Owl API CheatsheetΒΆ

Category Description [1] Function
Element-wise basics + - * /
exponential owl.elewise.exp(x)
ln owl.elewise.ln(x)
sigmoid owl.elewise.sigm(x)
sigmoid back owl.elewise.sigm_back(y)
tanh owl.elewise.tanh(x)
tanh back owl.elewise.tanh_back(y)
relu owl.elewise.relu(x)
relu back owl.elewise.relu_back(y, x)
Matrix multiplication *
transpose .trans()
Reduction [2] sum .sum(axis)
max .max(axis)
argmax .argmax(axis)
count zero .count_zero()
Broadcast [3] broadcast + - * /
Generator fill zeros owl.zeros(shape)
fill ones owl.ones(shape)
normal distribution owl.randn(shape, mu, var)
bernoulli distribution owl.randb(shape, prob)
Shape reshape .reshape(shape)
slice owl.slice(src, dim, off, count)
concat owl.concat(arrays, dim)
I/O convert to numpy .to_numpy()
convert from numpy owl.from_numpy(nparr)
Convnet convolution (ff/bp/grad) owl.conv.Convolver
pooling (ff/bp) owl.conv.Pooler
lrn (ff/bp) owl.conv.Lrner
softmax owl.conv.softmax(x, op)
Model & Trainer neural network definition owl.net.Net
build network from Caffe’s config owl.net.CaffeNetBuilder
multi-gpu trainer owl.net.NetTrainer
feature extractor owl.net.FeatureExtractor
multi-view tester owl.net.MultiviewTester
System initialize system owl.initialize(argv)
wait for all laziness to finish owl.wait_for_all()
create cpu device owl.create_cpu_device()
create gpu device owl.create_gpu_device(id)
choose device to compute owl.set_device(dev)
[1]Descriptions of non-lazy operations are in bold text.
[2]Currently, reduction (sum, max, argmax) is only allowed on 2-D matrix along row or column.
[3]Definition of broadcast. Currently, broadcast is only allowed on 2-D matrix along row or column.