TinNet - A compact C++17 based deep learning library.

[email protected]

A compact DNN library.

Build

This project uses Bazel as a build system(1.0 or above required) and compiles with Clang(NOT required, automatically fulfilled).

To build, issue below.

bazel build //tinnet:main

Windows are not supported currently.

Test

To run all tests, issue below.

bazel test //tinnet:test

Example Usages

Please refer the example projects.

Benchmarks

TODO

Owner
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Comments
  • Introducing Graph system

    Introducing Graph system

    TinNet is now introducing new feature : Graph system!

    A lot of deep-learning libraries are supporting this feature. It allows users to create various models without implementing model-specific layers. So far, TinNet is not flexible or feature-rich. By introducing the graph system, TinNet will be more powerful and more flexible.

    This feature is under development.

  • Implement the nodes

    Implement the nodes

    • [ ] Basic arithmetic nodes
    • [x] Basic shape manipulating nodes
    • [ ] Basic math function nodes
    • [x] Dense node
    • [x] Convolution node
    • [ ] Pooling node(max, average, etc.)
    • [ ] RNN nodes(Basic, LSTM, GRU, etc.)
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