tensorflow ide

Learning notes TF024: TensorFlow achieves Softmax Regression (Regression) Recognition of handwritten numbers, tf024softmax TensorFlow implements Softmax Regression (Regression) to recognize handwritten numbers. MNIST (Mixed National Institute of Standards and Technology database), simple machine vision dataset, 28x28 pixels handwritten number, only grayscale value information, blank part is 0, handwriting a

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

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

This is my first blog, in reference to other people's blog to install the process, for my platform system, encountered a lot of problems, here to write my practice and the problems encountered.For the reference to the blogger's article, here to express thanks.For this blog, if there is bad writing or wrong place, because my level is limited, as well as the limitations of the problems encountered, can not be taken into account, please give understanding, and hope to get good suggestions, for good

Win10 + python3.6 + VSCode + tensorflow-gpu + keras + cuda8 + cuDN6N environment configuration, win10cudn6n Preface: Before getting started, I knew almost nothing about python or tensorflow, so I took a lot of detours When configuring this environment, it took a whole week to complete the environment... However, the most annoying thing is that it is difficult to set up the environment. Because my laptop is

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 abnormal, find a half day reason ...This step on the Internet is still a lot of information, Dock

Learning notes TF024: TensorFlow achieves Softmax Regression (Regression) Recognition of handwritten numbersTensorFlow implements Softmax Regression (Regression) to recognize handwritten numbers. MNIST (Mixed National Institute of Standards and Technology database), simple machine vision dataset, 28x28 pixels handwritten number, only grayscale value information, blank part is 0, handwriting according to the color depth of [0, 1], 784 dimension. Two-di

Basic TensorFlow usage example This article is based on Python3 TensorFlow 1.4. This section describes the basic usage of TensorFlow by using the simplest example, plane fitting. The introduction method of constructing TensorFlow is as follows: Import tensorflow as tf Next,

Originating From: https://blog.csdn.net/jerr__y/article/details/61195257 Welcome reprint, but please be sure to indicate the source and author information. @author: Huangyongye@creat_date: 2017-03-09 According to my own learning TensorFlow realize LSTM experience, found that although there are many tutorials on the internet, many of them are based on the official examples, using multilayer LSTM to achieve Ptbmodel language model, such as:TensorFlow no

In the previous TensorFlow Exercise 1 I mentioned a high-level library using TensorFlow as the backend, called Keras, which is a high-level neural network Python library. In TensorFlow Exercise 1, I was manually defining a neural network, with a few lines of code to take care of it. The first Keras use Theano as the back end,

TensorFlow provides two levels of API, and the underlying TensorFlow core provides complete control for researchers. Higher-level use is simpler, such as Tf.contrib.learn, but contrib is still in the update TensorFlow operation of the core layer The data units in the TensorFlow are represented by tensor, and the tensor

Try installing a set of TensorFlow under Windows, due to the need for work. Just before the machine has been installed anaconda, can be directly through the Anaconda Navigator. Launch Anaconda Navigator, go to Environment Settings page (environments) 2. Click the Create button under the root environment to create a new environment named TensorFlow (because the window version of

TensorFlow is an open source software library for machine learning for a variety of perceptual and language understanding tasks. It is currently used by 50 teams to research and produce many Google business products, such as voice recognition, Gmail, Google albums and search, many of which have used their predecessor software Distbelief. Originally developed by the Google Brain team for Google Research and production,

There is INCEPTION-V3 model Python implementation on GitHub at:https://github.com/tensorflow/models/tree/master/inceptionThere is several shell scripts In/inception/inception/data folder. These scripts only can run on the Linux OS, especially on Ubuntu. So. How can we set up the INCEPTION-V3 model on Windows. Let's dive into these scripts code.In download_and_preprocess_flowers.sh.First, the script download flower_photo.tgz file from the Web. Second,