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diff --git a/docs/06_01_parsers.dox b/docs/06_01_parsers.dox new file mode 100644 index 0000000000..186ed6193a --- /dev/null +++ b/docs/06_01_parsers.dox @@ -0,0 +1,206 @@ +/// Copyright (c) 2021 ARM Limited and Contributors. All rights reserved. +/// +/// SPDX-License-Identifier: MIT +/// + +namespace armnn +{ +/** +@page parsers Parsers + +@tableofcontents +Execute models from different machine learning platforms efficiently with our parsers. Simply choose a parser according +to the model you want to run e.g. If you've got a model in onnx format (<model_name>.onnx) use our onnx-parser. + +If you would like to run a Tensorflow Lite (TfLite) model you probably also want to take a look at our @ref delegate. + +All parsers are written in C++ but it is also possible to use them in python. For more information on our python +bindings take a look into the @ref md_python_pyarmnn_README section. + +<br/><br/> + + + + +@section S5_onnx_parser Arm NN Onnx Parser + +`armnnOnnxParser` is a library for loading neural networks defined in ONNX protobuf files into the Arm NN runtime. + +## ONNX operators that the Arm NN SDK supports + +This reference guide provides a list of ONNX operators the Arm NN SDK currently supports. + +The Arm NN SDK ONNX parser currently only supports fp32 operators. + +### Fully supported + +- Add + - See the ONNX [Add documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Add) for more information + +- AveragePool + - See the ONNX [AveragePool documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#AveragePool) for more information. + +- Concat + - See the ONNX [Concat documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Concat) for more information. + +- Constant + - See the ONNX [Constant documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Constant) for more information. + +- Clip + - See the ONNX [Clip documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Clip) for more information. + +- Flatten + - See the ONNX [Flatten documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Flatten) for more information. + +- Gather + - See the ONNX [Gather documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Gather) for more information. + +- GlobalAveragePool + - See the ONNX [GlobalAveragePool documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#GlobalAveragePool) for more information. + +- LeakyRelu + - See the ONNX [LeakyRelu documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#LeakyRelu) for more information. + +- MaxPool + - See the ONNX [max_pool documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#MaxPool) for more information. + +- Relu + - See the ONNX [Relu documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Relu) for more information. + +- Reshape + - See the ONNX [Reshape documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Reshape) for more information. + +- Shape + - See the ONNX [Shape documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Shape) for more information. + +- Sigmoid + - See the ONNX [Sigmoid documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Sigmoid) for more information. + +- Tanh + - See the ONNX [Tanh documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Tanh) for more information. + +- Unsqueeze + - See the ONNX [Unsqueeze documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Unsqueeze) for more information. + +### Partially supported + +- Conv + - The parser only supports 2D convolutions with a group = 1 or group = #Nb_of_channel (depthwise convolution) +- BatchNormalization + - The parser does not support training mode. See the ONNX [BatchNormalization documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#BatchNormalization) for more information. +- Gemm + - The parser only supports constant bias or non-constant bias where bias dimension = 1. See the ONNX [Gemm documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Gemm) for more information. +- MatMul + - The parser only supports constant weights in a fully connected layer. + +## Tested networks + +Arm tested these operators with the following ONNX fp32 neural networks: +- Mobilenet_v2. See the ONNX [MobileNet documentation](https://github.com/onnx/models/tree/master/vision/classification/mobilenet) for more information. +- Simple MNIST. This is no longer directly documented by ONNX. The model and test data may be downloaded [from the ONNX model zoo](https://onnxzoo.blob.core.windows.net/models/opset_8/mnist/mnist.tar.gz). + +More machine learning operators will be supported in future releases. +<br/><br/><br/><br/> + + + + +@section S6_tf_lite_parser Arm NN Tf Lite Parser + +`armnnTfLiteParser` is a library for loading neural networks defined by TensorFlow Lite FlatBuffers files +into the Arm NN runtime. + +## TensorFlow Lite operators that the Arm NN SDK supports + +This reference guide provides a list of TensorFlow Lite operators the Arm NN SDK currently supports. + +### Fully supported +The Arm NN SDK TensorFlow Lite parser currently supports the following operators: + +- ABS +- ADD +- ARG_MAX +- ARG_MIN +- AVERAGE_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE +- BATCH_TO_SPACE +- CONCATENATION, Supported Fused Activation: RELU , RELU6 , TANH, NONE +- CONV_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE +- CONV_3D, Supported Fused Activation: RELU , RELU6 , TANH, NONE +- DEPTH_TO_SPACE +- DEPTHWISE_CONV_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE +- DEQUANTIZE +- DIV +- ELU +- EQUAL +- EXP +- EXPAND_DIMS +- FULLY_CONNECTED, Supported Fused Activation: RELU , RELU6 , TANH, NONE +- GATHER +- GREATER +- GREATER_EQUAL +- HARD_SWISH +- LEAKY_RELU +- LESS +- LESS_EQUAL +- LOGICAL_NOT +- LOGISTIC +- L2_NORMALIZATION +- MAX_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE +- MAXIMUM +- MEAN +- MINIMUM +- MIRROR_PAD +- MUL +- NEG +- NOT_EQUAL +- PACK +- PAD +- PRELU +- QUANTIZE +- RELU +- RELU6 +- REDUCE_MAX +- REDUCE_MIN +- RESHAPE +- RESIZE_BILINEAR +- RESIZE_NEAREST_NEIGHBOR +- RSQRT +- SHAPE +- SLICE +- SOFTMAX +- SPACE_TO_BATCH +- SPLIT +- SPLIT_V +- SQUEEZE +- STRIDED_SLICE +- SUB +- SUM +- TANH +- TRANSPOSE +- TRANSPOSE_CONV +- UNPACK + +### Custom Operator +- TFLite_Detection_PostProcess + +## Tested networks +Arm tested these operators with the following TensorFlow Lite neural network: +- [Quantized MobileNet](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224_quant.tgz) +- [Quantized SSD MobileNet](http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_quantized_300x300_coco14_sync_2018_07_18.tar.gz) +- DeepSpeech v1 converted from [TensorFlow model](https://github.com/mozilla/DeepSpeech/releases/tag/v0.4.1) +- DeepSpeaker +- [DeepLab v3+](https://www.tensorflow.org/lite/models/segmentation/overview) +- FSRCNN +- EfficientNet-lite +- RDN converted from [TensorFlow model](https://github.com/hengchuan/RDN-TensorFlow) +- Quantized RDN (CpuRef) +- [Quantized Inception v3](http://download.tensorflow.org/models/tflite_11_05_08/inception_v3_quant.tgz) +- [Quantized Inception v4](http://download.tensorflow.org/models/inception_v4_299_quant_20181026.tgz) (CpuRef) +- Quantized ResNet v2 50 (CpuRef) +- Quantized Yolo v3 (CpuRef) + +More machine learning operators will be supported in future releases. + +**/ +} + |