version update to 1.0.0
This commit is contained in:
parent
71b5791aa1
commit
769a1316ad
12
README.md
12
README.md
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@ -69,6 +69,8 @@ MindSpore offers build options across multiple backends:
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| | Ubuntu-aarch64 | ✔️ |
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| | EulerOS-x86 | ✔️ |
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| | EulerOS-aarch64 | ✔️ |
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| | CentOS-x86 | ✔️ |
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| | CentOS-aarch64 | ✔️ |
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| GPU CUDA 10.1 | Ubuntu-x86 | ✔️ |
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| CPU | Ubuntu-x86 | ✔️ |
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| | Ubuntu-aarch64 | ✔️ |
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@ -79,7 +81,7 @@ For installation using `pip`, take `CPU` and `Ubuntu-x86` build version as an ex
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1. Download whl from [MindSpore download page](https://www.mindspore.cn/versions/en), and install the package.
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```
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pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/0.7.0-beta/MindSpore/cpu/ubuntu_x86/mindspore-0.7.0-cp37-cp37m-linux_x86_64.whl
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pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/MindSpore/cpu/ubuntu_x86/mindspore-1.0.0-cp37-cp37m-linux_x86_64.whl
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```
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2. Run the following command to verify the install.
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@ -136,8 +138,8 @@ currently the containerized build options are supported as follows:
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For `CPU` backend, you can directly pull and run the latest stable image using the below command:
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```
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docker pull mindspore/mindspore-cpu:0.7.0-beta
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docker run -it mindspore/mindspore-cpu:0.7.0-beta /bin/bash
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docker pull mindspore/mindspore-cpu:1.0.0
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docker run -it mindspore/mindspore-cpu:1.0.0 /bin/bash
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```
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* GPU
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@ -170,8 +172,8 @@ currently the containerized build options are supported as follows:
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```
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Then you can pull and run the latest stable image using the below command:
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```
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docker pull mindspore/mindspore-gpu:0.7.0-beta
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docker run -it --runtime=nvidia --privileged=true mindspore/mindspore-gpu:0.7.0-beta /bin/bash
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docker pull mindspore/mindspore-gpu:1.0.0
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docker run -it --runtime=nvidia --privileged=true mindspore/mindspore-gpu:1.0.0 /bin/bash
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```
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To test if the docker image works, please execute the python code below and check the output:
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12
README_CN.md
12
README_CN.md
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@ -66,6 +66,8 @@ MindSpore提供跨多个后端的构建选项：
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| | Ubuntu-aarch64 | ✔️ |
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| | EulerOS-x86 | ✔️ |
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| | EulerOS-aarch64 | ✔️ |
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| | CentOS-x86 | ✔️ |
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| | CentOS-aarch64 | ✔️ |
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| GPU CUDA 10.1 | Ubuntu-x86 | ✔️ |
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| CPU | Ubuntu-x86 | ✔️ |
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| | Ubuntu-aarch64 | ✔️ |
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@ -76,7 +78,7 @@ MindSpore提供跨多个后端的构建选项：
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1. 请从[MindSpore下载页面](https://www.mindspore.cn/versions)下载并安装whl包。
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```
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pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/0.7.0-beta/MindSpore/cpu/ubuntu_x86/mindspore-0.7.0-cp37-cp37m-linux_x86_64.whl
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pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/MindSpore/cpu/ubuntu_x86/mindspore-1.0.0-cp37-cp37m-linux_x86_64.whl
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```
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2. 执行以下命令，验证安装结果。
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@ -132,8 +134,8 @@ MindSpore的Docker镜像托管在[Docker Hub](https://hub.docker.com/r/mindspore
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对于`CPU`后端，可以直接使用以下命令获取并运行最新的稳定镜像：
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```
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docker pull mindspore/mindspore-cpu:0.7.0-beta
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docker run -it mindspore/mindspore-cpu:0.7.0-beta /bin/bash
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docker pull mindspore/mindspore-cpu:1.0.0
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docker run -it mindspore/mindspore-cpu:1.0.0 /bin/bash
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```
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* GPU
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@ -166,8 +168,8 @@ MindSpore的Docker镜像托管在[Docker Hub](https://hub.docker.com/r/mindspore
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```
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使用以下命令获取并运行最新的稳定镜像：
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```
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docker pull mindspore/mindspore-gpu:0.7.0-beta
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docker run -it --runtime=nvidia --privileged=true mindspore/mindspore-gpu:0.7.0-beta /bin/bash
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docker pull mindspore/mindspore-gpu:1.0.0
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docker run -it --runtime=nvidia --privileged=true mindspore/mindspore-gpu:1.0.0 /bin/bash
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```
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要测试Docker是否正常工作，请运行下面的Python代码并检查输出：
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104
RELEASE.md
104
RELEASE.md
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@ -1,3 +1,107 @@
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# Release 1.0.0
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## Major Features and Improvements
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### MindSpore Training and Inference Framework
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#### Ascend 910
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* New models
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* Mask-RCNN: a simple and flexible deep neural network for object instance segmentation on COCO 2014 dataset.
