fix error links

events/summer2020/README.md

@@ -1,12 +1,13 @@
 # 开源软件供应链点亮计划 - 暑期 2020
 
-[开源供应链点亮计划 - 暑期 2020](https://isrc.iscas.ac.cn/summer2020)是由中科院软件所和 [openEuler](https://openeuler.org) 社区共同举办的一项面向高校学生的暑期活动，旨在鼓励在校学生积极参与开源软件的开发维护，促进国内优秀开源软件社区的蓬勃发展。
+[开源供应链点亮计划 - 暑期 2020](https://summer-ospp.ac.cn/2020/)是由中科院软件所和 [openEuler](https://openeuler.org) 社区共同举办的一项面向高校学生的暑期活动，旨在鼓励在校学生积极参与开源软件的开发维护，促进国内优秀开源软件社区的蓬勃发展。
 
-从即日起 [MindSpore](https://www.mindspore.cn) 社区通过[开源供应链点亮计划 - 暑期 2020](https://isrc.iscas.ac.cn/summer2020)活动发布开发任务，在活动过程中有对开发任务感兴趣的在校学生会通过社区 Issue / 邮件等方式和发布任务的导师进行沟通。 2020 年 6 月 30 日导师公布选中参与任务开发的学生，从 7 月 1 日开始到 9 月 30 日之间进行为期三个月的开发，在这个过程中导师对学生进行多种形式的辅导，帮助学生完成开发任务。
+从即日起 [MindSpore](https://www.mindspore.cn) 社区通过[开源供应链点亮计划 - 暑期 2020](https://summer-ospp.ac.cn/2020/)活动发布开发任务，在活动过程中有对开发任务感兴趣的在校学生会通过社区 Issue / 邮件等方式和发布任务的导师进行沟通。 2020 年 6 月 30 日导师公布选中参与任务开发的学生，从 7 月 1 日开始到 9 月 30 日之间进行为期三个月的开发，在这个过程中导师对学生进行多种形式的辅导，帮助学生完成开发任务。
 
 更多活动介绍
+
 1. https://docs.google.com/presentation/d/1XtMfT6XLLMw4yajz0M_Gi9WI71yk-rhWqx3xcT1q5kU
-2. https://isrc.iscas.ac.cn/summer2020
+2. https://summer-ospp.ac.cn/2020/
 
 ## MindSpore 社区任务提交方式
 

security/comments_specification_en.md

@@ -714,47 +714,34 @@ in which,
 ### C++ Example
 
 ```cpp
-/// \brief Function to create a CocoDataset.
-/// \note The generated dataset has multi-columns :
-///     - task='Detection', column: [['image', dtype=uint8], ['bbox', dtype=float32], ['category_id', dtype=uint32],
-///                                  ['iscrowd', dtype=uint32]].
-///     - task='Stuff', column: [['image', dtype=uint8], ['segmentation',dtype=float32], ['iscrowd', dtype=uint32]].
-///     - task='Keypoint', column: [['image', dtype=uint8], ['keypoints', dtype=float32],
-///                                 ['num_keypoints', dtype=uint32]].
-///     - task='Panoptic', column: [['image', dtype=uint8], ['bbox', dtype=float32], ['category_id', dtype=uint32],
-///                                 ['iscrowd', dtype=uint32], ['area', dtype=uitn32]].
+/// \brief Function to create a MnistDataset.
+/// \note The generated dataset has two columns ["image", "label"].
 /// \param[in] dataset_dir Path to the root directory that contains the dataset.
-/// \param[in] annotation_file Path to the annotation json.
-/// \param[in] task Set the task type of reading coco data, now support 'Detection'/'Stuff'/'Panoptic'/'Keypoint'.
-/// \param[in] decode Decode the images after reading.
+/// \param[in] usage Part of dataset of MNIST, can be "train", "test" or "all" (default = "all").
 /// \param[in] sampler Shared pointer to a sampler object used to choose samples from the dataset. If sampler is not
 ///     given, a `RandomSampler` will be used to randomly iterate the entire dataset (default = RandomSampler()).
 /// \param[in] cache Tensor cache to use (default=nullptr which means no cache is used).
-/// \param[in] extra_metadata Flag to add extra meta-data to row. (default=false).
-/// \return Shared pointer to the CocoDataset.
+/// \return Shared pointer to the MnistDataset.
 /// \par Example
 /// \code
 ///      /* Define dataset path and MindData object */
-///      std::string folder_path = "/path/to/coco_dataset_directory";
-///      std::string annotation_file = "/path/to/annotation_file";
-///      std::shared_ptr<Dataset> ds = Coco(folder_path, annotation_file);
+///      std::string folder_path = "/path/to/mnist_dataset_directory";
+///      std::shared_ptr<Dataset> ds = Mnist(folder_path, "all", std::make_shared<RandomSampler>(false, 20));
 ///
 ///      /* Create iterator to read dataset */
 ///      std::shared_ptr<Iterator> iter = ds->CreateIterator();
 ///      std::unordered_map<std::string, mindspore::MSTensor> row;
 ///      iter->GetNextRow(&row);
 ///
-///      /* Note: In COCO dataset, each dictionary has keys "image" and "annotation" */
+///      /* Note: In MNIST dataset, each dictionary has keys "image" and "label" */
 ///      auto image = row["image"];
 /// \endcode
-inline std::shared_ptr<CocoDataset> Coco(const std::string &dataset_dir, const std::string &annotation_file,
-                                         const std::string &task = "Detection", const bool &decode = false,
-                                         const std::shared_ptr<Sampler> &sampler = std::make_shared<RandomSampler>(),
-                                         const std::shared_ptr<DatasetCache> &cache = nullptr,
-                                         const bool &extra_metadata = false) {
-  return std::make_shared<CocoDataset>(StringToChar(dataset_dir), StringToChar(annotation_file), StringToChar(task),
-                                       decode, sampler, cache, extra_metadata);
+inline std::shared_ptr<MnistDataset> MS_API
+Mnist(const std::string &dataset_dir, const std::string &usage = "all",
+      const std::shared_ptr<Sampler> &sampler = std::make_shared<RandomSampler>(),
+      const std::shared_ptr<DatasetCache> &cache = nullptr) {
+  return std::make_shared<MnistDataset>(StringToChar(dataset_dir), StringToChar(usage), sampler, cache);
 }
 ```
 
