| commit | cfa4c91d1b36c37c7c104b9c664615e59f1abfe3 | [log] [tgz] |
|---|---|---|
| author | Alpha BAO <zhuijun.bao@outlook.com> | Sat Feb 24 13:40:47 2024 +0800 |
| committer | GitHub <noreply@github.com> | Sat Feb 24 05:40:47 2024 +0000 |
| tree | 1806762d442c096a30fa7b8f5749190f29f86c37 | |
| parent | 8085cecefcc2daefbc4c4480c644b59052841b95 [diff] |
Fix array out-of-bounds access in WideDynamicFuncLut (#2468) ### Problem description: In the original code, pointer arithmetic of gain_lut and the assignment of gain_lut[4 * interval + 3] could potentially lead to out-of-bounds array access. On certain architectures (e.g., macOS ARM64), this out-of-bounds access causes the program to crash. BUG=None, reported issue#2464 ### Solution: Increase the size of the gain_lut_storage array by 1 to provide an extra buffer and prevent overflow during the calculation within the loop. ### Risks and considerations: Increasing the array size will slightly increase memory usage. In extremely resource-constrained systems, alternative algorithm implementations may need to be considered.
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.: