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Tensorflow obtains the variable dimension information.

Tensorflow obtains the variable dimension information. Tensorflow version 1.4 Getting a variable dimension is a frequently used operation. You can use the following operations to obtain a variable dimension in tensorflow: Tensor. shape Tensor. get_shape () Tf. shape (input, name = None, out_type = tf. int32) Perform A simple analysis on the above three o

TensorFlow implements Batch Normalization,

TensorFlow implements Batch Normalization, I. BN (Batch Normalization) Algorithm 1. Importance of Data normalization The essence of the neural network learning process is to learn Data Distribution. When training data is different from test data distribution, the generalization capability of the model is greatly reduced. On the other hand, if the data distribution of each batch of batch is also different during the training process, the iterative lear

Machine Learning Series-tensorflow-03-linear regression Linear Regression

Use tensorflow to implement linear regression of data Import related libraries import tensorflow as tfimport numpyimport matplotlib.pyplot as pltrng = numpy.random Parameter settings learning_rate = 0.01training_epochs = 1000display_step = 50 Training data train_X = numpy.asarray([3.3,4.4,5.5,6.71,6.93,4.168,9.779,6.182,7.59,2.167, 7.042,10.791,5.313,7.997,5.654,9.27,3.1])train_Y = numpy

Ubuntu16.04 installation configuration Numpy,scipy,matplotlibm,pandas and sklearn+ deep learning tensorflow configuration (non-Anaconda environment)

Python-dev If the previous command doesn't work, you can use the following command to resolveUsing the Aptitude tool sudo apt-get install aptitudesudo aptitude install Python-dev Install the Python-dev now to install the PYTHON-PIP. sudo apt-get install Python-pip Type PIP in the terminal and, if shown, the installation succeeds4. Installation ResultsThe packages used for numeric calculations and drawings are now installed with Pip, respectively, NumPy scipy mat

TensorFlow Mac Installation Method

480 pip Install HTTPS://STORAGE.GOOGLEAPIS.COM/TENSORFLOW/MAC/TENSORFLOW-0.5.0-PY2-NONE-ANY.WHL481 virtualenv--system-site-packages ~/tensorflow482 CD ~/tensorflow483 Source Bin/activate484 pip Install--upgrade 485 pip install HTTPS://STORAGE.GOOGLEAPIS.COM/TENSORFLOW/MAC/TENSORFLOW-0.5.0-PY2-NONE-ANY.WHL486 pip instal

Time series prediction using TensorFlow seq2seq

Time series prediction can be based on short-term forecasts, long-term forecasts and specific scenarios, such as Arma, ARIMA, neural network prediction, SVM prediction, grey prediction, fuzzy prediction, combined forecasting method and so on. The so-called no best model, only the most suitable model. As to which model can achieve the highest precision for a particular predictive problem, it needs to be proved by experiments. In this paper, a single Variable time series prediction experiment is c

Tensorflow-slim Learning Notes (ii) the first level catalogue code reading _ machine learning

Http://www.cnblogs.com/bmsl/p/dongbin_bmsl_02.html By reading code to learn, always the most direct and fast. This chapter will explain the code for the first level of slim directory Tensorflow/tensorflow/contrib/slim/python/slim. This layer of code mainly includes learning.py, evaluation.py, summary.py, queue.py and model_analyzer.py, respectively corresponding to the model training, testing, logging, que

TensorFlow about tensor shape array _ machine learning

Order, shape, data type of tensor TensorFlow uses this data structure to represent all of the information. You can think of a tensor as an n-dimensional array or list. A tensor has a static type and a dynamic type of dimension. Tensor can flow between nodes in the diagram. Order In the TensorFlow system, The dimensions of the tensor are described as orders. But the order of the tensor and the order of the

TensorFlow Distributed Cluster

The previous blog said how to create a cluster of local servers, today talk about how to create a truly distributed cluster. We have prepared two machines, as follows: 192.168.0.192 192.168.0.193 We will use these two machines to form a cluster, and then throw the TensorFlow task on one of the nodes to run. We've prepared two server programs to start on two machines to form a cluster and receive tasks. Create a client program to submit a task to the

TensorFlow visual Tensorboard "No graph definition files were found." Error

Personally feel tensorflow relative to other in-depth learning Coulai said is relatively good installation, I began to install Theano had not been installed for several days, and finally have no way to install the TensorFlow, even a little problem is not out, one-time installation is good, Chong This I also optimistic tensorflow.