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* DenseNet121: a dense convolutional neural network, which connects each layer to every other layer in a feed-forward fashion for object recognition on ImageNet dataset.
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* PSENet: accurately detect arbitrary shape text instances and get better results on CTW1500, full text, ICDAR 2015, and ICDAR 2017 MLT datasets.
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* UNet2D-Medical: Unet Medical model for 2D image segmentation, Convolutional Networks for Biomedical Image Segmentation on ISBI Challenge database.
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* Frontend and user interface
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* Second-Order Optimization
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* Enable second-order optimization for Bert on Ascend 910, which can achieve a masked lm accuracy of 71.3% in 1000 seconds using 8 Ascend 910 (Bert-Large @MLPerf v0.7 dataset).
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* New GNN model BGCF
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* Bayesian Graph Convolutional Filtering network which naturally incorporate the uncertainty in the user-item interaction graph shows excellent recommendation performance on Amazon-Beauty dataset.
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* Add append interface for SequentialCell.
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* Add a level `auto` for AMP.
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* Executor and performance optimization
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* Support quantitative network (Resnet50 & YoloV3 & MobileNetV2).
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* Project ease of use optimization: project compilation time optimization, CMakelist regularization, cudnn, cuda independent compilation and installation independent.
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* Data processing, augmentation, and save format
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* Support GeneratorDataset return string type
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#### Other Hardware Support
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* GPU platform
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* New model supported: TinyBert, ShuffleNet, YoloV3-DarkNet53, EfficientNet-B0, NASNet-Mobile and Transformer.
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* Enable second-order optimization for resnet50 on GPU, which achieve 20% improvement on training time compared to SGD with Momentum (Resnet50 @ImageNet).
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* CPU platform
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* ...
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#### User interfaces change log
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* Remove global object GradOperation in Autodiff([!5011](https://gitee.com/mindspore/mindspore/pulls/5011))
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* Remove useless attribute 'name' in Autodiff([!5172](https://gitee.com/mindspore/mindspore/pulls/5172))
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* Rectification distributed init([!5350](https://gitee.com/mindspore/mindspore/pulls/5350))
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* Move the setting of ParalleMode from train.parallel_utils to context([!5351](https://gitee.com/mindspore/mindspore/pulls/5351))
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* Modification of save_checkpoint([!5482](https://gitee.com/mindspore/mindspore/pulls/5482))
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* Wrap numpy random seed into an api([!5634](https://gitee.com/mindspore/mindspore/pulls/5634))
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* Delete enable_fused_layernorm in some modelzoo scripts([!5665](https://gitee.com/mindspore/mindspore/pulls/5665))
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* Move 'multi-subgraphs' interface to internal([!5696](https://gitee.com/mindspore/mindspore/pulls/5696))
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* Rename mirror_mean to gradient_mean([!5700](https://gitee.com/mindspore/mindspore/pulls/5700))
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* Remove default value of 'group' of DepthWiseConv2d([!5865](https://gitee.com/mindspore/mindspore/pulls/5865))
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* Modify interface for function and remove duplicated def([!5958](https://gitee.com/mindspore/mindspore/pulls/5958))
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* Unify Conv2d and DepthwiseConv2d([!5916](https://gitee.com/mindspore/mindspore/pulls/5916))
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* Modification of SoftmaxCrossEntropyWithLogits([!5502](https://gitee.com/mindspore/mindspore/pulls/5502))
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* Change API set_strategy() to shard()([!5991](https://gitee.com/mindspore/mindspore/pulls/5991))
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* Move batch_size from bert_cfg_cfg to cfg([!6233](https://gitee.com/mindspore/mindspore/pulls/6233))
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* Remove unused parameters from SummaryRecord __init__([!5548](https://gitee.com/mindspore/mindspore/pulls/5548))
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* remove sens parameter of TrainOneStepWithLossScaleCell([!5753](https://gitee.com/mindspore/mindspore/pulls/5753))
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* optimize the TrainOneStepCell for user's define([!6159](https://gitee.com/mindspore/mindspore/pulls/6159))
