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TensorFlake

TensorFlake is my own machine learning framework. This aims to be able to train several networks on the CPU fast.

Features

  • Automatic differentiation
  • Foundational NDArray operations
  • Foundational functions for deep neural networks

TODO

  • smallvec
  • backward without create_graph
  • Efficient Linear -> matmul_add
  • Save & load
    • param_bin.rs
    • serde
      • Restore optimizers
      • Restore Fn (MLP::activation, etc...)
  • Strong typing -> Functional API (tensorflake::function::chain)
    • Generic for dimension
  • Multi thread
    • High level API
    • Synchronous update
    • Asynchronous update
    • Specify the number of thread
  • Impl ops
  • Lazy execution for optimization on the graph
  • Regularization
  • Tensordot -> ndarray_einsum_beta
  • Transposed convolution
  • Batch normalization
  • Embedding
  • Sequential
  • Param creator -> Initializer
  • Benchmarks
  • Measure the execution time of functions and export it as dot file
  • Tensor summarization
  • Sparse tensor
  • Examples
    • CNN
    • RNN
    • GAN
    • VAE
  • wasm
  • safe rust
  • Compare performance against GPU Tensorflow
  • Fitting report
  • Generic ndarray
  • functions
    • reduce_sum
    • signum
  • Optimize consecutive element-wise operations

Benchmark

$ cargo +nightly bench -q > benches/result.txt

Author

Copyright

Copyright (c) 2022 carrotflakes (carrotflakes@gmail.com)

License

Licensed under the MIT License.

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