Task Description

1. Go to the official tutorial, namely "Optimizing the Data Processing": https://www.mindspore.cn/tutorial/training/zh-CN/master/advanced_use/optimize_data_processing.html.
2. Extract as much as sample codes from the tutorial and write the code into a .py file.
3. Supplment relevant codes like datasets and networks in the .py file and enable the .py file to become runnable.(Code fragments can be run separately in different .py files).
4. Define the directory /docs/tutorials/tutorial_code/optimize_data_processing/ in the docs repository, deliver the completed codes under this directory, and submit PR.
5. Add the results of running the code to the PR comment.

The code should follow the Code Standards.

Using deep neural networks and datasets that have not appeared in the official tutorials is fine. Meanwhile, you can define the directories of reading datasets and generating models on your own. If a third-party dataset is used, please provide the reference and the link.

Task Goal

Let users learn and adopt the data optimization in MindSpore. It is important that the users should apply their studies to practice and have a throughout understanding of the MindSpore framework. Meanwhile, the source code of the tutorial submitted by users will be displayed for other users to learn.

Level

Easy