tensorflow serving docker

TensorFlow Serving,gpu TensorFlow serving is an open source tool that is designed to deploy a trained model for inference.TensorFlow serving GitHub AddressThis paper mainly introduces the installation of TensorFlow

1.Build Docker ImageBecause you always have problems with your build image, here is a temporary lease on a mirror on Dockerhub docker.io/mochin/tensorflow-servingPush this image to the Docker registry of the K8s cluster2. Writing YamlIn the official example, a yaml is given, but some places are wrong, or the dockerimage is not applicable (probably because of the

First, prefaceAs deep learning continues to evolve in areas such as image, language, and ad-click Estimation, many teams are exploring the practice and application of deep learning techniques at the business level. And in the Advertisement Ctr forecast aspect, the new model also emerges endlessly: Wide and deep[1], Deepcross network[2], deepfm[3], Xdeepfm[4], the American Regiment many deep study blog also did the detailed introduction. However, when the offline model needs to be online, it will

This article reproduced from: https://zhuanlan.zhihu.com/p/23361413, the original title: TensorFlow Serving Taste Fresh In the 2016, machine learning became more popular in the post-war era of Alpha go and Li Shishi. Google also launched the TensorFlow serving this year and added a fire.TensorFlow

TensorFlow serving provides a way to deploy TensorFlow- generated models to online services, including model export,load, and so on. Installation Reference thisHttps://github.com/tensorflow/serving/blob/master/tensorflow_serving/g3doc/setup.md??but because of the problem of

Recently in learning TensorFlow serving, but run the official website example, do not use Bazel, when found to run mnist_client.py error,PREDICT_PB2 was not found in the API file, so, after seeing it on the internet, it's here"Bazel-bin/tensorflow_serving/example/mnist_client.runfiles/tf_serving/tensorflow_serving/apis"As if this is Bazel compiled generated (online view, provenance can not find), well, back

TensorFlow is a deep learning package developed by Google and is currently only supported on Linux and OSX. But this fall may have a Windows-enabled version of it, so for developers who use Windows, there's no need to wait for the fall or go to Linux and OSX TensorFlow. There are two ways to run on Windows, one is to install the virtual machine and install the Ubuntu system, install

"Google" + "deep learning", two tags let the December 2015 Google open-source deep learning tool TensorFlow after its release quickly became the world's hottest open source project, April 2016, open source TensorFlow support distributed features, The application to the production environment is further.The TensorFlow API supports Python 2.7 and Python 3.3+, with

). Open Synaptic, Input: nvidia, select nvidia-352 (according to the graphics card model selection), and then point Apply,synaptic Package Manager will be installed in nvidia-352, all installed together, after installation, you will find that in fact, many things installed. So this installation drive way, more than one of their own installation of those bags, insurance a lot. After installation, reboot. Click on the upper right corner of the computer, found that the graphics inside the show has

Installing DockerBefore only the Docker file, not how to contact the installation of Docker environment, this time also try it, first download DockerToolbox.exeAfter the installation is complete, the startup script start.sh, will default to check the version, if it is installed at the same time VirtualBox, it is recommended to restart, this card for a long time, has been reported to start vboxmanage abnorma

? Install Docker https://docs.docker.com/install/linux/docker-ce/ubuntu/ latest Or48492937 Learning EditionTest with Docker-vTest with sudo Docker run Hello-world TensorFlow Environment building based on Docker