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# FAQ
<!-- TOC -->
- [FAQ](#faq)
- [Installation](#installation)
- [Pip Installation](#pip-installation)
- [Source Code Installation](#source-code-installation)
- [Support](#support)
- [Model Support](#model-support)
- [Backend Support](#backend-support)
- [Programming Language](#programming-language)
- [Others](#others)
- [Features](#features)
- [Capabilities](#capabilities)
<!-- /TOC -->
## Installation
### Pip Installation
Q: Any specific requirements for Python version when pip install MindSpore?
A: MindSpore utilizes many of the new features in Python3.7+,therefore we recommend you add Python3.7.5 develop environment via `conda`.
<br/>
Q: What should I do when error prompts during pip install ?
A: Please execute `pip -V` to check if pip is linked to Python3.7+. If not, we recommend you
use `python3.7 -m pip install` instead of `pip install` command.
<br/>
Q: What should I do if I cannot find whl package for MindInsight or MindArmour for installation ?
A: You can download whl package from the official [MindSpore Website download page](https://www.mindspore.cn/versions) and manually install it via `pip install`.
### Source Code Installation
Q: What should I do if the compilation time of MindSpore source code taking too long or the process is constantly interrupted by errors ?
A: MindSpore imports third party dependencies through submodule mechanism, among which `protobuf` v3.8.0 might not have the optimal or steady download speed, we recommend you prepare the protobuf package beforehand via other method.
<br/>
Q: What should I do if the software version required by MindSpore is not the same with the Ubuntu default software version ?
A: At the moment some software might need manual upgrade. (**Note**:MindSpore requires Python3.7.5 and gcc7.3,the default version in Ubuntu 16.04 are Python3.5 and gcc5,whereas the one in Ubuntu 18.04 are Python3.7.3 and gcc7.4)
<br/>
Q: What should I do if there is a prompt `tclsh not found` when I compile MindSpore from source code ?
A: Please install the software manually if there is any suggestion of certain `software not found`.
## Support
### Model Support
Q: What types of model is currently supported by MindSpore for training ?
A: MindSpore has basic support for common training scenarios, please refer to [Release note](https://gitee.com/mindspore/mindspore/blob/master/RELEASE.md) for detailed information.
### Backend Support
Q: When install or run MindSpore, are there any requirements for hardwares like GPU, NPU and so forth ?
A: MindSpore currently supports Ascend AI processor, CPU and GPU。For common models like lenet you can try run MindSpore on CPU alone.
<br/>
Q: Does MindSpore have any plan on supporting other types of heterogeneous computing hardwares ?
A: MindSpore provides pluggable device management interface so that developer could easily integrate other types of heterogeneous computing hardwares like FPGA to MindSpore. We welcome more backend support in MindSpore from the community.
### Programming Language
Q: The recent announced programming language such as taichi got Python extensions that could be directly used as `import taichi as ti`. Does MindSpore have similar support ?
A: MindSpore supports Python native expression via `import mindspore`
<br/>
Q: Does MindSpore plan to support more programming languages other than Python ?
A:MindSpore currently supports Python extensions,bindings for languages like C++、Rust、Julia are on the way.
### Others
Q: How does MindSpore implement semantic collaboration and processing? Is the popular Formal Concept Analysis (FCA) used?
A: The MindSpore framework does not support FCA. For semantic models, you can call third-party tools to perform FCA in the data preprocessing phase. MindSpore supports Python therefore `import FCA` could do the trick.
## Features
Q: Does MindSpore have any plan or consideration on the edge and device when the training and inference functions on the cloud are relatively mature?
A: MindSpore is a unified cloud-edge-device training and inference framework. Edge has been considered in its design, so MindSpore can perform inference at the edge. The open-source version will support Ascend 310-based inference. Currently, inference supports optimization operations, including quantization, operator fusion, and memory overcommitment.
## Capabilities
Q: Does MindSpore have a module that can implement object detection algorithms as TensorFlow does?
A: The TensorFlow's object detection pipeline API belongs to the TensorFlow's Model module. After MindSpore's detection models are complete, similar pipeline APIs will be provided.