-The API document page output according to the above comments is [Function mindspore::dataset::Coco](https://www.mindspore.cn/lite/api/en/master/generate/function_mindspore_dataset_Coco-1.html).
+The API document page output according to the above comments is [Function mindspore::dataset::Coco](https://www.mindspore.cn/lite/api/en/master/generate/function_mindspore_dataset_Mnist-1.html).

security/comments_specification_zh_cn.md

@@ -69,7 +69,7 @@ Examples:
 - `Raises`：异常信息，包含异常类型、含义等。
 - `Examples`：样例代码。
 
-**针对算子和Cell的注释，需要在`Examples`前添加`Inputs`、`Outputs`和`Supported Platforms`三项内容。**
+针对算子和Cell的注释，需要在`Examples`前添加`Inputs`、`Outputs`和`Supported Platforms`三项内容。
 
 - `Inputs`和`Outputs`：用于描述实例化后，算子的输入和输出的类型和shape，输入名可以和样例相同。建议在注释中给出对应的数学公式。
 - `Supported Platforms`：用于描述算子支持的硬件平台，名称前后需添加``，存在多个时使用空格隔开。
@@ -713,47 +713,34 @@ class BatchNorm(PrimitiveWithInfer):
 ### 完整示例
 
 ```cpp
-/// \brief Function to create a CocoDataset.
-/// \note The generated dataset has multi-columns :
-///     - task='Detection', column: [['image', dtype=uint8], ['bbox', dtype=float32], ['category_id', dtype=uint32],
-///                                  ['iscrowd', dtype=uint32]].
-///     - task='Stuff', column: [['image', dtype=uint8], ['segmentation',dtype=float32], ['iscrowd', dtype=uint32]].
-///     - task='Keypoint', column: [['image', dtype=uint8], ['keypoints', dtype=float32],
-///                                 ['num_keypoints', dtype=uint32]].
-///     - task='Panoptic', column: [['image', dtype=uint8], ['bbox', dtype=float32], ['category_id', dtype=uint32],
-///                                 ['iscrowd', dtype=uint32], ['area', dtype=uitn32]].
+/// \brief Function to create a MnistDataset.
+/// \note The generated dataset has two columns ["image", "label"].
 /// \param[in] dataset_dir Path to the root directory that contains the dataset.
-/// \param[in] annotation_file Path to the annotation json.
-/// \param[in] task Set the task type of reading coco data, now support 'Detection'/'Stuff'/'Panoptic'/'Keypoint'.
-/// \param[in] decode Decode the images after reading.
+/// \param[in] usage Part of dataset of MNIST, can be "train", "test" or "all" (default = "all").
 /// \param[in] sampler Shared pointer to a sampler object used to choose samples from the dataset. If sampler is not
 ///     given, a `RandomSampler` will be used to randomly iterate the entire dataset (default = RandomSampler()).
 /// \param[in] cache Tensor cache to use (default=nullptr which means no cache is used).
-/// \param[in] extra_metadata Flag to add extra meta-data to row. (default=false).
-/// \return Shared pointer to the CocoDataset.
+/// \return Shared pointer to the MnistDataset.
 /// \par Example
 /// \code
-/// /* Define dataset path and MindData object */
-/// std::string folder_path = "/path/to/coco_dataset_directory";
-/// std::string annotation_file = "/path/to/annotation_file";
-/// std::shared_ptr<Dataset> ds = Coco(folder_path, annotation_file);
+///      /* Define dataset path and MindData object */
+///      std::string folder_path = "/path/to/mnist_dataset_directory";
+///      std::shared_ptr<Dataset> ds = Mnist(folder_path, "all", std::make_shared<RandomSampler>(false, 20));
 ///
-/// /* Create iterator to read dataset */
-/// std::shared_ptr<Iterator> iter = ds->CreateIterator();
-/// std::unordered_map<std::string, mindspore::MSTensor> row;
-/// iter->GetNextRow(&row);
+///      /* Create iterator to read dataset */
+///      std::shared_ptr<Iterator> iter = ds->CreateIterator();
+///      std::unordered_map<std::string, mindspore::MSTensor> row;
