| commit | 95d4d90cafb75b936f11a1e425591d6703c4e14e | [log] [tgz] |
|---|---|---|
| author | deqiangc <86809673+deqiangc@users.noreply.github.com> | Thu Jan 06 22:44:30 2022 -0800 |
| committer | GitHub <noreply@github.com> | Fri Jan 07 06:44:30 2022 +0000 |
| tree | b66f423c9b2b5dcd2787583a61b8136b273b38d7 | |
| parent | e19a528addfacc06e694d81c65ba2cc26422becd [diff] |
By default set CC to be clang for msan, asan and ubsan bazel build. (#843) Previously typing "bazel build --config=msan" leads to a build failure on environment that has gcc as default and one has to type "CC=clang bazel build --config=msan". With this change, only can do "bazel build --config=msan". Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com>
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 |  |
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: