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Customizing the Eclipse IDE's interface Chapter

Why would you want to customize the IDE?At work, when the company has its own framework, open to its own personnel, or even can sell, we can make a product, and this product will include the framework itself, documents, tools, tutorials and so on. The most important of these tools is the development tools (IDE) and debugging tools. What I do in the company is a hybrid framework, and a supporting

Netbeans ide 6.0.1 installation instructions

Required Software Before installing the IDE, make sure that Java SE Development Kit (JDK) 5 update 14 (version 1.5.0 _ 14) or later (including JDK 6 Update 4) is installed in the system ). If JDK 5 update 14 or later is not installed, you cannot continue to perform this installation. For more information about the required JDK version, see the required software section in the release notes of netbeans ide 6

Python3 Installation TensorFlow problems encountered

1. Use command:sudo pip3 install--upgrade \ https://storage.googleapis.com/tensorflow/linux/cpu/ TENSORFLOW-1.1.0RC2-CP35-CP35M-LINUX_X86_64.WHL installation.The following issues were encountered:TENSORFLOW-1.1.0RC2-CP35-CP35M-LINUX_X86_64.WHL is a supported wheelon this platform.Try several versions to report the same error and do not support the platform.2. Change the command PIP3 install

Under "TensorFlow" Network Operation Api_

Error valueMeasure the loss error between two tensor or one tensor and 0, which can be used in a regression task or for the purpose of regularization (weight decay).loss tf.nn.l2_loss(t, name=None) Explanation: This function uses the L2 norm to calculate the error value of the tensor, but does not prescribe and takes only half of the value of the L2 norm, as follows: output = sum(t ** 2) / 2 Input parameters: t: One Tensor . The data type must be one of the followi

about using the lab server's GPU and running the TensorFlow code

Environment: virtualenv xxx_pyvirtualenv -p python3 xxx_pyEnter the environment:source xxx_py/bin/activateExit:deactivate Use Tsinghua Mirror Temporary usepip install -i https://pypi.tuna.tsinghua.edu.cn/simple some-package Set as Defaultpip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple Resources:Tsinghua PyPI Mirror Use HelpVIRTUALENV Introduction and basic useOne of the essential artifacts of Python development: virtualenvvirtualenv

TensorFlow Neural Network

TensorFlow let neural networks automatically create musicA few days ago to see an interesting share, the main idea is how to use TensorFlow teach neural network automatically create music. It sounds so fun, there's wood! As a Coldplay, the first idea was to automatically generate a music like the Coldplay genre, so I started to follow the tutorial on GitHub (project name: Projects Magenta) Step by step, get

Pointer-network's TensorFlow implementation-1

Pointer-network is a branch of the recent seq2seq comparison fire, which is widely used in the system of reading comprehension based on deep learning. interested can read the original paper recommended readinghttps://medium.com/@devnag/pointer-networks-in-tensorflow-with-sample-code-14645063f264??This idea is also relatively simple is that the decoded predictions are confined to the input position . it works in a lot of places .For example, consider a

"TensorFlow" Queue & multithreaded &tfrecod file _ my generation when singing

A detailed description of the TF data read queue mechanism TFR file multi-threaded queue read and write operations: Tfrecod File Write operation: Import TensorFlow as Tfdef _int64_feature (value): # value must be an iterator object # non-int data use bytes instead of Int64 to return Tf.train.Feature (Int64_list=tf.train.int64list (Value=[value])) Num_shards = 2instance_perpshard = 2for i in rang

Learning Note TF052: convolutional networks, neural network development, alexnet TensorFlow implementation

. Shaoqing Ren, kaiming He, Ross Girshick, Jian Sun thesis Faster r-cnn:towards real-time Object Detection with region proposal NETW Orks "https://arxiv.org/abs/1506.01497.Add a new function module.FCN (deconvolution), Stnet, CNN and RNN/LSTM hybrid structures.MNIST alexnet implementation. Network structure diagram.1. Study the network paper carefully, understand each layer input, output value, network structure.2. Implement the network by loading data, defining the network model, training the m

Compiling tensorflow from source in Ubuntu

This shows the process of compiling the TensorFlow from the source code.The original tutorial https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md# on GitHub Installing-from-sourcesFirst, install the Build tool Bazel (Http://www.bazel.io/docs/install.html#install-on-ubuntu)Insta

UBUNTU14 Installing TensorFlow and testing

1.ubuntu version of the choice: read a lot of blog, recommended the use of UBUNTU14, stable compatibility good.Installation of 2.tensorflow:Http://wiki.jikexueyuan.com/project/tensorflow-zh/get_started/introduction.htmlHere is a detailed description of how to install, I was the first method of choice, the successful installation completed.Later, try to install TensorFlow and Caffe under Docker.3. Test wheth

ubuntu1604 installation TensorFlow

Operating system: UBUNTU-16.04.2-DESKTOP-AMD64TensorFlow version: 1.0.0Python version: 2.7.12To open SSH:sudo Install openssh-server sudossh startInstall PIP:sudo Install Python-pipInstall TensorFlow:GitHub Address: Https://github.com/tensorflow/tensorflowwget https://CI.TENSORFLOW.ORG/VIEW/NIGHTLY/JOB/NIGHTLY-MATRIX-CPU/TF_BUILD_IS_OPT=OPT,TF _build_is_pip=pip,tf_build_python_version=python2,label=cpu-slave/lastsuccessfulbuild/artifact/pip_test/w

TensorFlow various Error summary

1. The ' list ' object has no attribute ' lower ' has the following error Traceback (most recent): File "h:/fasionai/mynet/train.py", line Problem reason: Tf.nn.max_pool () instead of Tf.nn.pool () 2.tensorflow Version inconsistency 1) attributeerror:module ' TensorFlow ' has no attribute ' scalar_summary ' Tf.image_summary (' images ', images) instead: tf.summary.image (' images ', images) 2 attribut

How does "TensorFlow" tf.nn.conv2d_transpose achieve deconvolution?

Three months has not updated Ah, come back a more ~ ~ CSDN mainly on some coding process encountered in the functions, problems, solutions. Partial practice In addition, if you want to see some of the theoretical aspects, welcome to add me to know the homepage Csdn DMS Almost do not look, there are problems Exchange can send a mailbox: hzmaoxiaofeng@163.com or know DMS, see I will be the first time to reply to you In the previous article, someone and I asked the question of the location of the p

LeNet-5 model and its TensorFlow code implementation

This paper first analyzes the structure of the LENET-5 model, and then based on the LENET-5 model to write the TensorFlow code to achieve mnist digital recognition, the code part of the detailed annotation, at present also in the learning phase, there are errors welcome to point out that we learn together. The LENET-5 model structure diagram is as follows: The LENET-5 model has a total of 7 layers. First layer: convolution layer The first layer of th

TensorFlow limit the number of CPUs

installation This uses the Pip to install the TensorFlow CPU version $ sudo pip install HTTPS://STORAGE.GOOGLEAPIS.COM/TENSORFLOW/LINUX/CPU/TENSORFLOW-0.5.0-CP27-NONE-LINUX_X86_64.WHL Check the success of the installation with handwriting recognition examples from the runtime when the installation is complete $ cd/usr/lib/python2.7/site-packages/

TensorFlow Combat Series 13--lenet-5 Model

The LENET-5 model, presented by Professor Yann LeCun in his paper gradient-basedlearning applied to document recognition in 1998, was the first volume to be successfully applied to digital recognition issues. Accumulated neural network. On the Mnist dataset, the LENET-5 model can achieve a correct rate of approximately 99.2%. The LENET-5 model has a total of 7 layers, and Figure 7 shows the architecture of the LENET-5 model. The structure of each layer of the LENET-5 model is described in deta

Ubuntu installation TensorFlow and its minist instances

1vmware install Ubuntu (oneself follow other tutorial easy to install Ubuntu, then install TensorFlow always error), follow this step follow TensorFlow step successful click Open Link 2 ubuntu install TensorFlow (CPU) Use PIP to click Open Link 3minist data set test, but will error, follow the online method changed after correct run click Open Link a softmax modi

Learn TensorFlow, print out the value of tensor

In the process of learning tensorflow, we need to know what the value of a tensor is, which is important, especially at the time of Debug. Maybe you can say, this is easy, just print it. In fact, print only prints output shape information, and to print out the value of the tensor, you need to use class TF. Session, class TF. InteractiveSession. Because we are building graph, we only build tensor structure shape information, and do not perform data ope

TensorFlow build your own picture data set Tfrecords (fine)

With so long TensorFlow, example ran n more, the basic flow is clear. But to do a small example of their own, various problems have come. What to do with your own picture data set. To tell you the truth, tensorflow really annoying, tube-side document tutorial on old mnist and cifar_10 this kind of good data set said, for us these beginners, completely do not know how to enter the picture. Today to share my

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