+///      iter->GetNextRow(&row);
 ///
-/// /* Note: In COCO dataset, each dictionary has keys "image" and "annotation" */
-/// auto image = row["image"];
+///      /* Note: In MNIST dataset, each dictionary has keys "image" and "label" */
+///      auto image = row["image"];
 /// \endcode
-inline std::shared_ptr<CocoDataset> Coco(const std::string &dataset_dir, const std::string &annotation_file,
-                                         const std::string &task = "Detection", const bool &decode = false,
-                                         const std::shared_ptr<Sampler> &sampler = std::make_shared<RandomSampler>(),
-                                         const std::shared_ptr<DatasetCache> &cache = nullptr,
-                                         const bool &extra_metadata = false) {
-  return std::make_shared<CocoDataset>(StringToChar(dataset_dir), StringToChar(annotation_file), StringToChar(task),
-                                       decode, sampler, cache, extra_metadata);
+inline std::shared_ptr<MnistDataset> MS_API
+Mnist(const std::string &dataset_dir, const std::string &usage = "all",
+      const std::shared_ptr<Sampler> &sampler = std::make_shared<RandomSampler>(),
+      const std::shared_ptr<DatasetCache> &cache = nullptr) {
+  return std::make_shared<MnistDataset>(StringToChar(dataset_dir), StringToChar(usage), sampler, cache);
 }
 ```
 
-根据以上注释内容输出的API文档页面为[Function mindspore::dataset::Coco](https://www.mindspore.cn/lite/api/en/master/generate/function_mindspore_dataset_Coco-1.html)。
+根据以上注释内容输出的API文档页面为[Function mindspore::dataset::Coco](https://www.mindspore.cn/lite/api/en/master/generate/function_mindspore_dataset_Mnist-1.html)。

sigs/data/README.md

@@ -23,8 +23,8 @@ This is the working repo for the Data special interest group (SIG). This repo co
 ## Representative videos
 
 * [mindspore data processing introduction](https://www.bilibili.com/video/BV1RZ4y1W7FL)
-* [mindspore data loading and data format conversion](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/quick_start/quick_video/loading_the_dataset_and_converting_data_format.html)
-* [optimize data processing](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/quick_start/quick_video/optimize_data_processing.html)
+* [mindspore data loading and data format conversion](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/teaching_video/video/%E5%8A%A0%E8%BD%BD%E6%95%B0%E6%8D%AE%E9%9B%86%E4%B8%8E%E8%BD%AC%E6%8D%A2%E6%A0%BC%E5%BC%8F.mp4)
+* [optimize data processing](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/teaching_video/video/%E4%BC%98%E5%8C%96%E6%95%B0%E6%8D%AE%E5%A4%84%E7%90%86.mp4)
 
 ## Main issue To be solved
 

sigs/data/docs/official_resource.md

@@ -1,5 +1,5 @@
 ## Resource about Dataset in mindspore.cn
 
 * [data loading and processing](https://www.mindspore.cn/tutorials/zh-CN/master/index.html)
-* [dataset sample](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/dataset_sample.html)
+* [dataset sample](https://www.mindspore.cn/tutorials/zh-CN/master/advanced/dataset.html)
 * [dataset API introduction](https://www.mindspore.cn/docs/api/zh-CN/master/api_python/mindspore.dataset.html)

tsc/meeting-notes/2021/2021-02-18.md

@@ -37,7 +37,7 @@ Meeting link: https://welink-meeting.zoom.us/j/448774327
 
 ## Action Items
 
-1. DX MEP is added: <https://gitee.com/lyd911/community/tree/master/design/meps/mep-dx>
+1. DX MEP is added: <https://gitee.com/mindspore/community/tree/master/design/meps/mep-dx>
 
 2. Goals of DX SIG:  
    2.1 Build user portraits, attract core developers