ESP-NN

The library contains optimised NN (Neural Network) functions for various Espressif chipsets.

  • Supported platforms:

    • TensorFlow Lite Micro (TFLite Micro). Repo can be found here
  • Supported ESP chipsets include:

    • ESP32-S3 (Assembly versions optimised to benefit from vector instructions of ESP32-S3)
    • ESP32 (Generic optimisations)
    • ESP32-C3 (Generic optimisations)

Performance

Kernelwise performance for s8 versions:

  • Kernelwise performance on ESP32-S3 chip
    • Numbers are ticks taken for kernel to execute
    • Chip config: 240MHz, SPI: QPI 80MHz, Data cache: 64KB
    Function ANSI C ESP32-S3 Opt Opt Ratio Data info Memory
    elementwise_add 320397 87119 3.68 size = 1615 External
    elementwise_mul 125958 44239 2.85 size = 1615 External
    convolution 4663012 428675 10.88 input(10,10), filter(64x1x1x64) External
    convolution 301014 32433 9.28 input(8,8), filter(16x1x1x16) External
    convolution 2115418 1020923 2.07 input(10,10), filter(64x3x3x3) External
    depthwise conv 1190062 203278 5.85 input (18, 18), pad(0,0), stride(1,1) filter: 1x3x3x16 External
    depthwise conv 837072 182335 4.59 input (12, 12), pad(1,1), stride(1,1) filter: 8x5x5x4 External
    max pool 485714 76747 6.33 input(16,16), filter (1x3x3x16) Internal
    avg pool 541462 160580 3.37 input(16,16), filter (1x3x3x16) Internal
    fully connected 15853 9547 1.66 len: 265, ch = 3 Internal
    prelu (relu6) 19472 2734 7.12 size, 1615 Internal

Configuration

  • To configure, please use idf.py menuconfig and under ESP-NN select NN_OPTIMIZATIONS

  • There are two options presented:

    • Optimized versions
    • ANSI C
  • Default selection is for Optimized versions. For ESP32-S3, assembly versions are automatically selected, whereas for other chipsets (viz., ESP32, ESP32-C3), generic optimisations are selected.

  • For debugging purposes, you may want to select ANSI C reference versions.

Contributing

If you encounter an issue with ESP-NN, or wish to submit a feature request, please use the Issues section on the Github.

For general questions related to this library, please use the esp32.com forum.

Copyrights and License

All original source code in this repository is Copyright (C) 2020-2021 Espressif Systems. This source code is licensed under the Apache License 2.0 as described in the file LICENSE.