| .. | ||
| apollo3evb | ||
| arc_emsdp | ||
| arduino | ||
| benchmarks | ||
| bluepill | ||
| chre | ||
| cortex_m_generic | ||
| docs | ||
| ecm3531 | ||
| examples | ||
| himax_we1_evb | ||
| kernels | ||
| mbed | ||
| memory_planner | ||
| openmvcam | ||
| riscv32_mcu | ||
| sparkfun_edge | ||
| stm32f4 | ||
| stm32f4HAL | ||
| testing | ||
| tools | ||
| xcore | ||
| all_ops_resolver.cc | ||
| all_ops_resolver.h | ||
| BUILD | ||
| build_def.bzl | ||
| compatibility.h | ||
| CONTRIBUTING.md | ||
| debug_log.cc | ||
| debug_log.h | ||
| memory_arena_threshold_test.cc | ||
| memory_helpers_test.cc | ||
| memory_helpers.cc | ||
| memory_helpers.h | ||
| micro_allocator_test.cc | ||
| micro_allocator.cc | ||
| micro_allocator.h | ||
| micro_error_reporter_test.cc | ||
| micro_error_reporter.cc | ||
| micro_error_reporter.h | ||
| micro_interpreter_test.cc | ||
| micro_interpreter.cc | ||
| micro_interpreter.h | ||
| micro_mutable_op_resolver_test.cc | ||
| micro_mutable_op_resolver.h | ||
| micro_op_resolver.h | ||
| micro_profiler.cc | ||
| micro_profiler.h | ||
| micro_string_test.cc | ||
| micro_string.cc | ||
| micro_string.h | ||
| micro_time_test.cc | ||
| micro_time.cc | ||
| micro_time.h | ||
| micro_utils_test.cc | ||
| micro_utils.cc | ||
| micro_utils.h | ||
| README.md | ||
| recording_micro_allocator_test.cc | ||
| recording_micro_allocator.cc | ||
| recording_micro_allocator.h | ||
| recording_micro_interpreter.h | ||
| recording_simple_memory_allocator_test.cc | ||
| recording_simple_memory_allocator.cc | ||
| recording_simple_memory_allocator.h | ||
| simple_memory_allocator_test.cc | ||
| simple_memory_allocator.cc | ||
| simple_memory_allocator.h | ||
| test_helpers.cc | ||
| test_helpers.h | ||
| testing_helpers_test.cc | ||
- TensorFlow Lite for Microcontrollers
- Continuous Build Status
- Getting Help and Involved
- Additional Documentation
TensorFlow Lite for Microcontrollers
TensorFlow Lite for Microcontrollers is a port of TensorFlow Lite designed to run machine learning models on microcontrollers and other devices with only kilobytes of memory.
To learn how to use the framework, visit the developer documentation at tensorflow.org/lite/microcontrollers.
Continuous Build Status
Official Builds
| Build Type | Status | Artifacts |
|---|---|---|
| Linux |  |
Community Supported Builds
| Build Type | Status | Artifacts |
|---|---|---|
| Xtensa |  |
Getting Help and Involved
A TF Lite Micro 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.
If you are interested in contributing code to TensorFlow Lite for Microcontrollers then please read our contributions guide.
Additional Documentation
For developers that are interested in more details of the internals of the project, we have additional documentation in the docs folder.