tensorflow classification

The first is tensorflow to clone to a local copy.git clone--recurse-submodules https://github.com/tensorflow/tensorflow.gitSince it is Google's official request, it is best to --recurse-submodules Add, the document said can avoid some data structure serialization when the problem of compilation.This is the GitHub homepage for Android demo.Preparing for compilation 1. Install BazelbazelIs Google's own build

Broadcast operation (broadcasting operation) An operation that uses Numpy-style broadcasting to ensure the morphological compatibility of tensor parameters. Devices A piece of hardware that can be used to compute and have its own address space, such as the GPU and CPU. Eval Tensor a method that returns the value of Tensor. This value is calculated to trigger any graph calculation. Can only be in a session that has been startedTo invoke the Tensor value in the diagram. Feed A concept of

Get ready: The l4t 27.1 an Ubuntu 16.04 64-bit variant (aarch64) CUDA 8.0 cudnn-5.1.10 TensorFlow installation requires CUDA and CUDNN installed versions: TensorFlow v1.0. 1 Increase the size of the swap swap area: Create Script $ mkdir ~/swap/ $ cd ~/swap/ $ vim createswapfile.sh //script content as follows #!/bin/bash #NVIDIA Jetson TX1 in 3D card #Create a swapfile to Ubuntu at the current directory lo

Welcome reprint, but please be sure to indicate the source and author information. TensorFlow Introduction (i) Basic usage Refer to:http://wiki.jikexueyuan.com/project/tensorflow-zh/get_started/basic_usage.html@author: Huangyongye@date: 2017-02-25 This example is mainly based on TensorFlow's Chinese documentation to learn the basic usage of tensorflow. According

about TensorFlow The TensorFlow is an open source software library that uses a data flow graph (graphs) for numerical calculations. A node (Nodes) represents a mathematical operation in a diagram, and a line (edges) in the graph represents a multidimensional array of data that is interconnected between nodes, that is, tensor (tensor). Its flexible architecture allows you to expand calculations on multiple

The release of TensorFlow itself is based on Ubuntu, so it's more convenient under Ubuntu than under Windows. There are three kinds of installation methods, see TensorFlow the second chapter of the construction of the environment. This article describes using PIP to install CPU-based TensorFlow.1, download install pip:$ sudo apt-get install Python-pip Python-dev2

Download and install AnacondaDownload the anaconda first, which can be downloaded from the image website of Tsinghua University .Install Anaconda, and be careful not to remove the option to add environment variables during installation.After the installation is complete, in the installation directory cmd, enterConda ListYou can see the integration environment that Anaconda provides for us:Here's just a part:To view version information:Conda--versionAnaconda installation was successful.Next need

In the previous article, "TensorFlow load pre-training model and save Model", we learned how to use the pre-training model. Note, however, that in the previous article, you must have at least 4 files to use the pre-training model: Checkpoint Mymodel.meta mymodel.data-00000-of-00001 mymodel.index This is very inconvenient for us to use. Is there a way to export a PB file and then use it directly. The answer is yes. In the article "

First to install the Anaconda.Note that to add an environment variable to the system, there is an option for this. Or you'll need to manually CD to Anaconda3\bin to execute the instructions below. Due to the installation of TensorFlow, use Pip Install TensorFlow The instructions always go wrong, even with the official website. Pip Install--upgrade HTTPS://STORAGE.GOOGLEAPIS.COM/

November 29, 2016, TF officially announced that version 0.12 TensorFlow supports native Windows operating systems and is not installed through Docker. TF beginners, Windows heavy dependent users, can follow the following feasible installation method. First, install Python 1. Install Python on Windows via pip TensorFlow only supports 64-bit Python3.5on Windows, either via Python 3.5 from python.org or Pyth

On the internet to find a lot of cases, stepped on a lot of pits, feel more comprehensive is the following introductionHttp://www.cnblogs.com/xuliangxing/p/7575586.htmlLet's talk about my steps:First installed the Anacoda, because it is a scientific computing environment, so first installed the latest version, so the corresponding Python 3.6Install graphics driver: gtx950m installed the latest 390 drivers, worried about incompatibility, so all with the latestInstalling Cuda, this pit was finally