# Latest Wheel Packages ## CPU server ### Python 3 ``` # Compile by gcc8.2 https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.0.0-py3-none-any.whl ``` ## GPU server ### Python 3 ``` #cuda10.1 Cudnn 7 with TensorRT 6, Compile by gcc8.2 https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post101-py3-none-any.whl #cuda10.2 Cudnn 7 with TensorRT 6, Compile by gcc5.4 https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post102-py3-none-any.whl #cuda10.2 Cudnn 8 with TensorRT 7, Compile by gcc8.2 https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post1028-py3-none-any.whl #cuda11.2 Cudnn 8 with TensorRT 8 (beta), Compile by gcc8.2 https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post112-py3-none-any.whl ``` ## Client ### Python 3.6 ``` https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp36-none-any.whl ``` ### Python 3.8 ``` https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp38-none-any.whl ``` ### Python 3.7 ``` https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp37-none-any.whl ``` ## App ### Python 3 ``` https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_app-0.0.0-py3-none-any.whl ``` ## Baidu Kunlun user for kunlun user who uses arm-xpu or x86-xpu can download the wheel packages as follows. Users should use the xpu-beta docker [DOCKER IMAGES](./Docker_Images_CN.md) **We only support Python 3.6 for Kunlun Users.** ### Wheel Package Links for arm kunlun user ``` https://paddle-serving.bj.bcebos.com/whl/xpu/0.7.0/paddle_serving_server_xpu-0.7.0.post2-cp36-cp36m-linux_aarch64.whl https://paddle-serving.bj.bcebos.com/whl/xpu/0.7.0/paddle_serving_client-0.7.0-cp36-cp36m-linux_aarch64.whl https://paddle-serving.bj.bcebos.com/whl/xpu/0.7.0/paddle_serving_app-0.7.0-cp36-cp36m-linux_aarch64.whl ``` for x86 kunlun user ``` https://paddle-serving.bj.bcebos.com/whl/xpu/0.7.0/paddle_serving_server_xpu-0.7.0.post2-cp36-cp36m-linux_x86_64.whl https://paddle-serving.bj.bcebos.com/whl/xpu/0.7.0/paddle_serving_client-0.7.0-cp36-cp36m-linux_x86_64.whl https://paddle-serving.bj.bcebos.com/whl/xpu/0.7.0/paddle_serving_app-0.7.0-cp36-cp36m-linux_x86_64.whl ``` ### Binary Package for most users, we do not need to read this section. But if you deploy your Paddle Serving on a machine without network, you will encounter a problem that the binary executable tar file cannot be downloaded. Therefore, here we give you all the download links for various environment. #### Bin links ``` # CPU AVX MKL https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-avx-mkl-0.0.0.tar.gz # CPU AVX OPENBLAS https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-avx-openblas-0.0.0.tar.gz # CPU NOAVX OPENBLAS https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-noavx-openblas-0.0.0.tar.gz # Cuda 10.1 https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-101-0.0.0.tar.gz # Cuda 10.2 + Cudnn 7 https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-102-0.0.0.tar.gz # Cuda 10.2 + Cudnn 8 https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-1028-0.0.0.tar.gz # Cuda 11.2 https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-cuda112-0.0.0.tar.gz ``` #### How to setup SERVING_BIN offline? - download the serving server whl package and bin package, and make sure they are for the same environment - download the serving client whl and serving app whl, pay attention to the Python version. - `pip install ` the serving and `tar xf ` the binary package, then `export SERVING_BIN=$PWD/serving-gpu-cuda11-0.0.0/serving` (take Cuda 11 as the example)