tensorflow debugger tutorial

XendDebugger.dll, unzip the dummy.php in the package to the Web root directory, I here Apache DocumentRoot set in D:/myserver/wwwroot, copy dummy.php to D: Myserverwwwroot, and then modify the php.ini, adding these content: Zend_extension_ts=d:/myserver/zenddebugger/5_2_x/zenddebugger.dllZend_debugger.allow_hosts=127.0.0.1/32,192.168.1.88/24Zend_debugger.expose_remotely=always Then restart Apache, after a little wait, we enter phpinfo () to see success or not? Aha, it's a good run. Below open

such.tensorflow1.6 or 1.7 with CUDA9.1 is not good, should use 9.0, I was the pit. But fortunately there is a solution, thank you for this article:79433298So I wrote a detailed tutorial on using CUDA9.1 's TensorFlow:79871564Update: TensorFlow package is relatively large, installed more slowly than the ordinary small package, please ensure that the program is ru

Ai This concept seems to suddenly fire up, the beginning of the big score to win Li Shishi Alphago success attracted a lot of attention, but in fact, look at your phone's voice assistant, face recognition on the camera, today's headlines to help you automatically filter out the news, as well as the major music software song "Daily Recommended" ... All kinds of AI have already entered all aspects of our lives. Profoundly affected us, it can be said, this is an AI era.In fact, at the end of last y

How to solve the compatibility problem between Optimizer and Debugger. ZendExtensionManager. dll -- Zend extension plug-in manager simplest installation tutorial: 1. install ZendOptimizer3.3.0a: www.jb51.netsofts9305.html so that ZendExtensionManager. dll -- Zend extension plug-in manager Zend extension plug-in manager installation tutorial: 1. install Zend Optim

　　Most complete Pycharm Tutorials (1)--Custom SkinsMost full Pycharm Tutorials (2)-code styleMost full Pycharm Tutorials (3)-code debugging, runningMost complete Pycharm Tutorials (4)--related configuration for Python interpreterMost full Pycharm Tutorials (5)--python shortcut key Related settingsMost full Pycharm Tutorials (6)--using Pycharm as a VIM editorMost full Pycharm Tutorials (7)--Configuration of VM VMsMost complete Pycharm tutorials (8) creation and management of--django engineeringMo

powerful influence can lead to the development of a field, as was the case with previous Android systems and Map reduce technologies.Although TensorFlow's official version of the tutorial has been published, but the full English tutorial narrative inevitably make domestic researchers read a little laborious, and personal understanding of the different will cause the inconvenience of use, translated into Ch

). The course content is basically code-based programming, there will be a small amount of deep learning theoretical content. The course starts with some of the most basic knowledge from TensorFlow's most basic diagrams (graphs), sessions (session), tensor (tensor), variables (Variable), and gradually talks about the basics of TensorFlow, And the use of CNN and LSTM in TensorFlow. After the course, we will

console's script output:13. Stepping Script debuggingLet's further debug the current script. Click Restart Debugging process and the program runs again to the first breakpoint and pauses.At the top of the debug window, you will see a list of toolbar stepping buttons with the Step Debug button.Click, or press F8, and you'll notice that the blue tag moves to the next line:At the same time, when you pause the execution of the script (click the button), you can see the highlighted function Print_ti

console's script output:13. Stepping Script debuggingLet's further debug the current script. Click Restart Debugging process and the program runs again to the first breakpoint and pauses.At the top of the debug window, you will see a list of toolbar stepping buttons with the Step Debug button.Click, or press F8, and you'll notice that the blue tag moves to the next line:At the same time, when you pause the execution of the script (click the button), you can see the highlighted function Print_ti

({x:mnist.test.images, y_: Mnist.test.labels}))The results are as follows:[[email protected] $] python digital_recognition.pyextracting. /train-images-idx3-ubyte.gzextracting. /train-labels-idx1-ubyte.gzextracting. /t10k-images-idx3-ubyte.gzextracting. /t10k-labels-idx1-ubyte.gz0.9039ExplainFlags. Define_string ('data_dir'mnist_data/ ' Directory for storing data')Indicates that we use Mnist_data's top level directory as a storage directory for training data, and if we do not have good training

environment variable configuration is not directly accessible to the bin and lib\x64 under the package, in the path to add these two paths.Once installed, there will not be more than four environmental variables, and two need to add them themselves. C:\Program Files\nvidia GPU Computing toolkit\cuda\v8.0C:\Program Files\nvidia GPU Computing toolkit\cuda\v8.0\binC:\Program Files\nvidia GPU Computing toolkit\cuda\v8.0\lib\x64C:\Program Files\nvidia GPU Computing TOOLKIT\CUDA\V8.0\LIBNVVP

variable, environment variable, left advanced system settings, properties---Edit text with path editPaste the directory of the Python folder up to the end and add a ";"That is, paste C:\Users\lobsterwww\AppData\Local\Programs\Python\Python36;Click the directory again to see the newly pasted directory is addedExit system settingsstep3 Installation NumPy if not installed, you cannot install TensorFlow directly under PIP. Go to https://pypi.python.org/p

This section corresponds to Google Open source TensorFlow object Detection API Object recognition System Quick start Step (i):Quick Start:jupyter notebook for off-the-shelf inferenceThe steps in this section are simple and do the following:1. After installing Jupyter in the first section, enter the Models folder directory at the Ternimal terminal to execute the command:Jupyter-notebook　　2. The Web page opens Jupyter access to the Object_detection fold

Session:with Tf.device ("/gpu:0"): Session.run (init) coord=tf.train.Coordinator () Threads= Tf.train.start_queue_runners (coord=coord) Max_iter=10000ITER=0ifOs.path.exists (Os.path.join ("Model",'model.ckpt')) isTrue:tf.train.Saver (Max_to_keep=none). Restore (Session, Os.path.join ("Model",'model.ckpt')) whileiterMax_iter:#Loss_np,_,label_np,image_np,inf_np=session.run ([Loss,opti,batch_image,batch_label,inf])B_batch_image,b_batch_label =Session.run ([Batch_image,batch_label]) l

Background: The latest version of Tensoflow has supported Python3.6First, download and install the Anaconda3 built-in Python3.6 version https://www.continuum.io/downloads do not modify its recommended options when installingThen download and install Cuda 8.0 https://developer.nvidia.com/cuda-downloadsThen download and install CUDNN 5.1 (the official recommended version, the latest version is not guaranteed to use) Link: Http://pan.baidu.com/s/1jHK0EFW Password: ai9f add cudnn extracted files to

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