Using TensorFlow to implement convolution and deconvolution detailed process, interview Python to achieve convolution operation

the step, which is a one-dimensional vector, length 4 padding: string type of quantity, can only be "SAME", "VALID" one of them, this value determines the different convolution mode Use_ CUDNN_ON_GPU:BOOL type, whether to use CUDNN acceleration, default to True The result returns a tensor, the output, which is what we often call the feature map implementation So how does the TensorFlow convolution work, with some examples to explain it: 1. Considerin

TensorFlow will train the good model freeze, the weight is solidified into the diagram inside, and use this model to predict (tf.graph_util.convert_variables_to_constants function) __ function

We often need to save the PB file of the TensorFlow model, which is very handy when using the Tf.graph_util.convert_variables_to_constants function. 1. Training Network: fully_conected.py Import argparse import OS import time import TensorFlow as TF import datasets_mnist # Basic model parameters as external Flags. FLAGS = None num_classes = # The mnist images are always 28x28. image_size = Image_pixels =

Mac OS installation TensorFlow Runtimeerror:broken toolchain:cannot link a simple C program

Mac OS installation TensorFlow Runtimeerror:broken toolchain:cannot link a simple C program Problems with Mac OS installation TensorFlow Runtimeerror:broken Toolchain:cannot Link a simple C program This is actually a problem when PIP is updating the numpy. Solving method sudo archflags=-wno-error=unused-command-line-argument-hard-error-in-future pip install--upgrade https:// Storage.googleapis.com/

TensorFlow methods for reading and using different formats pretrained model in different training scenarios

analysis and examples of different application scenarios TensorFlow read pre-training model is a common operation in model training, and the typical application scenarios include: 1) A restart is required after the training interruption, the previous checkpoint (including. data. Meta. Index checkpoint these four files) are saved, then the model is reloaded and the training or prediction continues from the last breakpoint. The implementation method is

TensorFlow Learning (4): Save the parameter naming mechanism for model Saver.save () and restore and create the handwriting recognition engine

Preface In the previous chapter, we talked about how to train a network, click to view the blog, this chapter we say TensorFlow when saving the network is how to give different parameters named, and how to restore the saved parameters to the reconstructed network structure. Finally, the reconstructed network is used to predict a picture (any pixel) that contains a number (0-9). Code main reference Github:github address body How to view the saved para

TensorFlow combat Cat and Dog War (a) training your own data

This article is a reference to some notes written by http://i.youku.com/deeplearning101, the great God's video. This is a simple two classification problem, the purpose is to distinguish between cat and dog pictures, data set in this link: http://pan.baidu.com/s/1dFd8kmt Password: psor First write a input_data.py this file, the purpose is to return input_data.py #coding =utf-8 import tensorflow as TF import numpy as NP import OS # file_dir = '/home/h

ubuntu16.0 Anaconda3 installation TensorFlow Keras Error Collection

Tags: caff href tps medium mode line DAO use UDAToday use Anaconda3 to install TensorFlow and Caffe, the main reference blogNow the computer environment:ubuntu16.04cuda8.0cudnn6.0Anaconda31. From Scipy.misc import imread,imresize errorHint error importerror:cannot import name ImreadBut import scipy is displayed correctly.Solution: Pip install Pillow. 2. Libcublas.so.9.0:cannot open Shared object file:no such file or directoryCause: The new version of

Ubuntu Deep learning Environment Building Tensorflow+pytorch

Current Computer Configuration: Ubuntu 16.04 + GTX1080 GraphicsConfiguring a deep learning environment, using Tsinghua Source to install a Miniconda environment is a very good choice. In particular, today found Conda install-c Menpo opencv3 A command can be smoothly installed on the OPENCV, before their own time also encountered a lot of errors. Conda installation of the TensorFlow and pytorch two kinds of framework is also very convenient, for not go

Learning notes TF053: Recurrent Neural Network, TensorFlow Model Zoo, reinforcement learning, deep forest, deep learning art, tf053tensorflow

Learning notes TF053: Recurrent Neural Network, TensorFlow Model Zoo, reinforcement learning, deep forest, deep learning art, tf053tensorflow Recurrent Neural Networks. Bytes. Natural language processing (NLP) applies the network model. Unlike feed-forward neural network (FNN), cyclic networks introduce qualitative loops, and the signal transmission does not disappear and continues to survive. The traditional neural network layer is fully connected, a

Windows Environment Installation TensorFlow

The machine environment Win7, want to install TensorFlow, tried for a long time, just installed. The official website is kingly.Note: Currently tensorflow only supports Python 3.5 in the Windows environment. *64,. So the Python version must be under the right.The approach I'm using isInstalling with native Pip, using the CPU version.Here is the shared Python link Http://pan.baidu.com/s/1qXGlYdIThe following

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