From c4ccb070c35fae98aa7bf891ab331e3f5b46f904 Mon Sep 17 00:00:00 2001 From: luopengting Date: Sat, 27 Mar 2021 11:29:48 +0800 Subject: [PATCH] update release notes --- RELEASE.md | 230 ++++++++++++++++++++++++++--------------------------- 1 file changed, 115 insertions(+), 115 deletions(-) diff --git a/RELEASE.md b/RELEASE.md index df2e42f6..946d9066 100644 --- a/RELEASE.md +++ b/RELEASE.md @@ -1,24 +1,24 @@ -# MindSpore 1.2.0-rc1 Release Notes +# MindInsight 1.2.0-rc1 -## MindInsight +## MindInsight 1.2.0 Release Notes ### Major Features and Improvements #### Profiling -* [STABLE] Support memory profiling.(Ascend) -* [STABLE] Support host cpu utilization profiling.(Ascend/GPU) -* [STABLE] Support timeline for Host&Device Hybrid Training.(Ascend/GPU) -* [STABLE] Support show step breakdown information(Step Interval, Forward and Backward Propagation, and Step Tail)of each device in cluster profiling ui page.(Ascend) +- [STABLE] Support memory profiling.(Ascend) +- [STABLE] Support host cpu utilization profiling.(Ascend/GPU) +- [STABLE] Support timeline for Host&Device Hybrid Training.(Ascend/GPU) +- [STABLE] Support show step breakdown information(Step Interval, Forward and Backward Propagation, and Step Tail)of each device in cluster profiling ui page.(Ascend) #### MindConverter -* [STABLE] Support both classic computer vision and bert model definition script and trained weights migration from TensorFlow or PyTorch. -* [STABLE] Support ONNX model migration to improve the usability of PyTorch model migration. +- [STABLE] Support both classic computer vision and bert model definition script and trained weights migration from TensorFlow or PyTorch. +- [STABLE] Support ONNX model migration to improve the usability of PyTorch model migration. #### Model Explanation -* [STABLE] Support counterfactual explanation for image classification. +- [STABLE] Support counterfactual explanation for image classification. ### API Change @@ -50,9 +50,9 @@ The pth format model is not supported anymore, please use ONNX to migrate. ### Bug fixes -* Error information missing when running on an unsupported device (e.g, cpu). [!11901](https://gitee.com/mind_spore/dashboard/projects/mindspore/mindspore/pulls/11801) +- Error information missing when running on an unsupported device (e.g, cpu). [!11801](https://gitee.com/mindspore/mindspore/pulls/11801) -### Thanks to our Contributors +### Contributors Thanks goes to these wonderful people: @@ -60,42 +60,42 @@ Congli Gao, Longfei Li, Yongxiong Liang, Chongming Liu, Pengting Luo, Yanming Mi Contributions of any kind are welcome! -# MindSpore 1.1.0 Release Notes +# MindInsight 1.1.0 -## MindInsight +## MindInsight 1.1.0 Release Notes ### Major Features and Improvements #### Precision tuning framework -* Support useful checks on weights, activations, gradients and tensors, such as: - * check unchanged weight - * check weight change above threshold - * check activation range - * check gradient vanishing - * check tensor overflow -* Support rechecking with new watch points on the same data. -* Newly designed tensor view with fix suggestions and tensor context to quickly locate root cause of problems. -* Support recommending watch points to find common precision problems. -* Support debugger on multigraph network. +- Support useful checks on weights, activations, gradients and tensors, such as: + - check unchanged weight + - check weight change above threshold + - check activation range + - check gradient vanishing + - check tensor overflow +- Support rechecking with new watch points on the same data. +- Newly designed tensor view with fix suggestions and tensor context to quickly locate root cause of problems. +- Support recommending watch points to find common precision problems. +- Support debugger on multigraph network. #### Profiler -* Support GPU step trace profiling. -* Support GPU minddata profiling. +- Support GPU step trace profiling. +- Support GPU minddata profiling. #### MindConverter -* Support