TFServing源代码编译&安装

开发环境准备

CPU Base Docker Image

GCC Version

Python Version

IMAGE

7.5.0

3.6.9

alideeprec/deeprec-base:deeprec-base-cpu-py36-ubuntu18.04

9.4.0

3.8.10

alideeprec/deeprec-base:deeprec-base-cpu-py38-ubuntu20.04

11.2.0

3.8.6

alideeprec/deeprec-base:deeprec-base-cpu-py38-ubuntu22.04

GPU Base Docker Image

GCC Version

Python Version

CUDA VERSION

IMAGE

7.5.0

3.6.9

CUDA 11.6.1

alideeprec/deeprec-base:deeprec-base-gpu-py36-cu116-ubuntu18.04

9.4.0

3.8.10

CUDA 11.6.2

alideeprec/deeprec-base:deeprec-base-gpu-py38-cu116-ubuntu20.04

11.2.0

3.8.6

CUDA 11.7.1

alideeprec/deeprec-base:deeprec-base-gpu-py38-cu117-ubuntu22.04

CPU Dev Docker (with bazel cache)

GCC Version

Python Version

IMAGE

7.5.0

3.6.9

alideeprec/deeprec-build:deeprec-dev-cpu-py36-ubuntu18.04

9.4.0

3.8.10

alideeprec/deeprec-build:deeprec-dev-cpu-py38-ubuntu20.04

GPU(cuda11.6) Dev Docker (with bazel cache)

GCC Version

Python Version

CUDA VERSION

IMAGE

7.5.0

3.6.9

CUDA 11.6.1

alideeprec/deeprec-build:deeprec-dev-gpu-py36-cu116-ubuntu18.04

9.4.0

3.8.10

CUDA 11.6.2

alideeprec/deeprec-build:deeprec-dev-gpu-py38-cu116-ubuntu20.04

TFServing代码库及分支

我们提供了针对DeepRec版本的TFServing,该版本指向DeepRec Repo.

代码库:https://github.com/DeepRec-AI/serving

开发分支:master,最新Release分支:deeprec2402

TFServing编译&打包

代码编译-CPU版本

bazel build -c opt tensorflow_serving/...

编译开启OneDNN + Eigen Threadpool工作线程池版本(CPU)

bazel build -c opt --config=mkl_threadpool --define build_with_mkl_dnn_v1_only=true tensorflow_serving/...

代码编译-GPU版本

bazel build -c opt --config=cuda tensorflow_serving/...

生成Client Wheel包

bazel-bin/tensorflow_serving/tools/pip_package/build_pip_package /tmp/tf_serving_client_whl

Server Bin

Server Bin生成在下面路径中:

bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server