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RELEASE.md 15 kB

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  1. # MindInsight 1.2.0
  2. ## MindInsight 1.2.0 Release Notes
  3. ### Major Features and Improvements
  4. #### Profiling
  5. - [STABLE] Support memory profiling.(Ascend)
  6. - [STABLE] Support host cpu utilization profiling.(Ascend/GPU)
  7. - [STABLE] Support timeline for Host&Device Hybrid Training.(Ascend/GPU)
  8. - [STABLE] Support show step breakdown information(Step Interval, Forward and Backward Propagation, and Step Tail) of each device in cluster profiling ui page.(Ascend)
  9. #### MindConverter
  10. - [STABLE] Support both classic computer vision and bert model definition script and trained weights migration from TensorFlow or PyTorch.
  11. - [STABLE] Support ONNX model migration to improve the usability of PyTorch model migration.
  12. #### Model Explanation
  13. - [STABLE] Support counterfactual explanation for image classification.
  14. ### API Change
  15. #### Backwards Compatible Change
  16. ##### Python API
  17. ###### add parameter `export_options` for `SummaryCollector` and `SummaryRecord`([!10881](https://gitee.com/mindspore/mindspore/pulls/10881))
  18. Perform custom operations on the export data. You can customize the export data with a dictionary. For example, you can set `{'tensor_format': 'npy'}` to export tensor as npy file.
  19. ###### add parameter `raise_exception` for `SummaryRecord`([!10436](https://gitee.com/mindspore/mindspore/pulls/10436))
  20. The parameter `raise_exception` determines whether to throw an exception when an exception occurs.
  21. ###### add API `register_uncertainty` for `explainer.ImageClassificationRunner`([!11309](https://gitee.com/mindspore/mindspore/pulls/11309))
  22. `register_uncertainty` helps register uncertainty instance to compute the epistemic uncertainty base on the Bayes’ theorem.
  23. ###### add API `register_hierarchical_occlusion` for `explainer.ImageClassificationRunner`([!11309](https://gitee.com/mindspore/mindspore/pulls/11309))
  24. `register_hierarchical_occlusion` helps register hierarchical occlusion instances.
  25. ##### Command Line Interface
  26. ###### `MindConverter` removes support for pth format model, `--project_path` deleted([!1253](https://gitee.com/mindspore/mindinsight/pulls/1253))
  27. The pth format model is not supported anymore, please use ONNX to migrate.
  28. ### Bug fixes
  29. - Error information missing when running on an unsupported device (e.g, cpu). [!11801](https://gitee.com/mindspore/mindspore/pulls/11801)
  30. ### Contributors
  31. Thanks goes to these wonderful people:
  32. Congli Gao, Longfei Li, Yongxiong Liang, Chongming Liu, Pengting Luo, Yanming Miao, Gongchang Ou, Kai Wen, Yue Wang, Lihua Ye, Ximiao Yu, Yunshu Zhang, Ning Ma, Yihui Zhang, Hong Sheng, Ran Mo, Zhaohong Guo, Tianshu Liang, Shuqiang Jiang, Yanjun Peng, Haitao Yang, Jiabin Liu, Han Gao, Xiaohui Li, Ngaifai Ng, Hui Pan, Weifeng Huang, Yifan Xia, Xuefeng Feng, Yanxi Wei.
  33. Contributions of any kind are welcome!
  34. # MindInsight 1.1.0
  35. ## MindInsight 1.1.0 Release Notes
  36. ### Major Features and Improvements
  37. #### Precision tuning framework
  38. - Support useful checks on weights, activations, gradients and tensors, such as:
  39. - check unchanged weight
  40. - check weight change above threshold
  41. - check activation range
  42. - check gradient vanishing
  43. - check tensor overflow
  44. - Support rechecking with new watch points on the same data.
  45. - Newly designed tensor view with fix suggestions and tensor context to quickly locate root cause of problems.
  46. - Support recommending watch points to find common precision problems.
  47. - Support debugger on multigraph network.
  48. #### Profiler
  49. - Support GPU step trace profiling.
  50. - Support GPU minddata profiling.
  51. #### MindConverter
  52. - Support TensorFlow model definition script to MindSpore for CV field.
  53. - Conversion capability of PyTorch is enhanced.
