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Diffstat (limited to 'dev-cpp/tiny-dnn/metadata.xml')
| -rw-r--r-- | dev-cpp/tiny-dnn/metadata.xml | 89 |
1 files changed, 89 insertions, 0 deletions
diff --git a/dev-cpp/tiny-dnn/metadata.xml b/dev-cpp/tiny-dnn/metadata.xml new file mode 100644 index 000000000000..0bc53e1c06ed --- /dev/null +++ b/dev-cpp/tiny-dnn/metadata.xml @@ -0,0 +1,89 @@ +<?xml version="1.0" encoding="UTF-8"?> +<!DOCTYPE pkgmetadata SYSTEM "http://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> |