theano

中文文档的描述： keras中文文档，切换后端 其实就是在 C:\Users\Administrator （Administrator是我的windos用户名字，找你对应的用户名就行）下有个文件夹 .keras ，里面有 keras.json 文件，改一下里面的内容就好了，如果没有文件夹和文件，手动创建就行。 用theano的话，keras.json写入 { " image_dim_ordering ": "th" , " epsilon ": 1e-07 , " floatx ": "float32" , " backend ": "theano" } 用thesorflow的话，keras.json写入 { " image_dim_ordering ": "tf" , " epsilon ": 1e-07 , " floatx ": "float32" , " backend ": "tensorflow" } 最后保存就可以了 文章来源: Keras 切换后端（Theano和TensorFlow）

WARNING (theano.tensor.blas): Using NumPy C-API based implementation for BLAS functions. solution： cmd conda install mkl conda install mkl-servic conda install blas .theanorc.txt ldflags=-lmkl_rt 或者 ldflags=-lblas 文章来源: win10 解决WARNING (theano.tensor.blas): Using NumPy C-API based implementation for BLAS functions.

Ubuntu16.04+CUDA8.0+Theano-0.8安装教程 Theano的安装真的是一部血泪史，花费了一个多星期的时间，终于在win7下和Ubuntu下安装theano成功，并且安装cuda、配置GPU工作。期间排了N多的坑，在这先说一下注意事项（避免各种坑）： 如果选择在Windows下安装Theano，请参考另一篇博文：https://blog.csdn.net/hczhcz0905/article/details/80422169 操作系统：Ubuntu16.04LTS 步骤如下： (1):检查自己的显卡信息，检查GPU是否支持CUDA 终端输入：lspci | grip -iVGA 然后去cuda官网查看自己的GPU版本是否在CUDA 的支持列表中。 可以看到gcc版本高于5.0,由于cuda8.0版本以后已经支持了gcc高于5,如果选择安装cuda7.5或更低的话，需要降低gcc的版本。 （3）安装NVIDIA驱动，由于cuda自带的驱动可能无法定位内核信息，所以先安装驱动程序。 先卸载之前的驱动程序：$ sudo apt remove --purge nvidia* 添加Graphic Drivers PPA $ sudoadd-apt-repository ppa:graphics-drivers/ppa $ sudo apt-get update

原文作者： lypbendlf 原文链接： https://www.cnblogs.com/BlueBlueSea/p/10778345.html 1.安装pygpu的部分 #使用豆瓣源or不使用，均安装失败 #报错： Looking in indexes: http://pypi.douban.com/simple/ Collecting pygpu No matching distribution found for pygpu #继续尝试使用conda，仍失败 conda install -c conda-forge pygpu` #报错： #尝试使用制定安装版本 pip install pygpu==0.7.5 #仍报错： Collecting pygpu==0.7.5 No matching distribution found for pygpu==0.7.5 //已保证pip是最新的。 #尝试将其拷贝到我的用户目录下 conda create -n my_root --clone="/data_d/public/miniconda2" #激活环境 source activate my_root #查看环境信息 #激活环境后再次尝试如下，仍旧失败 conda install pygpu #使用如下命令之后 sudo chown -R $USER:$USER ~/

I'm new to Theano and I wonder how to configure the default setting directly from script (without setting envir. variables). E.g. this is a working solution ( source ): $ THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python check1.py I intend to come up with the identical solution that is executed by only: $ python check1.py and the additional parameters are set directly in the script itself. E.g. somehow like this: import theano theano.set('mode', 'FAST_RUN') theano.set('device', 'gpu') theano.set('floatX', 'float32') # rest of the script Is it even possible? I read the config page

1.使用函数模型API，新建一个model，将输入和输出定义为原来的model的输入和想要的那一层的输出，然后重新进行predict. 1 #coding=utf-8 2 import seaborn as sbn 3 import pylab as plt 4 import theano 5 from keras.models import Sequential 6 from keras.layers import Dense,Activation 7 8 9 from keras.models import Model 10 11 model = Sequential() 12 model.add(Dense(32, activation='relu', input_dim=100)) 13 model.add(Dense(16, activation='relu',name="Dense_1")) 14 model.add(Dense(1, activation='sigmoid',name="Dense_2")) 15 model.compile(optimizer='rmsprop', 16 loss='binary_crossentropy', 17 metrics=['accuracy']) 18 19 # Generate dummy data 20 import

I'm trying to use the Theano library in python to do some experiments with Deep Belief Networks. I use the code in this address: DBN full code . This code use the MNIST Handwritten database . This file is already in pickle format. It is unpicked in: train_set valid_set test_set Which is further unpickled in: train_set_x, train_set_y = train_set valid_set_x, valid_set_y = valid_set test_set_x, test_set_y = test_set Please can someone give me the code that constructs this dataset in order to create my own? The DBN example I use needs the data in this format and I don't know how to do it. if

I'm trying to use Python with Theano to accelerate some code with OpenCL. I installed libgpuarray and pygpu as instructed (I think), and got no errors. The installation detected the OpenCL runtime installed. I just cannot run the Theano example for OpenCL, mainly because I don't know how to specify my GPU. My GPU is a Radeon HD 5340/5450/5470 , according to inxi . All code in the Theano documentation uses device=cuda0 and the only place where OpenCL is mentioned, it says device=openclN where N is a number. I tried device=opencl0 and got a pygpu error saying that the correct format is opencl