  54. #### Model Explanation
  55. Provide explanations and their benchmarks for image classification deep CNN models.
  56. - Support 6 explanation methods: Gradient, Deconvolution, GuidedBackprop, GradCAM, RISE, Occlusion
  57. - Support 4 benchmark methods: Localization, Faithfulness, Class Sensitivity, Robustness
  58. - Provide a high-level API (ImageClassificationRunner) for users to execute explanation methods and benchmark methods and store the results easily.
  59. ### API Change
  60. #### Improvements
  61. ##### Command Line Interface
  62. - `--enable_debugger`: Support both 1 and True ([!1051](https://gitee.com/mindspore/mindinsight/pulls/1051))
  63. - `ENABLE_MS_DEBUGGER`: Support both 1 and True ([!10199](https://gitee.com/mindspore/mindspore/pulls/10199))
  64. - `parse_summary`: Add parse_summary function to convert summary file to image file and csv file ([!774](https://gitee.com/mindspore/mindinsight/pulls/774))
  65. ### Bugfixes
  66. #### Profiler
  67. - Fix parser framework file error if the profiling data of one op is saved separately to two files.([!7824](https://gitee.com/mindspore/mindspore/pulls/7824))
  68. #### Model Explanation
  69. - Add reset_offset when CRCLengthError and CRCError happen([!955](https://gitee.com/mindspore/mindinsight/pulls/955))
  70. - FIx the bug which ignore the sample_event when sample_id == 0.([!968](https://gitee.com/mindspore/mindinsight/pulls/968))
  71. ### Thanks to our Contributors
  72. Thanks goes to these wonderful people:
  73. Congli Gao, Jianfeng Zhu, Zhenzhong Kou, Longfei Li, Yongxiong Liang, Chongming Liu, Pengting Luo, Yanming Miao, Gongchang Ou, Yongxiu Qu, Luyu Qiu, Kai Wen, Yue Wang, Lihua Ye, Ximiao Yu, Yunshu Zhang, Ning Ma, Yihui Zhang, Shuide Wang, Hong Sheng, Ran Mo, Zhaohong Guo, Hui Pan, Weining Wang, Weifeng Huang, Yifan Xia, Chen Cao, Ngaifai Ng, Xiaohui Li, Yi Yang, Luyu Qiu, Yunpeng Wang, Yuhan Shi, Yanxi Wei.
  74. Contributions of any kind are welcome!
  75. # MindInsight 1.0.0
  76. ## MindInsight 1.0.0 Release Notes
  77. ### Major Features and Improvements
  78. - Release MindSpore Debugger.
  79. - MindConverter ability is enhanced, supporting scripts generation based on PyTorch model.
  80. - Support training hyper-parameter importance visualization.
  81. - Support GPU timeline.
  82. ### Bugfixes
  83. - Optimize aicpu display method. ([!595](https://gitee.com/mindspore/mindinsight/pulls/595/files))
  84. - Add the summary loading switch mechanism. ([!601](https://gitee.com/mindspore/mindinsight/pulls/601/files))
  85. - Detect a summary dir having summary files or not. ([!632](https://gitee.com/mindspore/mindinsight/pulls/632/files))
  86. ### Thanks to our Contributors
  87. Thanks goes to these wonderful people:
  88. Congli Gao, Jianfeng Zhu, Zhenzhong Kou, Hongzhang Li, Longfei Li, Yongxiong Liang, Chongming Liu, Pengting Luo, Yanming Miao, Gongchang Ou, Yongxiu Qu, Luyu Qiu, Kai Wen, Yue Wang, Lihua Ye, Ximiao Yu, Yunshu Zhang, Ning Ma, Yihui Zhang, Shuide Wang, Hong Sheng, Ran Mo, Zhaohong Guo, Hui Pan, Junyan Qin, Weining Wang, Weifeng Huang, Yifan Xia.
  89. Contributions of any kind are welcome!
  90. # MindInsight 0.7.0-beta
  91. ## MindInsight 0.7.0 Release Notes
  92. ### Major Features and Improvements
  93. - Optimize node name display in computation graph.
  94. - MindSpore Profiler supports network training with GPU operators.
  95. - MindWizard generates classic network scripts according to user preference.
  96. - Web UI supports language internationalization, including both Chinese and English.
  97. ### Bugfixes
  98. - Optimize UI page initialization to handle timeout requests. ([!503](https://gitee.com/mindspore/mindinsight/pulls/503))
  99. - Fix the line break problem when the profiling file number is too long. ([!532](https://gitee.com/mindspore/mindinsight/pulls/532))
  100. ### Thanks to our Contributors
  101. Thanks goes to these wonderful people:
  102. Congli Gao, Weifeng Huang, Zhenzhong Kou, Hongzhang Li, Longfei Li, Yongxiong Liang, Chongming Liu, Pengting Luo, Yanming Miao, Gongchang Ou, Yongxiu Qu, Hui Pan, Luyu Qiu, Junyan Qin, Kai Wen, Weining Wang, Yue Wang, Zhuanke Wu, Yifan Xia, Lihua Ye, Weibiao Yu, Ximiao Yu, Yunshu Zhang, Ting Zhao, Jianfeng Zhu, Ning Ma, Yihui Zhang, Shuide Wang, Hong Sheng, Lin Pan, Ran Mo.
  103. Contributions of any kind are welcome!
  104. # MindInsight 0.6.0-beta
  105. ## MindInsight 0.6.0 Release Notes
  106. ### Major Features and Improvements
  107. - Provide monitoring capabilities for each of Ascend AI processor and other hardware resources, including CPU and memory.
  108. - Visualization of weight, gradient and other tensor data in model training.
  109. - Provide tabular from presentation of tensor data.
  110. - Provide histogram to show the distribution of tensor data and its change over time.
  111. ### Bugfixes
  112. - UI fix for the error message display mode of the tensor during real-time training. ([!465](https://gitee.com/mindspore/mindinsight/pulls/465))
  113. - The summary file size is larger than max_file_size. ([!3481](https://gitee.com/mindspore/mindspore/pulls/3481))
  114. - Fix real-time training error when disk is full. ([!3058](https://gitee.com/mindspore/mindspore/pulls/3058))
  115. ### Thanks to our Contributors
  116. Thanks goes to these wonderful people:
  117. Congli Gao, Weifeng Huang, Zhenzhong Kou, Hongzhang Li, Longfei Li, Yongxiong Liang, Chongming Liu, Pengting Luo, Yanming Miao, Gongchang Ou, Yongxiu Qu, Hui Pan, Luyu Qiu, Junyan Qin, Kai Wen, Weining Wang, Yue Wang, Zhuanke Wu, Yifan Xia, Lihua Ye, Weibiao Yu, Ximiao Yu, Yunshu Zhang, Ting Zhao, Jianfeng Zhu, Ning Ma, Yihui Zhang, Shuide Wang.
  118. Contributions of any kind are welcome!
  119. # MindInsight 0.5.0-beta
  120. ## MindInsight 0.5.0 Release Notes
  121. ### Major Features and Improvements
  122. - MindSpore Profiler
  123. - Provide performance analyse tool for the input data pipeline.
  124. - Provide timeline analyse tool, which can show the detail of the streams/tasks.
  125. - Provide a tool to visualize the step trace information, which can be used to analyse the general performance of the neural network in each phase.
  126. - Provide profiling guides for the users to find the performance bottlenecks quickly.
  127. - CPU summary operations support for CPU summary data.
  128. - Over threshold warn support in scalar training dashboard.
  129. - Provide more user-friendly callback function for visualization
  130. - Provide unified callback `SummaryCollector` to log most commonly visualization event.
  131. - Discard the original visualization callback `SummaryStep`, `TrainLineage` and `EvalLineage`.
  132. - `SummaryRecord` provide new API `add_value` to collect data into cache for summary persistence.
  133. - `SummaryRecord` provide new API `set_mode` to distinguish summary persistence mode at different stages.
  134. - MindConverter supports conversion of more operators and networks, and improves its ease of use.
  135. ### Bugfixes
  136. - Fix FileNotFound exception by adding robust check for summary watcher ([!281](https://gitee.com/mindspore/mindinsight/pulls/281)).
  137. - UI fix operator table sort jump problem ([!283](https://gitee.com/mindspore/mindinsight/pulls/283)).
  138. - Dataset serializer return schema json str when schema type is `mindspore.dataset.engine.Schema` ([!2185](https://gitee.com/mindspore/mindspore/pulls/2185)).
  139. ### Thanks to our Contributors
  140. Thanks goes to these wonderful people:
  141. Chao Chen, Congli Gao, Ye Huang, Weifeng Huang, Zhenzhong Kou, Hongzhang Li, Longfei Li, Yongxiong Liang, Chongming Liu, Pengting Luo, Yanming Miao, Gongchang Ou, Yongxiu Qu, Hui Pan, Luyu Qiu, Junyan Qin, Kai Wen, Weining Wang, Yue Wang, Zhuanke Wu, Yifan Xia, Lihua Ye, Weibiao Yu, Ximiao Yu, Yunshu Zhang, Ting Zhao, Jianfeng Zhu.
