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# Overall Architecture
This document describes the overall architecture of MindSpore.
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- [Overall Architecture](#overall-architecture)
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`Ascend` `GPU` `CPU` `On Device` `Model Development` `Model Optimization` `Framework Development` `Intermediate` `Expert` `Contributor`
<a href="https://gitee.com/mindspore/docs/blob/master/docs/source_en/architecture.md" target="_blank"><img src="./_static/logo_source.png"></a>
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# Benchmarks
`Ascend` `Model Training` `Intermediae` `Expert`
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- [Benchmarks](#benchmarks)
- [Training Performance](#training-performance)
- [ResNet](#resnet)
- [BERT](#bert)
- [Wide & Deep (data parallel)](#wide--deep-data-parallel)
- [Wide & Deep (Host-Device model parallel)](#wide--deep-host-device-model-parallel)
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<a href="https://gitee.com/mindspore/docs/blob/master/docs/source_en/benchmark.md" target="_blank"><img src="./_static/logo_source.png"></a>
This document describes the MindSpore benchmarks.
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# Constraints on Network Construction Using Python
`Ascend` `GPU` `CPU` `Model Development` `Beginner` `Intermediate` `Expert`
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- [Constraints on Network Construction Using Python](#constraints-on-network-construction-using-python)
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# Computational Graph Visualization Design
`Ascend` `GPU` `Model Development` `Model Optimization` `Framework Development` `Intermediate` `Expert` `Contributor`
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- [Computational Graph Visualization Design](#computational-graph-visualization-design)
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# Tensor Visualization Design
`Ascend` `GPU` `Model Development` `Model Optimization` `Framework Development` `Intermediate` `Expert` `Contributor`
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- [Tensor Visualization Design](#tensor-visualization-design)
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# Glossary
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- [Glossary](#glossary)
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`Ascend` `GPU` `CPU` `Whole Process` `Beginner` `Intermediate` `Expert`
<a href="https://gitee.com/mindspore/docs/blob/master/docs/source_en/glossary.md" target="_blank"><img src="./_static/logo_source.png"></a>
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# Seeking Help and Support
This document describes how to seek help and support when you encounter problems in using MindSpore.
`Ascend` `GPU` `CPU` `Whole Process` `Beginner` `Intermediate` `Expert`
<a href="https://gitee.com/mindspore/docs/blob/master/docs/source_en/help_seeking_path.md" target="_blank"><img src="./_static/logo_source.png"></a>
The following flowchart shows the overall help-seeking process which starts from users encountering a problem in using MindSpore and ends with they finding a proper solution. Help-seeking methods are introduced based on the flowchart.
This document describes how to seek help and support when you encounter problems in using MindSpore. The following flowchart shows the overall help-seeking process which starts from users encountering a problem in using MindSpore and ends with they finding a proper solution. Help-seeking methods are introduced based on the flowchart.
![solution](./images/help_seeking_path.png)
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# Network List
`Ascend` `GPU` `CPU` `Model Development` `Intermediate` `Expert`
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- [Network List](#network-list)
- [Model Zoo](#model-zoo)
- [Pre-trained Models](#pre-trained-models)
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<a href="https://gitee.com/mindspore/docs/tree/master/docs/source_en/network_list.md" target="_blank"><img src="./_static/logo_source.png"></a>
## Model Zoo
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# Operator List
`Ascend` `GPU` `CPU` `Model Development` `Beginner` `Intermediate` `Expert`
<!-- TOC -->
- [Operator List](#operator-list)
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# RoadMap
MindSpore's top priority plans in the year are displayed as follows. We will continuously adjust the priority based on user feedback.
`Ascend` `GPU` `CPU` `Whole Process` `Framework Development` `Intermediate` `Expert` `Contributor`
<!-- TOC -->
......@@ -16,6 +16,8 @@ MindSpore's top priority plans in the year are displayed as follows. We will con
<a href="https://gitee.com/mindspore/docs/blob/master/docs/source_en/roadmap.md" target="_blank"><img src="./_static/logo_source.png"></a>
MindSpore's top priority plans in the year are displayed as follows. We will continuously adjust the priority based on user feedback.
In general, we will make continuous improvements in the following aspects:
1. Support more preset models.
2. Continuously supplement APIs and operator libraries to improve usability and programming experience.
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# 差分隐私
`Ascend` `模型开发` `模型调优` `框架开发` `企业` `高级` `贡献者`
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- [差分隐私](#差分隐私)
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# Differential Privacy in Machine Learning
`Ascend` `Data Preparation` `Model Development` `Model Training` `Model Optimization` `Enterprise` `Expert`
`Ascend` `Model Development` `Model Optimization` `Enterprise` `Expert`
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# 机器学习中的差分隐私
`Ascend` `数据准备` `模型开发` `模型训练` `模型调优` `企业` `高级`
`Ascend` `模型开发` `模型调优` `企业` `高级`
<a href="https://gitee.com/mindspore/docs/blob/master/tutorials/source_zh_cn/advanced_use/differential_privacy.md" target="_blank"><img src="../_static/logo_source.png"></a>
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