| commit | 62f1ec8ed1caed13a077d3881cf24596a841d91b | [log] [tgz] |
|---|---|---|
| author | TFLM-bot <tflm-github-bot@google.com> | Tue Mar 29 09:36:00 2022 -0700 |
| committer | GitHub <noreply@github.com> | Tue Mar 29 16:36:00 2022 +0000 |
| tree | b64f88b7769db9de8d8dae3b17bd20a45898d0db | |
| parent | 1a0c74232ef6ec6f513e9026e3c47e46089ccb88 [diff] |
Automated size log update (#1005)
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 Type | Status |
|---|---|
| CI (Linux) |  |
| Code Sync |  |
This table captures platforms that TFLM has been ported to. Please see New Platform Support for additional documentation.
| Platform | Status |
|---|---|
| Arduino |   |
| ESP32 |  |
| Sparkfun Edge |  |
| Texas Instruments Dev Boards |  |
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 |   |
See our contribution documentation.
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:
