Premium tier Qualcomm® Snapdragon™ mobile platforms have extensive heterogeneous computing capabilities that are engineered to allow the running of trained neural networks on device without a need for connection to the cloud. The Qualcomm® Snapdragon™ Neural Processing Engine (NPE) SDK is designed to help developers run one or more neural network models trained in Caffe/Caffe2 or TensorFlow on Snapdragon mobile platforms, whether that is the CPU, GPU or DSP.
高级版Qualcomm®Snapdragon™移动平台具有广泛的异构计算功能，旨在允许在设备上运行受过训练的神经网络，而无需连接到云端。 Qualcomm®Snapdragon™神经处理引擎（NPE）SDK旨在帮助开发人员在Snapdragon移动平台上运行Caffe / Caffe2或TensorFlow培训的一个或多个神经网络模型，无论是CPU，GPU还是DSP。
The Snapdragon NPE is engineered to help developers save time and effort in optimizing performance of trained neural networks on devices with Snapdragon. It does this by providing tools for model conversion and execution as well as APIs for targeting the core with the power and performance profile to match the desired user experience. The Snapdragon NPE supports convolutional neural networks and custom layers.
Snapdragon NPE旨在帮助开发人员节省时间和精力来优化使用Snapdragon的设备上训练有素的神经网络的性能。 它通过提供用于模型转换和执行的工具以及针对核心的API，通过功能和性能配置文件来匹配所需的用户体验。 Snapdragon NPE支持卷积神经网络和用户自定义层。
The Snapdragon NPE does a lot of the heavy lifting needed to run neural networks on Snapdragon mobile platforms, which can help provide developers with more time and resources to focus on building new and innovative user experiences.
Snapdragon NPE在Snapdragon移动平台上运行神经网络所需的大量工作，可以帮助开发人员更多的时间和资源，专注于建立新的和创新的用户体验。
If you would like a more in-depth introduction to artificial intelligence and the Neural Processing SDK, we encourage you to view our Snapdragon and Artificial Intelligence at the Edge webinar, which provides an overview of what we have to offer.
如果您想更深入地介绍人工智能和神经处理SDK，我们鼓励您在“边缘”网络研讨会上查看我们的Snapdragon和人工智能，其中概述了我们提供的内容。
What’s in the SDK?（SDK中有什么？）
Android and Linux runtimes for neural network model execution
Android和Linux运行时神经网络模型执行Acceleration support for Qualcomm® Hexagon™ DSPs, Qualcomm® Adreno™ GPUs and Qualcomm® Kryo™, CPUs
加速支持Qualcomm®Hexagon™DSP，Qualcomm®Adreno™GPU和Qualcomm®Kryo™，CPUsSupport for models in Caffe, Caffe2 and TensorFlow formats
支持Caffe，Caffe2和TensorFlow格式的模型APIs for controlling loading, execution and scheduling on the runtimes
用于控制运行时的加载，执行和调度的APIDesktop tools for model conversion
用于模型转换的桌面工具Performance benchmark for bottleneck identification
瓶颈识别的性能基准Sample code and tutorials
示例代码和教程HTML Documentation
HTML文档
To make the AI developer’s life easier, the Snapdragon NPE SDK does not define yet another library of network layers; instead it gives developers the freedom to design and train their networks using familiar frameworks, with Caffe/Caffe2 and TensorFlow being supported at launch. The development workflow is the following:
为了使AI开发人员的生活更轻松，Snapdragon NPE SDK还没有定义另一个网络层库; 相反，它使开发人员可以自由地使用熟悉的框架设计和训练他们的网络，Caffe / Caffe2和TensorFlow在启动时得到支持。 开发工作流程如下：
After designing and training, the model file needs to be converted into a “.dlc” (Deep Learning Container) file to be used by the Snapdragon NPE runtime. The conversion tool will output conversion statistics, including information about unsupported or non-accelerated layers, that the developer can use to adjust the design of the initial model.
在设计和培训之后，模型文件需要转换为“.dlc”（深度学习容器）文件供Snapdragon NPE运行时使用。 转换工具将输出转换统计信息，包括有关不受支持或非加速层的信息，开发人员可以使用这些信息来调整初始模型的设计。
Is the Snapdragon NPE SDK Right for You?（Snapdragon NPE SDK是否适合您？）
Developing for artificial intelligence using the Snapdragon NPE SDK does require a few prerequisites before you can get started creating solutions.
使用Snapdragon NPE SDK开发人造智能需要几个先决条件，才能开始创建解决方案。
You need to run a convolutional modell in one or multiple verticals, including mobile, automotive, IoT, AR, drones, and robotics
您需要在一个或多个垂直方向运行卷积模型，包括移动，汽车，IoT，AR，无人机和机器人You know how to design and train a model or already have a pre-trained model file
您知道如何设计和训练一个模型，或者已经有一个预先训练的模型文件Your framework of choice is Caffe/Caffe2 or TensorFlow
您选择的框架是Caffe / Caffe2或TensorFlowYou make JAVA APPs for Android or native applications for Android or Linux
您可以为Android或Android或Linux的本机应用程序制作JAVA应用程序You have an Ubuntu 14.04 development environment
您有一个Ubuntu 14.04开发环境You have a supported device to test your application on
您有一个支持的设备来测试您的应用程序