  142. Contributions of any kind are welcome!
  143. # MindInsight 0.3.0-alpha
  144. ## MindInsight 0.3.0 Release Notes
  145. ### Major Features and Improvements
  146. - Profiling
  147. - Provide easy to use apis for profiling start/stop and profiling data analyse (on Ascend only).
  148. - Provide operators performance display and analysis on MindInsight UI.
  149. - Large scale network computation graph visualization.
  150. - Optimize summary record implementation and improve its performance.
  151. - Improve lineage usability
  152. - Optimize lineage display and enrich tabular operation.
  153. - Decouple lineage callback from `SummaryRecord`.
  154. - Support scalar compare of multiple runs.
  155. - Scripts conversion from other frameworks
  156. - Support for converting PyTorch scripts within TorchVision to MindSpore scripts automatically.
  157. ### Bugfixes
  158. - Fix pb files loaded problem when files are modified at the same time ([!53](https://gitee.com/mindspore/mindinsight/pulls/53)).
  159. - Fix load data thread stuck in `LineageCacheItemUpdater` ([!114](https://gitee.com/mindspore/mindinsight/pulls/114)).
  160. - Fix samples from previous steps erased due to tags size too large problem ([!86](https://gitee.com/mindspore/mindinsight/pulls/86)).
  161. - Fix image and histogram event package error ([!1143](https://gitee.com/mindspore/mindspore/pulls/1143)).
  162. - Equally distribute histogram ignoring actual step number to avoid large white space ([!66](https://gitee.com/mindspore/mindinsight/pulls/66)).
  163. ### Thanks to our Contributors
  164. Thanks goes to these wonderful people:
  165. Chao Chen, Congli Gao, Ye Huang, Weifeng Huang, Zhenzhong Kou, Hongzhang Li, Longfei Li, Yongxiong Liang, Pengting Luo, Yanming Miao, Gongchang Ou, Yongxiu Qu, Hui Pan, Luyu Qiu, Junyan Qin, Kai Wen, Weining Wang, Yue Wang, Zhuanke Wu, Yifan Xia, Weibiao Yu, Ximiao Yu, Ting Zhao, Jianfeng Zhu.
  166. Contributions of any kind are welcome!
  167. # MindInsight 0.2.0-alpha
  168. ## MindInsight 0.2.0 Release Notes
  169. ### Major Features and Improvements
  170. - Parameter distribution graph (Histogram).
  171. Now you can use [`HistogramSummary`](https://www.mindspore.cn/doc/api_python/en/master/mindspore/mindspore.ops.html#mindspore.ops.HistogramSummary) and MindInsight to record and visualize distribution info of tensors. See our [tutorial](https://www.mindspore.cn/tutorial/training/en/master/advanced_use/visualization_tutorials.html).
  172. - Lineage support Custom information
  173. - GPU support
  174. - Model and dataset tracking linkage support
  175. ### Bugfixes
  176. - Reduce cyclomatic complexity of `list_summary_directories` ([!11](https://gitee.com/mindspore/mindinsight/pulls/11)).
  177. - Fix unsafe functions and duplication files and redundant codes ([!14](https://gitee.com/mindspore/mindinsight/pulls/14)).
  178. - Fix sha256 checksum missing bug ([!24](https://gitee.com/mindspore/mindinsight/pulls/24)).
  179. - Fix graph bug when node name is empty ([!34](https://gitee.com/mindspore/mindinsight/pulls/34)).
  180. - Fix start/stop command error code incorrect ([!44](https://gitee.com/mindspore/mindinsight/pulls/44)).
  181. ### Thanks to our Contributors
  182. Thanks goes to these wonderful people:
  183. Ye Huang, Weifeng Huang, Zhenzhong Kou, Pengting Luo, Hongzhang Li, Yongxiong Liang, Gongchang Ou, Hui Pan, Luyu Qiu, Junyan Qin, Kai Wen, Weining Wang, Yifan Xia, Yunshu Zhang, Ting Zhao
  184. Contributions of any kind are welcome!
  185. # MindInsight 0.1.0-alpha
  186. ## MindInsight 0.1.0 Release Notes
  187. - Training process observation
  188. - Provides and displays training process information, including computational graphs and training process indicators.
  189. - Training result tracing
  190. - Provides functions of tracing and visualizing model training parameter information, including filtering and sorting of training data, model accuracy and training hyperparameters.