# FAQ
<!-- TOC -->
- [FAQ](#faq)
- [安装](#安装)
- [pip安装](#pip安装)
- [源码编译安装](#源码编译安装)
- [支持](#支持)
- [模型支持](#模型支持)
- [后端支持](#后端支持)
- [编程语言扩展](#编程语言扩展)
- [其他](#其他)
- [特性](#特性)
- [能力](#能力)
<!-- /TOC -->
## 安装
### pip安装
Q:pip安装MindSpore对Python版本是否有特别要求?
A:MindSpore开发过程中用到了Python3.7+的新特性,因此建议您通过`conda`工具添加Python3.7.5的开发环境。
<br/>
Q:使用pip安装时提示错误,应该怎么办?
A:请执行`pip -V`查看是否绑定了Python3.7+。如果绑定的版本不对,建议使用`python3.7 -m pip install`代替`pip install`命令。
<br/>
Q:MindSpore网站安装页面找不到MindInsight和MindArmour的whl包,无法安装怎么办?
A:您可以从[MindSpore网站下载地址](https://www.mindspore.cn/versions)下载whl包,通过`pip install`命令进行安装。
### 源码编译安装
Q:源码编译MindSpore过程时间过长,或时常中断该怎么办?
A:MindSpore通过submodule机制引入第三方依赖包,其中`protobuf`依赖包(v3.8.0)下载速度不稳定,建议您提前进行包缓存。
<br/>
Q:MindSpore要求的配套软件版本与Ubuntu默认版本不一致怎么办?
A:当前MindSpore只提供版本配套关系,需要您手动进行配套软件的安装升级。(**注明**:MindSpore要求Python3.7.5和gcc7.3,Ubuntu 16.04默认为Python3.5和gcc5,Ubuntu 18.04默认自带Python3.7.3和gcc7.4)
<br/>
Q:当源码编译MindSpore,提示`tclsh not found`时,应该怎么办?
A:当有此提示时说明要用户安装`tclsh`;如果仍提示缺少其他软件,同样需要安装其他软件。
## 支持
### 模型支持
Q:MindSpore支持哪些模型的训练?
A:MindSpore针对典型场景均有模型训练支持,支持情况详见[Release note](https://gitee.com/mindspore/mindspore/blob/master/RELEASE.md)
### 后端支持
Q:安装运行MindSpore时,是否要求平台有GPU、NPU等计算单元?
A:MindSpore当前支持CPU/GPU/NPU,重点支持Ascend AI处理器。CPU支持Lenet模型,您可以尝试使用。
<br/>
Q:针对异构计算单元的支持,MindSpore有什么计划?
A:MindSpore提供了可插拔式的设备管理接口,其他计算单元(比如FPGA)可快速灵活地实现与MindSpore的对接,欢迎您参与社区进行异构计算后端的开发工作。
### 编程语言扩展
Q:最近出来的taichi编程语言有Python扩展,类似`import taichi as ti`就能直接用了,MindSpore是否也支持?
A:MindSpore支持Python原生表达,`import mindspore`相关包即可使用。
<br/>
Q:MindSpore是否(计划)支持多语言扩展?
A:MindSpore目前支持Python扩展,针对C++、Rust、Julia等语言的支持正在开发中。
### 其他
Q:MindSpore在语义协同和处理上是如何实现的?是否利用当前学术界流行的FCA理论?
A:MindSpore框架本身并不需要支持FCA。对于语义类模型,用户可以调用第三方的工具在数据预处理阶段做FCA数学分析。MindSpore本身支持Python语言,`import FCA`相关包即可使用。
## 特性
Q:当前在云上MindSpore的训练和推理功能是比较完备的,至于边端场景(尤其是终端设备)MindSpore有什么计划?
A:MindSpore是端边云统一的训练和推理框架,支持将云侧训练的模型导出到Ascend AI处理器和终端设备进行推理。当前推理阶段支持的优化包括量化、算子融合、内存复用等。
## 能力
Q:MindSpore有没有类似基于TensorFlow实现的对象检测算法的模块?
A:TensorFlow的对象检测Pipeline接口属于TensorFlow Model模块。待MindSpore检测类模型完备后,会提供类似的Pipeline接口。
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