theano | 易学教程

Error while calling eval() on Tensor variable in keras

阅读更多关于 Error while calling eval() on Tensor variable in keras

问题 I am using keras and using a layer output for some modifications. Before, using the output ( a tensor variable ) I am converting it to numpy array and thus calling eval() on it, as below: def convert_output(orig_output): conv_output = invoke_modifications(orig_output.eval(), 8) The code fails with following error: File "<ipython-input-11-df86946997d5>", line 1, in <module> orig_output.eval() File "C:\ENV\p34\lib\site-packages\theano-0.9.0.dev4-py3.4.egg\theano\gof\graph.py", line 516, in eval

compilation issue when running theano

阅读更多关于 compilation issue when running theano

问题 I installed theano on windows 8, 64 bit. I am using anaconda implementation, python 3.4. Trying to install theano, I diligently followed all steps on this link (which helped on another computer with similar configuration): http://rosinality.ncity.net/doku.php?id=python:installing_theano (English and Korean) whenever I type 'import theano' on my IDE (pycharm) I get a long error message, but I believe the most meaningful portion is: import theano >>>>Exception: Compilation failed (return status

Changing pretrained AlexNet classification in Keras

阅读更多关于 Changing pretrained AlexNet classification in Keras

问题 I am using a AlexNet with pretrained weights(heuritech/convnets-keras) for a classification problem with 8 classes instead of 1000. After initialising the network with Model(input=..,output=..) and loading the initial weights, I drop the last two layers, Dense(1000) and Activation(softmax), and add my own two layers: Dense(8) and Activation(softmax). But then, after running I get an error Error when checking model target: expected softmax to have shape (None, 1000) but got array with shape

Theano with Anaconda on Windows: how to setup BLAS?

阅读更多关于 Theano with Anaconda on Windows: how to setup BLAS?

I've used Anaconda to install Theano (and Keras) on Windows 7 64bit. Here are my steps. Install the latest Anaconda for Python 3.5 conda install mingw libpython pip install Theano conda install pydot-ng pip install keras Edit .keras/keras.json to use "theano" instead of "tensorflow". Open Jupyter, copy and paste this code: https://github.com/fchollet/keras/blob/master/examples/cifar10_cnn.py It executes fine until the call to model.fit : imports, data download, model compilation all work. Please note that I set data_augmentation to False. The call to model.fit fails with the following error

Why does the floatX's flag impact whether GPU is used in Theano?

阅读更多关于 Why does the floatX's flag impact whether GPU is used in Theano?

问题 I am testing Theano with GPU using the script provided in the tutorial for that purpose: # Start gpu_test.py # From http://deeplearning.net/software/theano/tutorial/using_gpu.html#using-gpu from theano import function, config, shared, sandbox import theano.tensor as T import numpy import time vlen = 10 * 30 * 768 # 10 x #cores x # threads per core iters = 1000 rng = numpy.random.RandomState(22) x = shared(numpy.asarray(rng.rand(vlen), config.floatX)) f = function([], T.exp(x)) print(f.maker

Update keras.json on Google Colab

阅读更多关于 Update keras.json on Google Colab

问题 I tried to update keras.json on Google Colabs, but its throwing UnsupportedOperation error Is there any other alternative to achieve this? 回答1: You're opening the file as readonly -- pass 'w' to the open call on line 9. (docs) 来源： https://stackoverflow.com/questions/50083075/update-keras-json-on-google-colab

Indexing tensor with index matrix in theano?

阅读更多关于 Indexing tensor with index matrix in theano?

问题 I have a theano tensor A such that A.shape = (40, 20, 5) and a theano matrix B such that B.shape = (40, 20). Is there a one-line operation I can perform to get a matrix C, where C.shape = (40, 20) and C(i,j) = A[i, j, B[i,j]] with theano syntax? Essentially, I want to use B as an indexing matrix; what is the most efficient/elegant to do this using theano? 回答1: You can do the following in numpy: import numpy as np A = np.arange(4 * 2 * 5).reshape(4, 2, 5) B = np.arange(4 * 2).reshape(4, 2) % 5

How do you free up gpu memory?

阅读更多关于 How do you free up gpu memory?

问题 When running theano, I get an error: not enough memory. See below. What are some possible actions that can be taken to free up memory? I know I can close applications etc, but I just want see if anyone has other ideas. For example, is it possible to reserve memory? THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python conv_exp.py Using gpu device 0: GeForce GT 650M Trying to run under a GPU. If this is not desired, then modify network3.py to set the GPU flag to False. Error allocating

Python Numpy Error: ValueError: setting an array element with a sequence

阅读更多关于 Python Numpy Error: ValueError: setting an array element with a sequence

问题 I am trying to build a dataset similar to mnist.pkl.gz provided in theano logistic_sgd.py implementation. Following is my code snippet. import numpy as np import csv from PIL import Image import gzip, cPickle import theano from theano import tensor as T def load_dir_data(csv_file=""): print(" reading: %s" %csv_file) dataset=[] labels=[] cr=csv.reader(open(csv_file,"rb")) for row in cr: print row[0], row[1] try: image=Image.open(row[0]+'.jpg').convert('LA') pixels=[f[0] for f in list(image

Advanced 2d indexing in Theano to extract multiple pixels from an image

阅读更多关于 Advanced 2d indexing in Theano to extract multiple pixels from an image

问题 Background I have an image that I want to sample at a number (P) of x,y coordinates. In Numpy I can use advanced indexing to do this via: n_points = n_image[ [n_pos[:,1],n_pos[:,0]] ] This returns a vector of P pixels sampled from the image. Question How can I do this advanced indexing in Theano? What I've tried I've tried the corresponding code in theano: t_points = t_image[ [t_pos[:,1],t_pos[:,0]] ] this compiles and executes without any warning messages, but results in an output tensor of