mirror of
https://github.com/gentoo-mirror/guru.git
synced 2026-04-07 11:20:48 -04:00
90 lines
2.2 KiB
XML
90 lines
2.2 KiB
XML
<?xml version="1.0" encoding="UTF-8"?>
|
|
<!DOCTYPE pkgmetadata SYSTEM "https://www.gentoo.org/dtd/metadata.dtd">
|
|
<pkgmetadata>
|
|
<maintainer type="person">
|
|
<email>lssndrbarbieri@gmail.com</email>
|
|
<name>Alessandro Barbieri</name>
|
|
</maintainer>
|
|
<longdescription lang="en">
|
|
Features
|
|
|
|
Reasonably fast, without GPU:
|
|
With TBB threading and SSE/AVX vectorization.
|
|
98.8% accuracy on MNIST in 13 minutes training (@Core i7-3520M).
|
|
Portable and header-only:
|
|
Runs anywhere as long as you have a compiler which supports C++14.
|
|
Just include tiny_dnn.h and write your model in C++. There is nothing to install.
|
|
Easy to integrate with real applications:
|
|
No output to stdout/stderr.
|
|
A constant throughput (simple parallelization model, no garbage collection).
|
|
Works without throwing an exception.
|
|
Can import caffe's model.
|
|
Simply implemented:
|
|
A good library for learning neural networks.
|
|
|
|
Supported networks
|
|
|
|
layer-types
|
|
|
|
core
|
|
fully connected
|
|
dropout
|
|
linear operation
|
|
zero padding
|
|
power
|
|
convolution
|
|
convolutional
|
|
average pooling
|
|
max pooling
|
|
deconvolutional
|
|
average unpooling
|
|
max unpooling
|
|
normalization
|
|
contrast normalization (only forward pass)
|
|
batch normalization
|
|
split/merge
|
|
concat
|
|
slice
|
|
elementwise-add
|
|
activation functions
|
|
|
|
tanh
|
|
asinh
|
|
sigmoid
|
|
softmax
|
|
softplus
|
|
softsign
|
|
rectified linear(relu)
|
|
leaky relu
|
|
identity
|
|
scaled tanh
|
|
exponential linear units(elu)
|
|
scaled exponential linear units (selu)
|
|
loss functions
|
|
|
|
cross-entropy
|
|
mean squared error
|
|
mean absolute error
|
|
mean absolute error with epsilon range
|
|
optimization algorithms
|
|
|
|
stochastic gradient descent (with/without L2 normalization)
|
|
momentum and Nesterov momentum
|
|
adagrad
|
|
rmsprop
|
|
adam
|
|
adamax
|
|
</longdescription>
|
|
<use>
|
|
<flag name="double-precision">Build tiny-dnn with double precision computations</flag>
|
|
<!--<flag name="libdnn">Build tiny-dnn with GreenteaLibDNN library support</flag>-->
|
|
<!--<flag name="nnpack">Build tiny-dnn with NNPACK library support</flag>-->
|
|
<flag name="opencl">Build tiny-dnn with OpenCL library support</flag>
|
|
<flag name="serialization">Build tiny-dnn with Serialization support</flag>
|
|
<flag name="tbb">Build tiny-dnn with TBB library support</flag>
|
|
</use>
|
|
<upstream>
|
|
<remote-id type="github">tiny-dnn/tiny-dnn</remote-id>
|
|
</upstream>
|
|
</pkgmetadata>
|