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diff --git a/docs/01_01_parsers.dox b/docs/01_01_parsers.dox index 6607921585..af87eba7af 100644 --- a/docs/01_01_parsers.dox +++ b/docs/01_01_parsers.dox @@ -10,67 +10,14 @@ namespace armnn @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 tensorflow format (<model_name>.pb) use our tensorflow-parser. +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. - - -@section S4_caffe_parser Arm NN Caffe Parser - -`armnnCaffeParser` is a library for loading neural networks defined in Caffe protobuf files into the Arm NN runtime. - -Please note that certain deprecated Caffe features are not supported by the armnnCaffeParser. If you think that Arm NN -should be able to load your model according to the list of supported layers, but you are getting strange error -messages, then try upgrading your model to the latest format using Caffe, either by saving it to a new file or using -the upgrade utilities in `caffe/tools`. - -\b NOTE: The Arm NN Caffe Parser is deprecated in Arm NN 21.02 and will be removed in 21.05. - -## Caffe layers supported by the Arm NN SDK -This reference guide provides a list of Caffe layers the Arm NN SDK currently supports. - -### Although some other neural networks might work, Arm tests the Arm NN SDK with Caffe implementations of the following neural networks: - -- AlexNet. -- Cifar10. -- Inception-BN. -- Resnet_50, Resnet_101 and Resnet_152. -- VGG_CNN_S, VGG_16 and VGG_19. -- Yolov1_tiny. -- Lenet. -- MobileNetv1. -- SqueezeNet v1.0 and SqueezeNet v1.1 - -### The Arm NN SDK supports the following machine learning layers for Caffe networks: - -- Argmax, excluding the top_k and out_max_val parameters. -- BatchNorm, in inference mode. -- Convolution, excluding Weight Filler, Bias Filler, Engine, Force nd_im2col, and Axis parameters. -- Deconvolution, excluding the Dilation Size, Weight Filler, Bias Filler, Engine, Force nd_im2col, and Axis parameters. - - Caffe doesn't support depthwise convolution, the equivalent layer is implemented through the notion of groups. ArmNN supports groups this way: - - when group=1, it is a normal conv2d - - when group=#input_channels, we can replace it by a depthwise convolution - - when group>1 && group<#input_channels, we need to split the input into the given number of groups, apply a separate convolution and then merge the results -- Concat, along the channel dimension only. -- Dropout, in inference mode. -- Eltwise, excluding the coeff parameter. -- Inner Product, excluding the Weight Filler, Bias Filler, Engine, and Axis parameters. -- Input. -- LRN, excluding the Engine parameter. -- Pooling, excluding the Stochastic Pooling and Engine parameters. -- ReLU. -- Scale. -- Softmax, excluding the Axis and Engine parameters. -- Split. - -More machine learning layers will be supported in future releases. - -<br/><br/><br/><br/> +<br/><br/> @@ -229,125 +176,6 @@ Arm tested these operators with the following TensorFlow Lite neural network: - Quantized Yolo v3 (CpuRef) More machine learning operators will be supported in future releases. -<br/><br/><br/><br/> - - - - -@section S7_tf_parser ArmNN Tensorflow Parser - -`armnnTfParser` is a library for loading neural networks defined by TensorFlow protobuf files into the Arm NN runtime. - -\b NOTE: The Arm NN Tensorflow Parser is deprecated in Arm NN 21.02 and will be removed in 21.05. - -## TensorFlow operators that the Arm NN SDK supports - -This reference guide provides a list of TensorFlow operators the Arm NN SDK currently supports. - -The Arm NN SDK TensorFlow parser currently only supports fp32 operators. - -### Fully supported - -- avg_pool - - See the TensorFlow [avg_pool documentation](https://www.tensorflow.org/api_docs/python/tf/nn/avg_pool) for more information. -- bias_add - - See the TensorFlow [bias_add documentation](https://www.tensorflow.org/api_docs/python/tf/nn/bias_add) for more information. -- conv2d - - See the TensorFlow [conv2d documentation](https://www.tensorflow.org/api_docs/python/tf/nn/conv2d) for more information. -- expand_dims - - See the TensorFlow [expand_dims documentation](https://www.tensorflow.org/api_docs/python/tf/expand_dims) for more information. -- gather - - See the TensorFlow [gather documentation](https://www.tensorflow.org/api_docs/python/tf/gather) for more information. -- identity - - See the TensorFlow [identity documentation](https://www.tensorflow.org/api_docs/python/tf/identity) for more information. -- local_response_normalization - - See the TensorFlow [local_response_normalization documentation](https://www.tensorflow.org/api_docs/python/tf/nn/local_response_normalization) for more information. -- max_pool - - See the TensorFlow [max_pool documentation](https://www.tensorflow.org/api_docs/python/tf/nn/max_pool) for more information. -- placeholder - - See the TensorFlow [placeholder documentation](https://www.tensorflow.org/api_docs/python/tf/placeholder) for more information. -- reduce_mean - - See the TensorFlow [reduce_mean documentation](https://www.tensorflow.org/api_docs/python/tf/reduce_mean) for more information. -- relu - - See the TensorFlow [relu documentation](https://www.tensorflow.org/api_docs/python/tf/nn/relu) for more information. -- relu6 - - See the TensorFlow [relu6 documentation](https://www.tensorflow.org/api_docs/python/tf/nn/relu6) for more information. -- rsqrt - - See the TensorFlow [rsqrt documentation](https://www.tensorflow.org/api_docs/python/tf/math/rsqrt) for more information. -- shape - - See the TensorFlow [shape documentation](https://www.tensorflow.org/api_docs/python/tf/shape) for more information. -- sigmoid - - See the TensorFlow [sigmoid documentation](https://www.tensorflow.org/api_docs/python/tf/sigmoid) for more information. -- softplus - - See the TensorFlow [softplus documentation](https://www.tensorflow.org/api_docs/python/tf/nn/softplus) for more information. -- squeeze - - See the TensorFlow [squeeze documentation](https://www.tensorflow.org/api_docs/python/tf/squeeze) for more information. -- tanh - - See the TensorFlow [tanh documentation](https://www.tensorflow.org/api_docs/python/tf/tanh) for more information. -- transpose - - See the TensorFlow [transpose documentation](https://www.tensorflow.org/api_docs/python/tf/transpose) for more information. - -### Partially supported - -- add - - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of scalars and 1D tensors. See the TensorFlow [add operator documentation](https://www.tensorflow.org/api_docs/python/tf/add) for more information. -- add_n - - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of scalars and 1D tensors. See the TensorFlow [add operator documentation](https://www.tensorflow.org/api_docs/python/tf/add_n) for more information. -- concat - - Arm NN supports concatenation along the channel dimension for data formats NHWC and NCHW. -- constant - - The parser does not support the optional `shape` argument. It always infers the shape of the output tensor from `value`. See the TensorFlow [constant documentation](https://www.tensorflow.org/api_docs/python/tf/constant) for further information. -- depthwise_conv2d_native - - The parser only supports a dilation rate of (1,1,1,1). See the TensorFlow [depthwise_conv2d_native documentation](https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d_native) for more information. -- equal - - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of 4D and 1D tensors. See the TensorFlow [equal operator documentation](https://www.tensorflow.org/api_docs/python/tf/math/equal) for more information. -- fused_batch_norm - - The parser does not support training outputs. See the TensorFlow [fused_batch_norm documentation](https://www.tensorflow.org/api_docs/python/tf/nn/fused_batch_norm) for more information. -- greater - - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of 4D and 1D tensors. See the TensorFlow [greater operator documentation](https://www.tensorflow.org/api_docs/python/tf/math/greater) for more information. -- matmul - - The parser only supports constant weights in a fully connected layer. See the TensorFlow [matmul documentation](https://www.tensorflow.org/api_docs/python/tf/matmul) for more information. -- maximum - where maximum is used in one of the following ways - - max(mul(a, x), x) - - max(mul(x, a), x) - - max(x, mul(a, x)) - - max(x, mul(x, a) - This is interpreted as a ActivationLayer with a LeakyRelu activation function. Any other usage of max will result in the insertion of a simple maximum layer. The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting). See the TensorFlow [maximum documentation](https://www.tensorflow.org/api_docs/python/tf/maximum) for more information. -- minimum - - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of 4D and 1D tensors. See the TensorFlow [minimum operator documentation](https://www.tensorflow.org/api_docs/python/tf/math/minimum) for more information. -- multiply - - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of scalars and 1D tensors. See the TensorFlow [multiply documentation](https://www.tensorflow.org/api_docs/python/tf/multiply) for more information. -- pack/stack - - See the TensorFlow [stack documentation](https://www.tensorflow.org/api_docs/python/tf/stack) for more information. -- pad - - Only supports tf.pad function with mode = 'CONSTANT' and constant_values = 0. See the TensorFlow [pad documentation](https://www.tensorflow.org/api_docs/python/tf/pad) for more information. -- realdiv - - The parser does not support all forms of [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of scalars and 1D tensors. See the TensorFlow [realdiv documentation](https://www.tensorflow.org/api_docs/python/tf/realdiv) for more information. -- reshape - - The parser does not support reshaping to or from 4D. See the TensorFlow [reshape documentation](https://www.tensorflow.org/api_docs/python/tf/reshape) for more information. -- resize_images - - The parser only supports `ResizeMethod.BILINEAR` with `align_corners=False`. See the TensorFlow [resize_images documentation](https://www.tensorflow.org/api_docs/python/tf/image/resize_images) for more information. -- softmax - - The parser only supports 2D inputs and does not support selecting the `softmax` dimension. See the TensorFlow [softmax documentation](https://www.tensorflow.org/api_docs/python/tf/nn/softmax) for more information. -- split - - Arm NN supports split along the channel dimension for data formats NHWC and NCHW. -- strided_slice - - See the TensorFlow [strided_slice documentation](https://www.tensorflow.org/api_docs/python/tf/strided_slice) for more information. -- subtract - - The parser does not support all forms of broadcasting [broadcast composition](https://www.tensorflow.org/performance/xla/broadcasting), only broadcasting of scalars and 1D tensors. See the TensorFlow [subtract documentation](https://www.tensorflow.org/api_docs/python/tf/math/subtract) for more information. - - -## Tested networks - -Arm tests these operators with the following TensorFlow fp32 neural networks: -- Lenet -- mobilenet_v1_1.0_224. The Arm NN SDK only supports the non-quantized version of the network. See the [MobileNet_v1 documentation](https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md) for more information on quantized networks. -- inception_v3. The Arm NN SDK only supports the official inception_v3 transformed model. See the TensorFlow documentation on [preparing models for mobile deployment](https://www.tensorflow.org/mobile/prepare_models) for more information on how to transform the inception_v3 network. -- Simple MNIST. For more information check out the [tutorial](https://developer.arm.com/technologies/machine-learning-on-arm/developer-material/how-to-guides/deploying-a-tensorflow-mnist-model-on-arm-nn) on the Arm Developer portal. -- ResNet v2 50 implementation from the [TF Slim model zoo](https://github.com/tensorflow/models/tree/master/research/slim) - -More machine learning operators will be supported in future releases. **/ } |