| commit | 6bb1e3a635b903bbe10a81f715845e37c10bf1bc | [log] [tgz] |
|---|---|---|
| author | Ryan Kuester <kuester@bdti.com> | Wed Oct 18 16:01:22 2023 -0500 |
| committer | GitHub <noreply@github.com> | Wed Oct 18 21:01:22 2023 +0000 |
| tree | 8e218404305b2757a0fbf7c71eca66d648bae73d | |
| parent | 49ab008118d255e747a746871f99b1c3d03905b7 [diff] |
build: update flatbuffers dependency to v23.5.26 (#2274) Update the third_party flatbuffers library to v23.5.26, the current version in upstream TF. Synchronize the override BUILD and build_defs.bzl files with those from upstream TF at e4485c98eae. Also update the Makefile build, which downloads flatbuffers separately. Rebase the patch applied to the download. Regenerate the generated-and-checked-in schemas (see ci/sync_from_upstream_tf.sh and codegen/preprocessor/ update_schema.sh), because they are stamped with the version of the flatbuffers library, and fail a static_assert if they are built with a different version of flatbuffers than they were generated with. BUG=unsuccessful attempt to fix warning in #2183
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 |   |
| Coral Dev Board Micro | TFLM + EdgeTPU Examples for Coral Dev Board Micro |
| Espressif Systems Dev Boards |  |
| Renesas Boards | TFLM Examples for Renesas Boards |
| Silicon Labs Dev Kits | TFLM Examples for Silicon Labs Dev Kits |
| 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 |  |
| Generate Integration Test |  |
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 TFLM, please consult the broader TensorFlow project, e.g.: