Deep Learning withMATLAB编码器

生成深度学习神经网络的C ++代码（需要深度学习工具箱™）

深度学习是机器学习的一个分支，它教会计算机去做人类自然而然的事情：从经验中学习。学习算法使用计算方法直接从数据中“学习”信息，而无需依赖预定方程作为模型。深度学习使用卷积神经网络（CNN）直接从图像中学习有用的数据表示。

您可以使用MATLAB^®CODER™with Deep Learning Toolbox to generate C++ code from a trained CNN. You can then deploy the generated code to an embedded platform that uses an Intel^®或手臂^®processor. You can also generate generic C or C++ code from a trained CNN that does not depend on any third-party libraries.

Deep Learning withMATLAB编码器不支持金宝appMATLABOnline™.

Functions

`代码gen`	从中生成C/C ++代码MATLAB代码
`代码r.loadDeepLearningNetwork`	加载深度学习网络模型
`coder.deeplearningconfig`	创建深度学习代码生成配置对象
`代码r.ARMNEONConfig`	Parameters to configure deep learning code generation with theARMCompute Library
`代码r.CMSISNNConfig`	Parameters to configure deep learning code generation with the CMSIS-NN library for Cortex-M targets
`代码r.MklDNNConfig`	Parameters to configure deep learning code generation with theIntelMath Kernel Library for Deep Neural Networks
`Coder.getDeeplearninglayers`	获取为特定深度学习库的代码生成支持的层列表金宝app
`Coder.RegeneratedEeplearningningParameters`	Regenerate files containing network learnables and states parameters

Topics

与MATLAB编码器进行深度学习的先决条件
Install products and configure environment for code generation for deep learning networks.
Workflow for Deep Learning Code Generation with MATLAB Coder
Generate code for prediction from a pretrained network.
Networks and Layers Supported for Code Generation
选择一个为您的目标处理器支持的卷积神经网络。金宝app
Code Generation for dlarray
Use deep learning arrays in MATLAB code intended for code generation.
代码生成的dlarray限制
Adhere to code generation limitations for deep learning arrays.
Load Pretrained Networks for Code Generation
Create aSeriesNetwork,DAGNetwork,yolov2ObjectDetector,ssdObjectDetector, ordlnetworkobject for code generation.
Generate Generic C/C++ Code for Deep Learning Networks
Generate C/C++ code for prediction from a deep learning network that does not depend on any third-party libraries.
使用MKL-DNN的深度学习网络代码生成
从深度学习网络中生成用于预测的C ++代码，以Intel CPU为目标。
使用ARM计算库的深度学习网络代码生成
从深度学习网络中生成C ++代码，以针对ARM处理器进行预测。
使用ARM Compute库的跨编译深度学习代码
在主机计算机上生成库或可执行代码，以在ARM硬件目标上部署。
生成深度学习网络的INT8代码
Quantize and generate code for a pretrained convolutional neural network.
代码后更新网络参数
Perform post code generation updates of deep learning network parameters.