| commit | e7a86a4a3363993fb41b1ea62f23b3643b8b0c78 | [log] [tgz] |
|---|---|---|
| author | Francis Murtagh <francis.murtagh@arm.com> | Wed Aug 29 12:42:10 2018 +0100 |
| committer | Matthew Bentham <matthew.bentham@arm.com> | Mon Sep 17 17:21:23 2018 +0100 |
| tree | 6d054cae92a13412129525e4f9ea441e7d8c6b73 | |
| parent | a68241066c3e797dab70f515d2c55aaa74abf564 [diff] |
IVGCVSW-1200 Division layer *IVGCVSW-1772 Create QueueDescriptors *IVGCVSW-1773 Add a CL implementation of the DivisionWorkload *IVGCVSW-1774 Add Neon implementation of the DivisionWorkload *IVGCVSW-1775 Add a Ref implementation of the DivisionWorkload *IVGCVSW-1776 Add a Division Layer * Added simple division unit tests with broadcasting Change-Id: I05751fb7f868789f6c06f91e8d25e52b4f12ab5e
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: TensorFlow Lite Support
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: ONNX Support
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.