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* delete seed0 and seed1 of nn.Dropout([!5735](https://gitee.com/mindspore/mindspore/pulls/5735))
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* delete DataWrapper([!6101](https://gitee.com/mindspore/mindspore/pulls/6101))
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* LSTM API optimization([!6374](https://gitee.com/mindspore/mindspore/pulls/6374))
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* Merge P\C\F of ops([!5645](https://gitee.com/mindspore/mindspore/pulls/5645))
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* Log optimization([!5842](https://gitee.com/mindspore/mindspore/pulls/5842))
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* Remove useless API dataset.set_dataset_size（[!5806](https://gitee.com/mindspore/mindspore/pulls/5806))
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* Some of Dataset API add usage parameter（[!5605](https://gitee.com/mindspore/mindspore/pulls/5605))
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* Change the import path, such as from mindspore.dataset.transforms.vision to mindspore.dataset.vision.transforms（[!5384](https://gitee.com/mindspore/mindspore/pulls/5384))
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* Rename ImageFolderDatasetV2 to ImageFolderDataset（[!5384](https://gitee.com/mindspore/mindspore/pulls/5384))
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* Dataset.map parameter optimization（[!5384](https://gitee.com/mindspore/mindspore/pulls/5384))
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* Add new api dataset.get_col_names（[!5384](https://gitee.com/mindspore/mindspore/pulls/5384))
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* Add new api dataset.get_col_names（[!5384](https://gitee.com/mindspore/mindspore/pulls/5384))
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* Remove useless API MindRecord finish（[!5580](https://gitee.com/mindspore/mindspore/pulls/5580))
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### MindSpore Lite
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* Converter
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* Add 6 TFLite op, 7 Caffe op, 1 ONNX op.
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* Add support for Windows.
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* Support parallel inference of multiple sessions to adapt to more scenarios
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* Support 8bits only weight-quantization, most main-stream models has small accuracy loss (less than 0.5%) when compared to non-qunantized fp32 model.
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* CPU & GPU
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* Add 20 CPU ops，include FP32, int8/uint8, FP16 and int32 ops.
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* Add supporting FP16 for GPU, add 14 GPU ops include FP32/FP16.
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* Add Buffer/Image2D transform op for GPU
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* Performance optimization for CPU ops focus on ARM32.
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* Performance optimization for GPU Convolution using winograd.
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* Tool & example
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* Add object detection Android Demo.
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## Bugfixes
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* Models
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* Python API
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* fix semi auto parallel parameter of reshape has another user([!5722](https://gitee.com/mindspore/mindspore/pulls/5722))
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* raise ValueError when call hook function in graph mode([!5831](https://gitee.com/mindspore/mindspore/pulls/5831))
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* Executor
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* Bugfix pynative mode to build temporary nn objects.（[!6189](https://gitee.com/mindspore/mindspore/pulls/6189))
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* Bugfix the accuracy problem of multiple inputs of multi-card communication operator broadcast.([!6522](https://gitee.com/mindspore/mindspore/pulls/5622))
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* Bugfix the problem that the sample distribution interface categorical does not support graph mode.([!5772](https://gitee.com/mindspore/mindspore/pulls/5772))
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* Bugfix the random seed failure problem of the polynomial downsampling distribution operator.([!5948](https://gitee.com/mindspore/mindspore/pulls/5948))
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* Bugfix unnecessary address binding issues in GPU heterogeneous scenarios.([!6232](https://gitee.com/mindspore/mindspore/pulls/6232))
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* GPU platform
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* Bugfix for kernel resource leak([!5315](https://gitee.com/mindspore/mindspore/pulls/5315))
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* Bugfix for insufficient memory for continuous unit test running([!5617](https://gitee.com/mindspore/mindspore/pulls/5617))
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* Bugfix for the memory leak in the sparse slicer([!5578](https://gitee.com/mindspore/mindspore/pulls/5578))
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* Data processing and Pro
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* ...
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## Contributors
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Thanks goes to these wonderful people:
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Adel, AGroupofProbiotocs, anthonyaje, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, danish, Danish, dayschan, eric, Eric, fary86, fuzhiye, Gaoxiong, gengdongjie, gongdaguo, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huzhifeng, hwjiaorui, Jesse, jianghui58, jiangzhiwen, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, Jonathan, jonyguo, jzg, kai00, kingfo, kingxian, kpy, kswang, laiyongqiang, leonwanghui, Li, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luoyang, lvchangquan, lvliang, lz, mahdi, Mahdi, maning202007, Margaret_wangrui, mayang, mengyuanli, nhussain, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, r1chardf1d0, riemann_penn, root, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin, wangnan39@huawei.com, wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wukesong, wuweikang, wuxuejian, Xiaoda, xiefangqi, xuanyue, xulei2020, Xun, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang, zhanghaibo5@huawei.com, zhanghuiyao, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhoufeng, zhousiyi, zhouyaqiang, Zichun, Zirui, Ziyan, zjun, ZPaC
|
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|
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Contributions of any kind are welcome!
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# Release 0.7.0-beta
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## Major Features and Improvements
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|
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@ -0,0 +1,67 @@
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FROM ubuntu:18.04
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MAINTAINER leonwanghui <leon.wanghui@huawei.com>
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# Set env
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ENV PYTHON_ROOT_PATH /usr/local/python-3.7.5
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ENV PATH /usr/local/bin:$PATH
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# Install base tools
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RUN apt update \
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&& DEBIAN_FRONTEND=noninteractive apt install -y \
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vim \
|
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wget \
|
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curl \
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xz-utils \
|
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net-tools \
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openssh-client \
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git \
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ntpdate \
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tzdata \
|
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tcl \
|
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sudo \
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bash-completion
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||||
|
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# Install compile tools
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RUN DEBIAN_FRONTEND=noninteractive apt install -y \
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gcc \
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g++ \
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zlibc \
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make \
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libgmp-dev \
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patch \
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autoconf \
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libtool \
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automake \
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flex
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|
||||
# Set bash
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RUN echo "dash dash/sh boolean false" | debconf-set-selections
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RUN DEBIAN_FRONTEND=noninteractive dpkg-reconfigure dash
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# Install python (v3.7.5)
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RUN apt install -y libffi-dev libssl-dev zlib1g-dev libbz2-dev libncurses5-dev \
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libgdbm-dev libgdbm-compat-dev liblzma-dev libreadline-dev libsqlite3-dev \
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&& cd /tmp \
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&& wget https://github.com/python/cpython/archive/v3.7.5.tar.gz \
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&& tar -xvf v3.7.5.tar.gz \
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&& cd /tmp/cpython-3.7.5 \
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||||
&& mkdir -p ${PYTHON_ROOT_PATH} \
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&& ./configure --prefix=${PYTHON_ROOT_PATH} \
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&& make -j4 \
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&& make install -j4 \
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&& rm -f /usr/local/bin/python \
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||||
&& rm -f /usr/local/bin/pip \
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&& ln -s ${PYTHON_ROOT_PATH}/bin/python3.7 /usr/local/bin/python \
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&& ln -s ${PYTHON_ROOT_PATH}/bin/pip3.7 /usr/local/bin/pip \
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&& rm -rf /tmp/cpython-3.7.5 \
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&& rm -f /tmp/v3.7.5.tar.gz
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||||
# Set pip source
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||||
RUN mkdir -pv /root/.pip \
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||||
&& echo "[global]" > /root/.pip/pip.conf \
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&& echo "trusted-host=mirrors.aliyun.com" >> /root/.pip/pip.conf \
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&& echo "index-url=http://mirrors.aliyun.com/pypi/simple/" >> /root/.pip/pip.conf
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|
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# Install MindSpore cpu whl package
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RUN pip install --no-cache-dir https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/MindSpore/cpu/ubuntu_x86/mindspore-1.0.0-cp37-cp37m-linux_x86_64.whl
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|
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@ -0,0 +1,81 @@
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FROM nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04
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|
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MAINTAINER leonwanghui <leon.wanghui@huawei.com>
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|
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# Set env
|
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ENV PYTHON_ROOT_PATH /usr/local/python-3.7.5
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ENV OMPI_ROOT_PATH /usr/local/openmpi-3.1.5
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ENV PATH ${OMPI_ROOT_PATH}/bin:/usr/local/bin:$PATH
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ENV LD_LIBRARY_PATH ${OMPI_ROOT_PATH}/lib:$LD_LIBRARY_PATH
|
||||
|
||||
# Install base tools
|
||||
RUN apt update \
|
||||
&& DEBIAN_FRONTEND=noninteractive apt install -y \
|
||||
vim \
|
||||
wget \
|
||||
curl \
|
||||
xz-utils \
|
||||
net-tools \
|
||||
openssh-client \
|
||||
git \
|
||||
ntpdate \
|
||||
tzdata \
|
||||
tcl \
|
||||
sudo \
|
||||
bash-completion
|
||||
|
||||
# Install compile tools
|
||||
RUN DEBIAN_FRONTEND=noninteractive apt install -y \
|
||||
gcc \
|
||||
g++ \
|
||||
zlibc \
|
||||
make \
|
||||
libgmp-dev \
|
||||
patch \
|
||||
autoconf \
|
||||
libtool \
|
||||
automake \
|
||||
flex
|
||||
|
||||
# Set bash
|
||||
RUN echo "dash dash/sh boolean false" | debconf-set-selections
|
||||
RUN DEBIAN_FRONTEND=noninteractive dpkg-reconfigure dash
|
||||
|
||||
# Install python (v3.7.5)
|
||||
RUN apt install -y libffi-dev libssl-dev zlib1g-dev libbz2-dev libncurses5-dev \
|
||||
libgdbm-dev libgdbm-compat-dev liblzma-dev libreadline-dev libsqlite3-dev \
|
||||
&& cd /tmp \
|
||||
&& wget https://github.com/python/cpython/archive/v3.7.5.tar.gz \
|
||||
&& tar -xvf v3.7.5.tar.gz \
|
||||
&& cd /tmp/cpython-3.7.5 \
|
||||
&& mkdir -p ${PYTHON_ROOT_PATH} \
|
||||
&& ./configure --prefix=${PYTHON_ROOT_PATH} \
|
||||
&& make -j4 \
|
||||
&& make install -j4 \
|
||||
&& rm -f /usr/local/bin/python \
|
||||
&& rm -f /usr/local/bin/pip \
|
||||
&& ln -s ${PYTHON_ROOT_PATH}/bin/python3.7 /usr/local/bin/python \
|
||||
&& ln -s ${PYTHON_ROOT_PATH}/bin/pip3.7 /usr/local/bin/pip \
|
||||
&& rm -rf /tmp/cpython-3.7.5 \
|
||||
&& rm -f /tmp/v3.7.5.tar.gz
|
||||
|
||||
# Set pip source
|
||||
RUN mkdir -pv /root/.pip \
|
||||
&& echo "[global]" > /root/.pip/pip.conf \
|
||||
&& echo "trusted-host=mirrors.aliyun.com" >> /root/.pip/pip.conf \
|
||||
&& echo "index-url=http://mirrors.aliyun.com/pypi/simple/" >> /root/.pip/pip.conf
|
||||
|
||||
# Install openmpi (v3.1.5)
|
||||
RUN cd /tmp \
|
||||
&& wget https://download.open-mpi.org/release/open-mpi/v3.1/openmpi-3.1.5.tar.gz \
|
||||
&& tar -xvf openmpi-3.1.5.tar.gz \
|
||||
&& cd /tmp/openmpi-3.1.5 \
|
||||
&& mkdir -p ${OMPI_ROOT_PATH} \
|
||||
&& ./configure --prefix=${OMPI_ROOT_PATH} \
|
||||
&& make -j4 \
|
||||
&& make install -j4 \
|
||||
&& rm -rf /tmp/openmpi-3.1.5 \
|
||||
&& rm -f /tmp/openmpi-3.1.5.tar.gz
|
||||
|
||||
# Install MindSpore cuda-10.1 whl package
|
||||
RUN pip install --no-cache-dir https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/MindSpore/gpu/ubuntu_x86/cuda-10.1/mindspore_gpu-1.0.0-cp37-cp37m-linux_x86_64.whl
|
||||
2
setup.py
2
setup.py
|
|
@ -23,7 +23,7 @@ from setuptools import setup, find_packages
|
|||
from setuptools.command.egg_info import egg_info
|
||||
from setuptools.command.build_py import build_py
|
||||
|
||||
version = '0.7.0'
|
||||
version = '1.0.0'
|
||||
|
||||
backend_policy = os.getenv('BACKEND_POLICY')
|
||||
device_target = os.getenv('BACKEND_TARGET')
|
||||
|
|
|
|||
Loading…
Reference in New Issue