_dir
+    # actionformer_utils uses the same path for copy_pkl_to; run_actionformer_eval must skip copy2.
+    assert eval_pkl_parent(staged) / "eval_results.pkl" == work_dir / "eval_results.pkl"
+
+
 def test_build_reference_env_sets_container_safe_defaults(monkeypatch: pytest.MonkeyPatch) -> None:
     monkeypatch.delenv("TORCHINDUCTOR_CACHE_DIR", raising=False)
     monkeypatch.delenv("USER", raising=False)