The kernel and unit test list is going to be smaller (and have all the code and CI be part of the TFLM repo). The examples list is expected to grow and will be maintained external to the TFLM repository as described in #407. BUG=#407
5.9 KiB
- TensorFlow Lite for Microcontrollers
- Build Status
- Contributing
- Getting Help
- Additional Documentation
- RFCs
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:
Build Status
Official Builds
| Build Type | Status |
|---|---|
| CI (Linux) | |
| Code Sync |
Community Supported TFLM Examples
This table captures platforms that TFLM has been ported to. Please see New Platform Support for additional documentation.
| Platform | Status |
|---|---|
| Arduino | |
| ESP32 | |
| Sparkfun Edge |
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 | |
| Hexagon | |
| RISC-V | |
| Xtensa |
Contributing
See our contribution documentation.
Getting Help
A Github issue should be the primary method of getting in touch with the TensorFlow Lite Micro (TFLM) team.
The following resources may also be useful:
-
SIG Micro email group and monthly meetings.
-
SIG Micro gitter chat room.
-
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
- Create a TensorFlow Lite Converter Issue
- Create an issue in the model optimization toolkit GitHub repository
Additional Documentation
- Continuous Integration
- Benchmarks
- Profiling
- Memory Management
- Porting Reference Kernels from TfLite to TFLM
- Optimized Kernel Implementations
- New Platform Support
- Software Emulation with Renode