git push --recurse-submodules=on-demand
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X = np.array([ [0,0,1],[0,1,1],[1,0,1],[1,1,1] ]) | |
y = np.array([[0,1,1,0]]).T | |
syn0 = 2*np.random.random((3,4)) - 1 | |
syn1 = 2*np.random.random((4,1)) - 1 | |
for j in xrange(60000): | |
l1 = 1/(1+np.exp(-(np.dot(X,syn0)))) | |
l2 = 1/(1+np.exp(-(np.dot(l1,syn1)))) | |
l2_delta = (y - l2)*(l2*(1-l2)) | |
l1_delta = l2_delta.dot(syn1.T) * (l1 * (1-l1)) | |
syn1 += l1.T.dot(l2_delta) |
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addpath matlab | |
vl_compilenn('enableGPU', 1, 'cudaRoot', '/usr/local/cuda', 'cudaMethod', 'nvcc', 'enableCudnn', 1, 'cudnnRoot', 'local/'); |
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git remote add -t dag matconvnet https://github.com/vlfeat/matconvnet | |
git pull matconvnet dag |
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export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH |
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An extremely handy tool :: Incremental history searching | |
In terminal enter: | |
gedit ~/.inputrc | |
Then copy paste and save: | |
"\e[A": history-search-backward | |
"\e[B": history-search-forward |
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name: "CaffeNet" | |
layers { | |
name: "data" | |
type: DATA | |
top: "data" | |
top: "label" | |
data_param { | |
source: "@YOUR_PATH_TO_DATA@/chairs_128x128_reduced/data-lmdb" | |
batch_size: 64 | |
scale: 0.00390625 |
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name: "CaffeNet" | |
layers { | |
name: "data" | |
type: DATA | |
top: "data" | |
data_param { | |
source: "/misc/lmbraid10/dosovits/Datasets/ILSVRC2012/all/val_leveldb" | |
backend: LEVELDB | |
batch_size: 16 | |
crop_size: 227 |
gs -sDEVICE=pdfwrite -dCompatibilityLevel=1.4 -dPDFSETTINGS=/screen -dNOPAUSE -dQUIET -dBATCH -sOutputFile=output.pdf input.pdf
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convert -density 300 \[TensorFlow\]\ Sequence-to-Sequence\ Models.pdf TensorFlow/output.png |