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| * [TensorFlow Lite for Microcontrollers](#tensorflow-lite-for-microcontrollers) |
| * [Build Status](#build-status) |
| * [Official Builds](#official-builds) |
| * [Community Supported TFLM Examples](#community-supported-tflm-examples) |
| * [Community Supported Kernels and Unit Tests](#community-supported-kernels-and-unit-tests) |
| * [Contributing](#contributing) |
| * [Getting Help](#getting-help) |
| * [Additional Documentation](#additional-documentation) |
| * [RFCs](#rfcs) |
| |
| <!-- Added by: advaitjain, at: Mon 04 Oct 2021 11:23:57 AM PDT --> |
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| # TensorFlow Lite for Microcontrollers |
| |
| TensorFlow Lite for Microcontrollers is a port of TensorFlow Lite designed to |
| run machine learning models on DSPs, microcontrollers and other devices with |
| limited memory. |
| |
| Additional Links: |
| * [Tensorflow github repository](https://github.com/tensorflow/tensorflow/) |
| * [TFLM at tensorflow.org](https://www.tensorflow.org/lite/microcontrollers) |
| |
| # Build Status |
| |
| * [GitHub Status](https://www.githubstatus.com/) |
| |
| ## Official Builds |
| |
| Build Type | Status | |
| ----------- | --------------| |
| CI (Linux) | [](https://github.com/tensorflow/tflite-micro/actions/workflows/ci.yml?query=event%3Aschedule) | |
| Code Sync | [](https://github.com/tensorflow/tflite-micro/actions/workflows/sync.yml) | |
| |
| |
| ## Community Supported TFLM Examples |
| This table captures platforms that TFLM has been ported to. Please see |
| [New Platform Support](tensorflow/lite/micro/docs/new_platform_support.md) for |
| additional documentation. |
| |
| Platform | Status | |
| ----------- | --------------| |
| Arduino | [](https://github.com/tensorflow/tflite-micro-arduino-examples/actions/workflows/ci.yml) [](https://github.com/antmicro/tensorflow-arduino-examples/actions/workflows/test_examples.yml) | |
| ESP32 | [](https://github.com/espressif/tflite-micro-esp-examples/actions/workflows/build.yml) | |
| Sparkfun Edge | [](https://github.com/advaitjain/tflite-micro-sparkfun-edge-examples/actions/workflows/ci.yml) |
| |
| |
| ## Community Supported Kernels and Unit Tests |
| This is a list of targets that have optimized kernel implementations and/or run |
| the TFLM unit tests using software emulation or instruction set simulators. |
| |
| Build Type | Status | |
| ----------- | --------------| |
| Cortex-M | [](https://github.com/tensorflow/tflite-micro/actions/workflows/cortex_m.yml) | |
| Hexagon | [](https://github.com/tensorflow/tflite-micro/actions/workflows/hexagon.yml) | |
| RISC-V | [](https://github.com/tensorflow/tflite-micro/actions/workflows/riscv.yml) | |
| Xtensa | [](https://github.com/tensorflow/tflite-micro/actions/workflows/xtensa.yml?query=event%3Aschedule) [](https://github.com/advaitjain/tflite-micro/tree/local-continuous-builds/tensorflow/lite/micro/docs/local_continuous_builds/xtensa.md#summary) | |
| |
| |
| # Contributing |
| See our [contribution documentation](CONTRIBUTING.md). |
| |
| # Getting Help |
| |
| A [Github issue](https://github.com/tensorflow/tflite-micro/issues/new/choose) |
| should be the primary method of getting in touch with the TensorFlow Lite Micro |
| (TFLM) team. |
| |
| The following resources may also be useful: |
| |
| 1. SIG Micro [email group](https://groups.google.com/a/tensorflow.org/g/micro) |
| and |
| [monthly meetings](http://doc/1YHq9rmhrOUdcZnrEnVCWvd87s2wQbq4z17HbeRl-DBc). |
| |
| 1. SIG Micro [gitter chat room](https://gitter.im/tensorflow/sig-micro). |
| |
| 1. For questions that are not specific to inference with TFLM (for example |
| model conversion and quantization) please use the following resources: |
| * Send an email to the [TfLite Mailing List](https://groups.google.com/a/tensorflow.org/g/tflite) |
| * Create a [TensorFlow Lite Converter Issue](https://github.com/tensorflow/tensorflow/issues/new?assignees=&labels=TFLiteConverter&template=60-tflite-converter-issue.md) |
| * Create an issue in the [model optimization toolkit](https://github.com/tensorflow/model-optimization) GitHub repository |
| |
| |
| # Additional Documentation |
| |
| * [Continuous Integration](docs/continuous_integration.md) |
| * [Benchmarks](tensorflow/lite/micro/benchmarks/README.md) |
| * [Profiling](tensorflow/lite/micro/docs/profiling.md) |
| * [Memory Management](tensorflow/lite/micro/docs/memory_management.md) |
| * [Porting Reference Kernels from TfLite to TFLM](tensorflow/lite/micro/docs/porting_reference_ops.md) |
| * [Optimized Kernel Implementations](tensorflow/lite/micro/docs/optimized_kernel_implementations.md) |
| * [New Platform Support](tensorflow/lite/micro/docs/new_platform_support.md) |
| * [Software Emulation with Renode](tensorflow/lite/micro/docs/renode.md) |
| * [Python Dev Guide](docs/python.md) |
| * [Automatically Generated Files](docs/automatically_generated_files.md) |
| |
| # RFCs |
| |
| 1. [Pre-allocated tensors](tensorflow/lite/micro/docs/rfc/001_preallocated_tensors.md) |
| 1. [TensorFlow Lite for Microcontrollers Port of 16x8 Quantized Operators](tensorflow/lite/micro/docs/rfc/002_16x8_quantization_port.md) |