TensorFlow model definition script to MindSpore for CV field. -* Conversion capability of PyTorch is enhanced. +- Support TensorFlow model definition script to MindSpore for CV field. +- Conversion capability of PyTorch is enhanced. #### Model Explanation Provide explanations and their benchmarks for image classification deep CNN models. -* Support 6 explanation methods: Gradient, Deconvolution, GuidedBackprop, GradCAM, RISE, Occlusion -* Support 4 benchmark methods: Localization, Faithfulness, Class Sensitivity, Robustness -* Provide a high-level API (ImageClassificationRunner) for users to execute explanation methods and benchmark methods and store the results easily. +- Support 6 explanation methods: Gradient, Deconvolution, GuidedBackprop, GradCAM, RISE, Occlusion +- Support 4 benchmark methods: Localization, Faithfulness, Class Sensitivity, Robustness +- Provide a high-level API (ImageClassificationRunner) for users to execute explanation methods and benchmark methods and store the results easily. ### API Change @@ -103,20 +103,20 @@ Provide explanations and their benchmarks for image classification deep CNN mode ##### Command Line Interface -* `--enable_debugger`: Support both 1 and True ([!1051](https://gitee.com/mindspore/mindinsight/pulls/1051)) -* `ENABLE_MS_DEBUGGER`: Support both 1 and True ([!10199](https://gitee.com/mindspore/mindspore/pulls/10199)) -* `parse_summary`: Add parse_summary function to convert summary file to image file and csv file ([!774](https://gitee.com/mindspore/mindinsight/pulls/774)) +- `--enable_debugger`: Support both 1 and True ([!1051](https://gitee.com/mindspore/mindinsight/pulls/1051)) +- `ENABLE_MS_DEBUGGER`: Support both 1 and True ([!10199](https://gitee.com/mindspore/mindspore/pulls/10199)) +- `parse_summary`: Add parse_summary function to convert summary file to image file and csv file ([!774](https://gitee.com/mindspore/mindinsight/pulls/774)) ### Bugfixes #### Profiler -* 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)) +- 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)) #### Model Explanation -* Add reset_offset when CRCLengthError and CRCError happen([!955](https://gitee.com/mindspore/mindinsight/pulls/955)) -* FIx the bug which ignore the sample_event when sample_id == 0.([!968](https://gitee.com/mindspore/mindinsight/pulls/968)) +- Add reset_offset when CRCLengthError and CRCError happen([!955](https://gitee.com/mindspore/mindinsight/pulls/955)) +- FIx the bug which ignore the sample_event when sample_id == 0.([!968](https://gitee.com/mindspore/mindinsight/pulls/968)) ### Thanks to our Contributors @@ -126,22 +126,22 @@ Congli Gao, Jianfeng Zhu, Zhenzhong Kou, Longfei Li, Yongxiong Liang, Chongming Contributions of any kind are welcome! -# MindSpore 1.0.0 Release Notes +# MindInsight 1.0.0 -## MindInsight +## MindInsight 1.0.0 Release Notes ### Major Features and Improvements -* Release MindSpore Debugger. -* MindConverter ability is enhanced, supporting scripts generation based on PyTorch model. -* Support training hyper-parameter importance visualization. -* Support GPU timeline. +- Release MindSpore Debugger. +- MindConverter ability is enhanced, supporting scripts generation based on PyTorch model. +- Support training hyper-parameter importance visualization. +- Support GPU timeline. ### Bugfixes -* Optimize aicpu display method. ([!595](https://gitee.com/mindspore/mindinsight/pulls/595/files)) -* Add the summary loading switch mechanism. ([!601](https://gitee.com/mindspore/mindinsight/pulls/601/files)) -* Detect a summary dir having summary files or not. ([!632](https://gitee.com/mindspore/mindinsight/pulls/632/files)) +- Optimize aicpu display method. ([!595](https://gitee.com/mindspore/mindinsight/pulls/595/files)) +- Add the summary loading switch mechanism. ([!601](https://gitee.com/mindspore/mindinsight/pulls/601/files)) +- Detect a summary dir having summary files or not. ([!632](https://gitee.com/mindspore/mindinsight/pulls/632/files)) ### Thanks