src/paddle_ocr/Dockerfile.build-paddle

@@ -92,8 +92,16 @@ RUN mkdir -p build
 WORKDIR /build/Paddle/build
 
 # Configure CMake for ARM64 + CUDA build
-# Note: Adjust CUDA_ARCH_NAME based on your GPU architecture
-# Common values: Auto, Ampere, Ada, Hopper
+#
+# CUDA_ARCH is auto-detected from host GPU and passed via docker-compose.
+# To detect: nvidia-smi --query-gpu=compute_cap --format=csv,noheader
+# Example: 12.1 -> use "90" (Hopper, closest supported), 9.0 -> use "90"
+#
+# Build time: ~30-60 min with single arch vs 2-4 hours with all archs
+
+ARG CUDA_ARCH=90
+RUN echo "Building for CUDA architecture: sm_${CUDA_ARCH}"
+
 RUN cmake .. \
     -GNinja \
     -DCMAKE_BUILD_TYPE=Release \
@@ -107,7 +115,9 @@ RUN cmake .. \
     -DON_INFER=OFF \
     -DWITH_PYTHON=ON \
     -DWITH_AVX=OFF \
-    -DCUDA_ARCH_NAME=Auto \
+    -DCUDA_ARCH_NAME=Manual \
+    -DCUDA_ARCH_BIN="${CUDA_ARCH}" \
+    -DCMAKE_CUDA_ARCHITECTURES="${CUDA_ARCH}" \
     -DCMAKE_EXPORT_COMPILE_COMMANDS=ON
 
 # Build PaddlePaddle (this takes 2-4 hours)

src/paddle_ocr/docker-compose.yml

@@ -3,16 +3,22 @@
 #   CPU:   docker compose up ocr-cpu
 #   GPU:   docker compose up ocr-gpu
 #   Test:  docker compose run --rm test
-#   Build: docker compose run --rm build-paddle  (ARM64 GPU wheel, one-time)
+#   Build: CUDA_ARCH=90 docker compose --profile build run --rm build-paddle
+#
+# Auto-detect CUDA arch before building:
+#   export CUDA_ARCH=$(nvidia-smi --query-gpu=compute_cap --format=csv,noheader | head -1 | tr -d '.')
+#   docker compose --profile build run --rm build-paddle
 
 services:
   # PaddlePaddle GPU wheel builder (ARM64 only, one-time build)
   # Creates ./wheels/paddlepaddle_gpu-*.whl for ARM64 GPU support
-  # Run once: docker compose run --rm build-paddle
+  # CUDA_ARCH env var controls target GPU architecture (default: 90 for Hopper)
   build-paddle:
     build:
       context: .
       dockerfile: Dockerfile.build-paddle
+      args:
+        CUDA_ARCH: ${CUDA_ARCH:-90}
     volumes:
       - ./wheels:/wheels
     profiles: