Main Content

coder.getDeepLearningLayers

Get the list of layers supported for code generation for a specific deep learning library

所有的页面崩溃

Syntax

coder.getDeepLearningLayers
coder.getDeepLearningLayers(TargetLibrary = libraryname)

Description

coder.getDeepLearningLayersreturns the layers supported for code generation that do not use any third-party libraries.

example

coder.getDeepLearningLayers(TargetLibrary =libraryname)returns the layers supported for code generation for a specific deep learning library.

Note

To usecoder.getDeepLearningLayers, you must install the support package that corresponds tolibraryname:

  • For'none','arm-compute','cmsis-nn', and'mkldnn', installMATLAB®Coder™ Interface for Deep Learning Libraries.

  • For'cudnn','tensorrt', or'arm-compute-mali', installGPU Coder™ Interface for Deep Learning Libraries.

Note

Thecoder.getDeepLearningLayersfunction does not list certain custom layers if the associated support packages are not installed. For example,keras层没有列出如果Deep Learning Toolbox™ Converter for TensorFlow™ Modelssupport package is not installed.

Examples

collapse all

Get a list of layers supported for code generation for Intel®Math Kernel Library for Deep Neural Networks.

coder.getDeepLearningLayers(TargetLibrary ='mkldnn')
ans = 59×1 cell array {'AdditionLayer' } {'AnchorBoxLayer' } {'AveragePooling2DLayer' } {'BatchNormalizationLayer' } {'BiLSTMLayer' } {'ClassificationOutputLayer' } {'ClippedReLULayer' } {'ConcatenationLayer' } {'Convolution2DLayer' } {'Crop2DLayer' } {'CrossChannelNormalizationLayer' } {'DepthConcatenationLayer' } {'DepthToSpace2DLayer' } {'DicePixelClassificationLayer' } {'DropoutLayer' } {'ELULayer' } {'FeatureInputLayer' } {'FlattenLayer' } {'FocalLossLayer' } {'FullyConnectedLayer' } {'GRULayer' } {'GlobalAveragePooling2DLayer' } {'GlobalMaxPooling2DLayer' } {'GroupedConvolution2DLayer' } {'ImageInputLayer' } {'LSTMLayer' } {'LeakyReLULayer' } {'MaxPooling2DLayer' } {'MaxUnpooling2DLayer' } {'MultiplicationLayer' } {'PixelClassificationLayer' } {'RCNNBoxRegressionLayer' } {'RPNClassificationLayer' } {'ReLULayer' } {'RegressionOutputLayer' } {'Resize2DLayer' } {'SSDMergeLayer' } {'SequenceFoldingLayer' } {'SequenceInputLayer' } {'SequenceUnfoldingLayer' } {'SigmoidLayer' } {'SoftmaxLayer' } {'SpaceToDepthLayer' } {'TanhLayer' } {'TransposedConvolution2DLayer' } {'WordEmbeddingLayer' } {'YOLOv2OutputLayer' } {'YOLOv2ReorgLayer' } {'YOLOv2TransformLayer' } {'nnet.keras.layer.FlattenCStyleLayer' } {'nnet.keras.layer.GlobalAveragePooling2dLayer'} {'nnet.keras.layer.SigmoidLayer' } {'nnet.keras.layer.TanhLayer' } {'nnet.keras.layer.ZeroPadding2dLayer' } {'nnet.onnx.layer.ElementwiseAffineLayer' } {'nnet.onnx.layer.FlattenLayer' } {'nnet.onnx.layer.IdentityLayer' } {'ScalingLayer' } {'SoftplusLayer' }

Input Arguments

collapse all

Name of deep learning library, specified as one of the values in this table.

Value Description
'arm-compute'

ARM®Compute Library for targeting ARM CPU processors.

Requires theMATLAB Coder Interface for Deep Learning Libraries.
'arm-compute-mali'

ARM Compute Library for targeting ARM GPU processors.

Requires the GPU Coder product and theGPU Coder Interface for Deep Learning Libraries.
'cmsis-nn'

Common Microcontroller Software Interface Standard - Neural Network (CMSIS-NN) library.

Requires theMATLAB Coder Interface for Deep Learning Libraries.
'cudnn'

NVIDIA®CUDA®Deep Neural Network library (cuDNN).

Requires the GPU Coder product and theGPU Coder Interface for Deep Learning Libraries.
'mkldnn'

Intel Math Kernel Library for Deep Neural Networks.

Requires theMATLAB Coder Interface for Deep Learning Libraries.
'none'

coder.getDeepLearningLayers(TargetLibrary = 'none')returns the layers supported for code generation that do not use any third-party libraries. This is equivalent to callingcoder.getDeepLearningLayerswith no input argument.

Requires theMATLAB Coder Interface for Deep Learning Libraries.
'tensorrt'

NVIDIA TensorRT™ high performance deep learning inference optimizer and run-time library.

Requires the GPU Coder product and theGPU Coder Interface for Deep Learning Libraries.

Version History

Introduced in R2018b

See Also

Functions

Topics