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review.mlplatform.org / ml / armnn / d5b9e6497b03d58c671c15b9ebe8e35500171f06
commitd5b9e6497b03d58c671c15b9ebe8e35500171f06[log] [tgz]
authorMatteo Martincigh <matteo.martincigh@arm.com>Fri Jan 04 18:01:21 2019 +0000
committerMatteo Martincigh <matteo.martincigh@arm.com>Mon Jan 07 11:25:42 2019 +0000
treebf1e995d1b88f75cf497e8fd5f52f5003272187e
parent2ad6cb486164ff3aabe4e9ecabc47f08da48da35 [diff]
IVGCVSW-2421 Remove the template-based version of armnnUtils::Permute
in favor of a type-indepent implementation that takes void-pointers

 * The new implementation requires the size of the type to be passed
   to the function
 * Updated all the usages accordingly
 * Removed the old implementation no longer used

!android-nn-driver:469

Change-Id: I37f4e6d62a38fbb8ec8c39bb559a2c54c83365d4
10 files changed
tree: bf1e995d1b88f75cf497e8fd5f52f5003272187e
  1. Android.bp
  2. Android.mk
  3. BuildGuideAndroidNDK.md
  4. BuildGuideCrossCompilation.md
  5. CMakeLists.txt
  6. ContributorGuide.md
  7. LICENSE
  8. README.md
  9. cmake/
  10. docs/
  11. include/
  12. samples/
  13. scripts/
  14. src/
  15. tests/
  16. third-party/
README.md

Arm NN

For more information about Arm NN, see: https://developer.arm.com/products/processors/machine-learning/arm-nn

There is a getting started guide here using TensorFlow: https://developer.arm.com/technologies/machine-learning-on-arm/developer-material/how-to-guides/configuring-the-arm-nn-sdk-build-environment-for-tensorflow

There is a getting started guide here using TensorFlow Lite: https://developer.arm.com/technologies/machine-learning-on-arm/developer-material/how-to-guides/configuring-the-arm-nn-sdk-build-environment-for-tensorflow-lite

There is a getting started guide here using Caffe: https://developer.arm.com/technologies/machine-learning-on-arm/developer-material/how-to-guides/configuring-the-arm-nn-sdk-build-environment-for-caffe

There is a getting started guide here using ONNX: https://developer.arm.com/technologies/machine-learning-on-arm/developer-material/how-to-guides/configuring-the-arm-nn-sdk-build-environment-for-onnx

There is a guide for backend development: Backend development guide

Build Instructions

Arm tests the build system of Arm NN with the following build environments:

Arm NN is written using portable C++14 and the build system uses CMake so it is possible to build for a wide variety of target platforms, from a wide variety of host environments.

The armnn/tests directory contains tests used during ArmNN development. Many of them depend on third-party IP, model protobufs and image files not distributed with ArmNN. The dependencies of some of the tests are available freely on the Internet, for those who wish to experiment.

The 'ExecuteNetwork' program, in armnn/tests/ExecuteNetwork, has no additional dependencies beyond those required by ArmNN and the model parsers. It takes any model and any input tensor, and simply prints out the output tensor. Run with no arguments to see command-line help.

The 'armnn/samples' directory contains SimpleSample.cpp. A very basic example of the ArmNN SDK API in use.

Note that Arm NN needs to be built against a particular version of ARM's Compute Library. The get_compute_library.sh in the scripts subdirectory will clone the compute library from the review.mlplatform.org github repository into a directory alongside armnn named 'clframework' and checkouts the correct revision

License

Arm NN is provided under the MIT license. See LICENSE for more information. Contributions to this project are accepted under the same license.

Individual files contain the following tag instead of the full license text.

SPDX-License-Identifier: MIT

This enables machine processing of license information based on the SPDX License Identifiers that are available here: http://spdx.org/licenses/

Contributions

The ArmNN project welcomes contributions. Please see the Contributor Guide for more details.