forked from Qortal/Brooklyn
50 lines
2.0 KiB
Plaintext
50 lines
2.0 KiB
Plaintext
/// Copyright (c) 2021 ARM Limited and Contributors. All rights reserved.
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///
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/// SPDX-License-Identifier: MIT
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///
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namespace armnn
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{
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/**
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This is a very simple example which uses the Arm NN SDK API to create a neural network which consists of
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nothing else but a single fully connected layer with a single weights value. It's as minimalistic as it can get.
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@note Most of our users won't use our API to create a network manually. Usually you would use one of our software
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tools like the @ref S6_tf_lite_parser "TfLite Parser" that will translate a TfLite model into Arm NN for you.
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Still it's a very nice example to see how an Arm NN network is created, optimized and executed.
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(You can find more complex examples using the TfLite Parser in samples/ObjectDetection and
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samples/SpeechRecognition. And another example using @ref md_python_pyarmnn_README "PyArmnn" in
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samples/ImageClassification)
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@example SimpleSample.cpp
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**/
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/**
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This is simple example that shows how to use a dynamic backend. Dynamic Backends can be compiled as standalone
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against Arm NN and can be loaded by Arm NN dynamically at runtime. This way you can quickly integrate new backends
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without having to worry or recompile Arm NN.
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This example makes use of a very simplistic dynamic backend called 'SampleDynamic'. There is a guide that tells you
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more about dynamic backends and how this particular backend was created so you can create a dynamic backend
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yourself @ref md_src_dynamic_README.
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@example DynamicSample.cpp
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**/
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/**
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This example is basically a copy of the SimpleSample example. But it makes use of a CustomAllocator to allocate
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memory for the inputs, outputs and inter layer memory.
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@note This is currently an experimental interface
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@example CustomMemoryAllocatorSample.cpp
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**/
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/**
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Yet another variant of the SimpleSample application. In this little sample app you will be shown how to run a
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network multiple times asynchronously.
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@note This is currently an experimental interface
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@example AsyncExecutionSample.cpp
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**/
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}
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