- TensorFlow Lite for Microcontrollers
- Build Status
- Contributing
- Getting Help
- Additional Documentation
- RFCs
This tensorflow micro-lite target is Knowles IA8201. The base is https://github.com/cad-audio/tflite-micro update: 07/23/2024
- Xtensa Development Kit, 2020.4-RI Linux/Win32
- Contributing
build/build_xtensa_lib.sh
target-platform:
- dmx: DMX core
- hmd: HMD core
- hifi: HMD core/ hifi-3 instruction hmd core
make-target:
- << empty is release >>
- test_kernel_fully_connected_test
example: build dmx test
$ cd build
$ bash build_xtensa_lib.sh dmx test
or make command make a release hifi
$ make -f tensorflow/lite/micro/tools/make/Makefile TARGET=xtensa OPTIMIZED_KERNEL_DIR=xtensa TARGET_ARCH=hifi3 \
XTENSA_TOOLS_VERSION=RI-2020.4-linux XTENSA_CORE=hmd1aRI04 XTENSA_BASE=/home/jimchen/xtensa/XtDevTools/install/ \
BUILD_TYPE=release RM_TFLM_SIGNAL=1 TEST_MODE=0
- Xtensa SVDF/FC was optimized by HMD MVM instructions by enabling USE_HMD_MVM_OPT macro
- The kernl's weights was supposed re-mapping in the external
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.:
- Create a topic on the TensorFlow Discourse forum
- Send an email to the TensorFlow Lite mailing list
- Create a TensorFlow issue
- Create a Model Optimization Toolkit issue
- Continuous Integration
- Benchmarks
- Profiling
- Memory Management
- Logging
- Porting Reference Kernels from TfLite to TFLM
- Optimized Kernel Implementations
- New Platform Support
- Platform/IP support
- Software Emulation with Renode
- Software Emulation with QEMU
- Python Dev Guide
- Automatically Generated Files
- Python Interpreter Guide