bazel

Some time ago, made a compilation of the example of CC, finally finally fix ... But to compile in the IDE is not successful, continue to explore.Now share, explore the process, welcome nagging, Exchange.http://home.cnblogs.com/u/mydebug/Prepare: inception_dec_2015 files to the Data folderConcrete Look Https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples/label_image1, first need to install Bazel in TensorFlow (pre-download good)$ ch

Official document, please refer to the official documentation. Environment TensorFlow serving currently relies on Google's Open-source compilation tool Bazel. Bazel is an open source version of Google's internal compiler tool, which is basically consistent in functionality and performance blaze. Specific installation can refer to the official documentation. You will also need to install GRPC (Google has an

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 (onli

Reference: http://blog.sina.com.cn/s/blog_672f698e0102wavp.html1. First install the NVIDIA graphics driver:Add-on driver, software update, system settings, select Nvidia latest drivers (361), application changes? 2. Download CUDA8.0 address https://developer.nvidia.com/cuda-release-candidate-download (login required)3. Installing Cudasudo dpkg-i cuda-repo-ubuntu1604-8-0-rc_8.0.27-1_amd64? Debsudo apt-get updatesudo apt-get install Cuda?4. Download the CUDNN, preferably the V4 version address HTT

, I changed a line of code it can build something new. This is the way we are going to compare the Earth.Google recently open source Bazel, which is written in Java compiler tool, it is actually a build command, followed by two backslashes representing the root of the entire Workspace, and then coding is a project,server is Project Targ Et. With this thing you actually build any project you think about it is logically layered rather than physically la

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 0.4.0 version)Made some changes.Apiversion:extensions/v1beta1kind:deploymentmetadata: name:inception-deploymentspec: replicas:2 Temp

The current skaffold version is v0.4 and has not yet been released, and is not recommended for use in production environments;Skaffold is used for developer rapid deployment programs to Kubernetes,Skaffold provides dev, run two modes , and Skaffold requires a skaffold configuration file that defines Skaffold workflow ；The Skaffold workflow defines three main stages : Build, Push, Deploy;First, BuildDuring the build phase, Skaffold uses the dockerfile to generate Artifacts,skaffold docker images,

Reference website:[1] tensorflow official website Tutorials [2] Geek College 's translation of TensorFlow's official website tutorial[3] How to install TensorFlow under Csdn-ubuntuhttp://blog.csdn.net/zhaoyu106/article/details/52793183 [CSDN]Https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md#pip-installationHttps://www.tensorflow.org/versions/r0.11/get_started/os_setup#test_the_tensorflow_installation (official website tutorial)http://blog.csdn.n

TensorFlow Official Tutorial: The last layer of the retraining model to cope with the new classification This article mainly includes the following content: TensorFlow Official Tutorial re-training the final layer of the model to cope with the new classification flowers the inception model for the dataset re-training inception model for flowers data sets    First, before you start training, you need to prepare the dataset and download the dataset as follows. CD ~ Curl-o http://download.tensorfl

, after getting the correct label, the model is fully trained.4, the use of training modeThe script outputs a version of Inception V3 with the last layer of retrained to your directory/TMP/OUTPUT_GRAPH.PB, and contains the label/tmp/output_labels.txt text file. Both are in a format C + + and Python image classification Examples:https://www.tensorflow.org/versions/master/tutorials/image_ Recognition/index.html are able to read, so you can start using your new mode immediately. Now that you have r

for static code analysis. Official Website PMD: Bad programming habits for source code analysis. Official Website SonarQube: integrates other analysis components through the plug-in to collect statistics on data from the past period of time. Official Website Compiler Generation Tool Framework used to create a parser, interpreter, or compiler. Anlr: a complex, full-featured top-down parsing framework. Official Website JavaCC: JavaCC is a more specialized lightweight tool that is easy to use

Tensorflow creates variables and searches for variables by name. tensorflow Variables Environment: Ubuntu14.04, tensorflow = 1.4 (bazel source code installation), Anaconda python = 3.6 There are two main methods to declare variables:Tf. VariableAndTf. get_variable, The biggest difference between the two is: (1) tf. Variable is a class with many attribute functions, while tf. get_variable is a function;(2) tf. Variable can only generate unique variable

Installation of TensorFlow SyntaxnetBefore installing, make sure that Ubuntu, Python, TensorFlow, and some of the appropriate packages are installed successfully.1. Installing Syntaxnet# (1) Pip$ sudo apt-get install python-virtualenv# (2) PIP3$ sudo apt-get install python3-virtualenv2. Create the TensorFlow environment in Virtualenv$ virtualenv--system-sit-packages ~/tensorflow3. Activating the TensorFlow virtualenv environment$ source ~/tensorflow/bin/activate# (1) Pip(tensorflow) $ pip Instal

$ cd ~/tensorflow $ git clone https://github.com/ncnynl/ Installtensorflowtx2.git $ cd installTensorFlowTX2 //Installation dependencies: //Installation Java,protobuf,grpc-java, Bazel etc $ chmod +x installprerequisites.sh $./installprerequisites.sh //Download TensorFlow code: $./clonetensorflow.sh //SET environment variable: $./settensorflowev.sh //Compile TensorFlow: $./buildtensorflow.sh $./ packagetensorflow.sh //Installation WHL file: $ pip

Tags: var wap ext color started common red EPS virtual machineSTEPS:0. Install Homebrew1. Install ' Docker for Mac 18.03+ ', configure CPUs (n Cpus,bazel open n thread compilation), memory (>2g, compile min memory, 4G recommended), Swap (>2g, recommended 2G )2 . Git clone ... Apollo ...3. Enter the Apollo catalogue, pull Docker image for Apollo (first run will pull 5G images)./docker/scripts/dev_start.sh* Note that the dev_start.sh here need to be mod

I. Installation of CUDASpecific installation process See my other blog, ubuntu16.04 installation configuration deep learning environmentSecond, installation TensorFlow1. Specific installation process In fact, the official website is written in more detail, summed up the words can be divided into two types: Install release version and source code compiled installation. Because the source code compiled installation is cumbersome, and need to install Google's own compiler

programming habits for source code analysis. Website SonarQube: Integrate other analytics components with plug-ins to count data over time in the past. Website Compiler Build ToolThe framework used to create the parser, interpreter, or compiler. ANTLR: Complex full-featured top-down parsing framework. Website JAVACC:JAVACC is a more specialized lightweight tool that is easy to get started and supports predictive grammar. Website Build toolsBuild and apply dependency p

interesting facts: Dropbox recently completed the upgrade from Go 1.5 to 1.6 in its production service; To track the upgrade process, the staff created a simple Dropbox paper document and asked for each service. The holder reports progress and, if necessary, applies for help. Dropbox decided to skip go 1.7 and upgrade directly to version 1.8 after the 1.6 migration was completed, including non-production services. Dropbox How does the company guide new engineers to use Go

; Stores the running results of Session sessions std::vector When the C + + program is written, the compile time need to link the header file, open source has helped us tidy up, stored in the directory/usr/lib/python2.7/site-packages/tensorflow/include. When compiling and running, you need to link libtensorflow_cc.so, you can compile the library file as follows: Bazel build-c opt//tensorflow:libtensorflow_cc.so--copt=-m64- linkopt=-m64--spawn_s