深度学习代码生成基础知识

可用于为深度学习网络生成代码的函数、对象和工作流

您可以将 MATLAB^® Coder™ 与 Deep Learning Toolbox™ 结合使用，从经过训练的 CNN 生成 C++ 代码。然后您可以将生成的代码部署到使用 Intel^® 或 ARM^® 处理器的嵌入式平台。您还可以从不依赖任何第三方库的经过训练的 CNN 生成泛型 C 或 C++ 代码。

函数

`codegen`	从 MATLAB 代码生成 C/C++ 代码。
`coder.loadDeepLearningNetwork`	Load deep learning network model
`coder.DeepLearningConfig`	Create deep learning code generation configuration objects
`coder.DeepLearningCodeConfig`	Parameters to configure deep learning code generation that does not depend on third-party libraries (自 R2021a 起)
`coder.ARMNEONConfig`	Parameters to configure deep learning code generation with the ARM Compute Library
`coder.CMSISNNConfig`	Parameters to configure deep learning code generation with the CMSIS-NN library for Cortex-M targets (自 R2022a 起)
`coder.MklDNNConfig`	Parameters to configure deep learning code generation with the Intel Math Kernel Library for Deep Neural Networks
`analyzeNetworkForCodegen`	Analyze deep learning network for code generation (自 R2022b 起)
`coder.regenerateDeepLearningParameters`	Regenerate files containing network learnables and states parameters (自 R2021b 起)

主题

使用 MATLAB Coder 进行深度学习的前提条件
为用于深度学习网络的代码生成安装相关产品并配置环境。
使用 MATLAB Coder 生成深度学习代码的工作流
根据预训练网络生成用于预测的代码。
代码生成支持的网络和层
选择目标处理器支持的卷积神经网络。
Analyze Network for Code Generation
Check code generation compatibility of a deep learning network.
Code Generation for dlarray
Use deep learning arrays in MATLAB code intended for code generation.
dlarray Limitations for Code Generation
Adhere to code generation limitations for deep learning arrays.
加载预训练网络以用于代码生成
创建 SeriesNetwork、DAGNetwork、yolov2ObjectDetector、ssdObjectDetector 或 dlnetwork 对象以用于代码生成。
为深度学习网络生成泛型 C/C++ 代码
从不依赖任何第三方库的深度学习网络中生成用于预测的 C/C++ 代码。
Optimize C/C++ Code Performance for Deep Learning Applications without Deep Learning Libraries
Code generation configuration settings that optimize the performance of the generated C/C++ code for a deep learning network.
Code Generation for Deep Learning Networks with MKL-DNN
Generate C++ code for prediction from a deep learning network, targeting an Intel CPU.
Code Generation for Deep Learning Networks with ARM Compute Library
Generate C++ code for prediction from a deep learning network, targeting an ARM processor.
Cross-Compile Deep Learning Code That Uses ARM Compute Library
Generate library or executable code on host computer for deployment on ARM hardware target.
Generate int8 Code for Deep Learning Networks
Quantize and generate code for a pretrained convolutional neural network.
Generate bfloat16 Code for Deep Learning Networks
Perform learnables compression and generate C/C++ code in Brain Floating Point format, bfloat16.
Update Network Parameters After Code Generation
Perform post code generation updates of deep learning network parameters.

精选示例

Generate Digit Images Using Variational Autoencoder on Intel CPUs

Generate code for a trained VAE dlnetwork to generate hand-drawn digits.

打开实时脚本

Cross Compile Deep Learning Code for ARM Neon Targets

Generate library or executable code on host computer for deployment on ARM hardware target.

打开实时脚本

Post-Code-Generation Update of Deep Learning Network Parameters

Incrementally update the network learnables of a deep learning network application running on edge devices such as Raspberry Pi. This example uses a cart-pole reinforcement learning application to illustrate:

打开实时脚本

深度学习代码生成基础知识

函数

主题

相关信息

精选示例

Generate Digit Images Using Variational Autoencoder on Intel CPUs

Cross Compile Deep Learning Code for ARM Neon Targets

Post-Code-Generation Update of Deep Learning Network Parameters

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