to our Contributors @@ -151,21 +151,21 @@ Congli Gao, Jianfeng Zhu, Zhenzhong Kou, Hongzhang Li, Longfei Li, Yongxiong Lia Contributions of any kind are welcome! -# MindSpore 0.7.0-beta Release Notes +# MindInsight 0.7.0-beta -## MindInsight +## MindInsight 0.7.0 Release Notes ### Major Features and Improvements -* Optimize node name display in computation graph. -* MindSpore Profiler supports network training with GPU operators. -* MindWizard generates classic network scripts according to user preference. -* Web UI supports language internationalization, including both Chinese and English. +- Optimize node name display in computation graph. +- MindSpore Profiler supports network training with GPU operators. +- MindWizard generates classic network scripts according to user preference. +- Web UI supports language internationalization, including both Chinese and English. ### Bugfixes -* Optimize UI page initialization to handle timeout requests. ([!503](https://gitee.com/mindspore/mindinsight/pulls/503)) -* Fix the line break problem when the profiling file number is too long. ([!532](https://gitee.com/mindspore/mindinsight/pulls/532)) +- Optimize UI page initialization to handle timeout requests. ([!503](https://gitee.com/mindspore/mindinsight/pulls/503)) +- Fix the line break problem when the profiling file number is too long. ([!532](https://gitee.com/mindspore/mindinsight/pulls/532)) ### Thanks to our Contributors @@ -175,22 +175,22 @@ Congli Gao, Weifeng Huang, Zhenzhong Kou, Hongzhang Li, Longfei Li, Yongxiong Li Contributions of any kind are welcome! -# MindSpore 0.6.0-beta Release Notes +# MindInsight 0.6.0-beta -## MindInsight +## MindInsight 0.6.0 Release Notes ### Major Features and Improvements -* Provide monitoring capabilities for each of Ascend AI processor and other hardware resources, including CPU and memory. -* Visualization of weight, gradient and other tensor data in model training. - * Provide tabular from presentation of tensor data. - * Provide histogram to show the distribution of tensor data and its change over time. +- Provide monitoring capabilities for each of Ascend AI processor and other hardware resources, including CPU and memory. +- Visualization of weight, gradient and other tensor data in model training. + - Provide tabular from presentation of tensor data. + - Provide histogram to show the distribution of tensor data and its change over time. ### Bugfixes -* UI fix for the error message display mode of the tensor during real-time training. ([!465](https://gitee.com/mindspore/mindinsight/pulls/465)) -* The summary file size is larger than max_file_size. ([!3481](https://gitee.com/mindspore/mindspore/pulls/3481)) -* Fix real-time training error when disk is full. ([!3058](https://gitee.com/mindspore/mindspore/pulls/3058)) +- UI fix for the error message display mode of the tensor during real-time training. ([!465](https://gitee.com/mindspore/mindinsight/pulls/465)) +- The summary file size is larger than max_file_size. ([!3481](https://gitee.com/mindspore/mindspore/pulls/3481)) +- Fix real-time training error when disk is full. ([!3058](https://gitee.com/mindspore/mindspore/pulls/3058)) ### Thanks to our Contributors @@ -200,31 +200,31 @@ Congli Gao, Weifeng Huang, Zhenzhong Kou, Hongzhang Li, Longfei Li, Yongxiong Li Contributions of any kind are welcome! -# MindSpore 0.5.0-beta Release Notes +# MindInsight 0.5.0-beta -## MindInsight +## MindInsight 0.5.0 Release Notes ### Major Features and Improvements -* MindSpore Profiler - * Provide performance analyse tool for the input data pipeline. - * Provide timeline analyse tool, which can show the detail of the streams/tasks. - * 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. - * Provide profiling guides for the users to find the performance bottlenecks quickly. -* CPU summary operations support for CPU summary data. -* Over threshold warn support in scalar training dashboard. -* Provide more user-friendly callback function for visualization - * Provide unified callback `SummaryCollector` to log most commonly visualization event. - * Discard the original visualization callback `SummaryStep`, `TrainLineage` and `EvalLineage`. - * `SummaryRecord` provide new API `add_value` to collect data into cache for summary persistence. - * `SummaryRecord` provide new API `set_mode` to distinguish summary persistence mode at different stages. -* MindConverter supports conversion of more operators and networks, and improves its ease of use. +- MindSpore Profiler + - Provide performance analyse tool for the input data pipeline. + - Provide timeline analyse tool, which can show the detail of the streams/tasks. + - 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. + - Provide profiling guides for the users to find the performance bottlenecks quickly. +- CPU summary operations support for CPU summary data. +- Over threshold warn support in scalar training dashboard. +- Provide more user-friendly callback function for visualization + - Provide unified callback `SummaryCollector` to log most commonly visualization event. + - Discard the original visualization callback `SummaryStep`, `TrainLineage` and `EvalLineage`. + - `SummaryRecord` provide new API `add_value` to collect data into cache for summary persistence. + - `SummaryRecord` provide new API `set_mode` to distinguish summary persistence mode at different stages. +- MindConverter supports conversion of more operators and networks, and improves its ease of use. ### Bugfixes -* Fix FileNotFound exception by adding robust check for summary watcher ([!281](https://gitee.com/mindspore/mindinsight/pulls/281)). -* UI fix operator table sort jump problem ([!283](https://gitee.com/mindspore/mindinsight/pulls/283)). -* Dataset serializer return schema json str when schema type is `mindspore.dataset.engine.Schema` ([!2185](https://gitee.com/mindspore/mindspore/pulls/2185)). +- Fix FileNotFound exception by adding robust check for summary watcher ([!281](https://gitee.com/mindspore/mindinsight/pulls/281)). +- UI fix operator table sort jump problem ([!283](https://gitee.com/mindspore/mindinsight/pulls/283)). +- Dataset serializer return schema json str when schema type is `mindspore.dataset.engine.Schema` ([!2185](https://gitee.com/mindspore/mindspore/pulls/2185)). ### Thanks to our Contributors @@ -234,31 +234,31 @@ Chao Chen, Congli Gao, Ye Huang, Weifeng Huang, Zhenzhong Kou, Hongzhang Li, Lon Contributions of any kind are welcome! -# MindSpore 0.3.0-alpha Release Notes +# MindInsight 0.3.0-alpha -## MindInsight +## MindInsight 0.3.0 Release Notes ### Major Features and Improvements -* Profiling - * Provide easy to use apis for profiling start/stop and profiling data analyse (on Ascend only). - * Provide operators performance display and analysis on MindInsight UI. -* Large scale network computation graph visualization. -* Optimize summary record implementation and improve its performance. -* Improve lineage usability - * Optimize lineage display and enrich tabular operation. - * Decouple lineage callback from `SummaryRecord`. -* Support scalar compare of multiple runs. -* Scripts conversion from other frameworks - * Support for converting PyTorch scripts within TorchVision to MindSpore scripts automatically. +- Profiling + - Provide easy to use apis for profiling start/stop and profiling data analyse (on Ascend only). + - Provide operators performance display and analysis on MindInsight UI. +- Large scale network computation graph visualization. +- Optimize summary record implementation and improve its performance. +- Improve lineage usability + - Optimize lineage display and enrich tabular operation. + - Decouple lineage callback from `SummaryRecord`. +- Support scalar compare of multiple runs. +- Scripts conversion from other frameworks + - Support for converting PyTorch scripts within TorchVision to MindSpore scripts automatically. ### Bugfixes -* Fix pb files loaded problem when files are modified at the same time ([!53](https://gitee.com/mindspore/mindinsight/pulls/53)). -* Fix load data thread stuck in `LineageCacheItemUpdater` ([!114](https://gitee.com/mindspore/mindinsight/pulls/114)). -* Fix samples from previous steps erased due to tags size too large problem ([!86](https://gitee.com/mindspore/mindinsight/pulls/86)). -* Fix image and histogram event package error ([!1143](https://gitee.com/mindspore/mindspore/pulls/1143)). -* Equally distribute histogram ignoring actual step number to avoid large white space ([!66](https://gitee.com/mindspore/mindinsight/pulls/66)). +- Fix pb files loaded problem when files are modified at the same time ([!53](https://gitee.com/mindspore/mindinsight/pulls/53)). +- Fix load data thread stuck in `LineageCacheItemUpdater` ([!114](https://gitee.com/mindspore/mindinsight/pulls/114)). +- Fix samples from previous steps erased due to tags size too large problem ([!86](https://gitee.com/mindspore/mindinsight/pulls/86)). +- Fix image and histogram event package error ([!1143](https://gitee.com/mindspore/mindspore/pulls/1143)). +- Equally distribute histogram ignoring actual step number to avoid large white space ([!66](https://gitee.com/mindspore/mindinsight/pulls/66)). ### Thanks to our Contributors @@ -268,27 +268,27 @@ Chao Chen, Congli Gao, Ye Huang, Weifeng Huang, Zhenzhong Kou, Hongzhang Li, Lon Contributions of any kind are welcome! -# MindSpore 0.2.0-alpha Release Notes +# MindInsight 0.2.0-alpha -## MindInsight +## MindInsight 0.2.0 Release Notes ### Major Features and Improvements -* Parameter distribution graph (Histogram). +- Parameter distribution graph (Histogram). 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). -* Lineage support Custom information -* GPU support -* Model and dataset tracking linkage support +- Lineage support Custom information +- GPU support +- Model and dataset tracking linkage support ### Bugfixes -* Reduce cyclomatic complexity of `list_summary_directories` ([!11](https://gitee.com/mindspore/mindinsight/pulls/11)). -* Fix unsafe functions and duplication files and redundant codes ([!14](https://gitee.com/mindspore/mindinsight/pulls/14)). -* Fix sha256 checksum missing bug ([!24](https://gitee.com/mindspore/mindinsight/pulls/24)). -* Fix graph bug when node name is empty ([!34](https://gitee.com/mindspore/mindinsight/pulls/34)). -* Fix start/stop command error code incorrect ([!44](https://gitee.com/mindspore/mindinsight/pulls/44)). +- Reduce cyclomatic complexity of `list_summary_directories` ([!11](https://gitee.com/mindspore/mindinsight/pulls/11)). +- Fix unsafe functions and duplication files and redundant codes ([!14](https://gitee.com/mindspore/mindinsight/pulls/14)). +- Fix sha256 checksum missing bug ([!24](https://gitee.com/mindspore/mindinsight/pulls/24)). +- Fix graph bug when node name is empty ([!34](https://gitee.com/mindspore/mindinsight/pulls/34)). +- Fix start/stop command error code incorrect ([!44](https://gitee.com/mindspore/mindinsight/pulls/44)). ### Thanks to our Contributors @@ -298,12 +298,12 @@ Ye Huang, Weifeng Huang, Zhenzhong Kou, Pengting Luo, Hongzhang Li, Yongxiong Li Contributions of any kind are welcome! -# MindSpore 0.1.0-alpha Release Notes +# MindInsight 0.1.0-alpha -## MindInsight +## MindInsight 0.1.0 Release Notes -* Training process observation - * Provides and displays training process information, including computational graphs and training process indicators. +- Training process observation + - Provides and displays training process information, including computational graphs and training process indicators. -* Training result tracing - * Provides functions of tracing and visualizing model training parameter information, including filtering and sorting of training data, model accuracy and training hyperparameters. +- Training result tracing + - Provides functions of tracing and visualizing model training parameter information, including filtering and sorting of training data, model accuracy and training hyperparameters.