mirror of https://github.com/vee1e/tflite-micro - Infrastructure to enable deployment of ML models to low-powe
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Ryan Kuester bbf70db499
feat(compression): add SpecBuilder for programmatic compression specs (#3133)
Add a fluent builder API for creating compression specifications
without writing YAML strings. This is useful in scripts and
Jupyter notebooks.

Example usage:
    spec = (compression.SpecBuilder()
        .add_tensor(subgraph=0, tensor=2)
            .with_lut(index_bitwidth=4)
        .build())

BUG=#3125

Co-authored-by: suleshahid <110432064+suleshahid@users.noreply.github.com>
2025-07-10 16:32:57 -04:00
.github ci(Make): add test jobs for compression (#2988) 2024-12-06 00:55:36 +00:00
ci CI changes for REVERSE_V2 Operator (#3121) 2025-06-16 16:54:27 +00:00
codegen Remove deprecated BUILD tags (#3091) 2025-04-08 19:21:25 +00:00
data/continuous_builds
docs
python feat(compression): add SpecBuilder for programmatic compression specs (#3133) 2025-07-10 16:32:57 -04:00
signal build(bazel): introduce tflm_cc_* macros, refactoring away micro_copts (#2765) 2024-11-14 23:16:28 +00:00
tensorflow feat(compression): add SpecBuilder for programmatic compression specs (#3133) 2025-07-10 16:32:57 -04:00
third_party test(compression): remove the test log hexdump of the Python metadata (#2941) 2024-11-27 00:12:18 +00:00
tools Add expand_stamp_vars docstring and fix import (#2178) 2023-08-21 16:53:10 +00:00
.bazelrc build(bazel): provide means of excluding whl_test locally (#2940) 2024-11-27 00:51:53 +00:00
.bazelversion build(bazel): pin bazel version to 7.0.0 (#2360) 2024-01-03 20:53:21 +00:00
.clang-format
.editorconfig
.gitignore
.style.yapf style: add .style.yapf to control yapf styling of Python code (#2709) 2024-10-02 18:36:01 +00:00
AUTHORS
BUILD build(bazel): add --//:with_compression build setting (#2843) 2024-11-20 14:01:21 -08:00
CODEOWNERS Replace rascani with suleshahid on OWNERS (#2715) 2024-10-07 17:36:26 +00:00
CONTRIBUTING.md style: add .style.yapf to control yapf styling of Python code (#2709) 2024-10-02 18:36:01 +00:00
debugging_output.md Adding ReadMe for Layer by Layer Debug Targets (#2305) 2023-11-28 22:06:25 +00:00
LICENSE
README.md
SECURITY.md
WORKSPACE build(bazel): add integrity check to nnlib_hifi4 download (#2743) 2024-11-01 22:10:05 +00:00

TensorFlow Lite for Microcontrollers

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 Status

Official Builds

Build Type Status
CI (Linux) CI
Code Sync Sync from Upstream TF

Community Supported TFLM Examples

This table captures platforms that TFLM has been ported to. Please see New Platform Support for additional documentation.

Platform Status
Arduino Arduino Antmicro
Coral Dev Board Micro TFLM + EdgeTPU Examples for Coral Dev Board Micro
Espressif Systems Dev Boards ESP Dev Boards
Renesas Boards TFLM Examples for Renesas Boards
Silicon Labs Dev Kits TFLM Examples for Silicon Labs Dev Kits
Sparkfun Edge Sparkfun Edge
Texas Instruments Dev Boards Texas Instruments Dev Boards

Community Supported Kernels and Unit Tests

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 Cortex-M
Hexagon Hexagon
RISC-V RISC-V
Xtensa Xtensa
Generate Integration Test Generate Integration Test

Contributing

See our contribution documentation.

Getting Help

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:

  1. SIG Micro email group and monthly meetings.

  2. SIG Micro gitter chat room.

  3. For questions that are not specific to TFLM, please consult the broader TensorFlow project, e.g.:

Additional Documentation

RFCs

  1. Pre-allocated tensors
  2. TensorFlow Lite for Microcontrollers Port of 16x8 Quantized Operators