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178 lines
2.9 KiB
Plaintext
178 lines
2.9 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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@page delegate TfLite Delegate
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@tableofcontents
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@section delegateintro About the delegate
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'armnnDelegate' is a library for accelerating certain TensorFlow Lite (TfLite) operators on Arm hardware. It can be
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integrated in TfLite using its delegation mechanism. TfLite will then delegate the execution of operators supported by
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Arm NN to Arm NN.
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The main difference to our @ref S6_tf_lite_parser is the amount of operators you can run with it. If none of the active
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backends support an operation in your model you won't be able to execute it with our parser. In contrast to that, TfLite
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only delegates operations to the armnnDelegate if it does support them and otherwise executes them itself. In other
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words, every TfLite model can be executed and every operation in your model that we can accelerate will be accelerated.
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That is the reason why the armnnDelegate is our recommended way to accelerate TfLite models.
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If you need help building the armnnDelegate, please take a look at our [build guide](delegate/BuildGuideNative.md).
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An example how to setup TfLite to integrate the armnnDelegate can be found in this
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guide: [Integrate the delegate into python](delegate/IntegrateDelegateIntoPython.md)
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@section delegatesupport Supported Operators
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This reference guide provides a list of TensorFlow Lite operators the Arm NN SDK currently supports.
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@subsection delegatefullysupported Fully supported
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The Arm NN SDK TensorFlow Lite delegate currently supports the following operators:
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- ABS
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- ADD
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- ARGMAX
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- ARGMIN
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- AVERAGE_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE
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- BATCH_TO_SPACE_ND
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- CAST
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- CONCATENATION, Supported Fused Activation: RELU , RELU6 , TANH, NONE
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- CONV_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE
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- CONV_3D, Supported Fused Activation: RELU , RELU6 , TANH, NONE
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- DEPTH_TO_SPACE
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- DEPTHWISE_CONV_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE
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- DEQUANTIZE
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- DIV
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- EQUAL
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- ELU
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- EXP
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- FULLY_CONNECTED, Supported Fused Activation: RELU , RELU6 , TANH, NONE
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- FLOOR
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- GATHER
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- GREATER
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- GREATER_OR_EQUAL
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- HARD_SWISH
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- LESS
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- LESS_OR_EQUAL
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- LOCAL_RESPONSE_NORMALIZATION
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- LOGICAL_AND
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- LOGICAL_NOT
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- LOGICAL_OR
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- LOGISTIC
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- LOG_SOFTMAX
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- LSTM
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- L2_NORMALIZATION
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- L2_POOL_2D
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- MAXIMUM
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- MAX_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE
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- MEAN
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- MINIMUM
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- MIRROR_PAD
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- MUL
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- NEG
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- NOT_EQUAL
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- PACK
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- PAD
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- PRELU
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- QUANTIZE
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- RANK
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- REDUCE_MAX
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- REDUCE_MIN
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- RESHAPE
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- RESIZE_BILINEAR
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- RESIZE_NEAREST_NEIGHBOR
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- RELU
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- RELU6
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- RSQRT
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- SHAPE
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- SOFTMAX
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- SPACE_TO_BATCH_ND
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- SPACE_TO_DEPTH
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- SPLIT
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- SPLIT_V
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- SQRT
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- STRIDED_SLICE
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- SUB
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- SUM
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- TANH
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- TRANSPOSE
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- TRANSPOSE_CONV
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- UNIDIRECTIONAL_SEQUENCE_LSTM
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- UNPACK
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More machine learning operators will be supported in future releases.
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**/
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} |