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55 lines
2.6 KiB
Markdown
55 lines
2.6 KiB
Markdown
# ESP-NN
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The library contains optimised NN (Neural Network) functions for various Espressif chipsets.
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* Supported platforms:
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* TensorFlow Lite Micro (TFLite Micro). Repo can be found [here](https://github.com/espressif/tflite-micro-esp-examples)
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* Supported ESP chipsets include:
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* ESP32-S3 (Assembly versions optimised to benefit from vector instructions of ESP32-S3)
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* ESP32 (ANSI C versions)
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## Performance
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### Kernelwise performance for s8 versions:
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* Kernelwise performance on ESP32-S3 chip
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* Numbers are ticks taken for kernel to execute
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* Chip config: 240MHz, SPI: QPI 80MHz, Data cache: 64KB
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| Function | ANSI C | ESP32-S3 Opt | Opt Ratio | Data info | Memory |
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| ----------------| --------|---------|---------|-------------|-----------|
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| elementwise_add | 320397 | 87119 | 3.68 | size = 1615 | External |
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| elementwise_mul | 125958 | 44239 | 2.85 | size = 1615 | External |
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| convolution | 4663012 | 428675 | 10.88 | input(10,10), filter(64x1x1x64) | External |
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| convolution | 301014 | 32433 | 9.28 | input(8,8), filter(16x1x1x16) | External |
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| convolution | 2115418 | 1020923 | 2.07 | input(10,10), filter(64x3x3x3) | External |
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| depthwise conv | 1190062 | 203278 | 5.85 | input (18, 18), pad(0,0), stride(1,1) filter: 1x3x3x16 | External |
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| depthwise conv | 837072 | 182335 | 4.59 | input (12, 12), pad(1,1), stride(1,1) filter: 8x5x5x4 | External |
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| max pool | 485714 | 76747 | 6.33 | input(16,16), filter (1x3x3x16) | Internal |
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| avg pool | 541462 | 160580 | 3.37 | input(16,16), filter (1x3x3x16) | Internal |
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| fully connected | 15853 | 9547 | 1.66 | len: 265, ch = 3 | Internal |
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| prelu (relu6) | 19472 | 2734 | 7.12 | size, 1615 | Internal |
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## Configuration
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* To configure, please use `idf.py menuconfig` and under `ESP-NN` select `NN_OPTIMIZATIONS`
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* There are two options presented:
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* Optimized versions
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* ANSI C
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* Default selection is for `Optimized versions`. For ESP32-S3, assembly versions are automatically selected, whereas for ESP32, ANSI-C versions are selected by default.
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* For debugging purposes, you may want to select `ANSI C`
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## Contributing
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If you encounter an issue with ESP-NN, or wish to submit a feature request, please use the Issues section on the Github.
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For general questions related to this library, please use the esp32.com forum.
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## Copyrights and License
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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.
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