fix: force CPU-only torch to avoid libcufft import error

Author: ShengkaiXu

Dockerfile

@@ -1,6 +1,6 @@
 FROM ghcr.io/lambda-feedback/evaluation-function-base/python:3.12 AS builder
 
-RUN pip install poetry==1.8.3
+RUN python -m pip install --no-cache-dir poetry==1.8.3
 
 ENV POETRY_NO_INTERACTION=1 \
     POETRY_VIRTUALENVS_IN_PROJECT=1 \
@@ -9,9 +9,14 @@ ENV POETRY_NO_INTERACTION=1 \
 
 COPY pyproject.toml poetry.lock ./
 
+# Install deps (torch/torchvision will be resolved from pytorch-cpu source via pyproject.toml)
 RUN --mount=type=cache,target=$POETRY_CACHE_DIR \
     poetry install --without dev --no-root
 
+# Sanity check: ensure torch is CPU-only (cuda should be None)
+RUN python -c "import torch; print('torch', torch.__version__); print('torch.cuda', torch.version.cuda); print('cuda available', torch.cuda.is_available())"
+
+
 FROM ghcr.io/lambda-feedback/evaluation-function-base/python:3.12
 
 ENV VIRTUAL_ENV=/app/.venv \
@@ -31,5 +36,6 @@ ENV FUNCTION_COMMAND="python"
 # Args to start the evaluation function with
 ENV FUNCTION_ARGS="-m,evaluation_function.main"
 
+# Interface / logging
 ENV FUNCTION_INTERFACE="file"
-ENV LOG_LEVEL="debug"
+ENV LOG_LEVEL="debug"

evaluation_function/yolo_pipeline.py

@@ -18,8 +18,7 @@
 
 import cv2
 import numpy as np
-#from ultralytics import YOLO
-YOLO = None
+from ultralytics import YOLO
 
 
 # =========================