forked from mindspore-Ecosystem/mindspore
Update some docs
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@ -70,6 +70,7 @@ MindSpore offers build options across multiple backends:
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| | EulerOS-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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| | Windows-x86 | ✔️ |
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For installation using `pip`, take `CPU` and `Ubuntu-x86` build version as an example:
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@ -179,7 +180,7 @@ currently the containerized build options are supported as follows:
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from mindspore import Tensor
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from mindspore.ops import functional as F
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context.set_context(device_target="GPU")
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
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x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
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y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
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@ -24,11 +24,8 @@
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MindSpore是一种适用于端边云场景的新型开源深度学习训练/推理框架。
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MindSpore提供了友好的设计和高效的执行,旨在提升数据科学家和算法工程师的开发体验,并为Ascend AI处理器提供原生支持,以及软硬件协同优化。
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同时,MindSpore作为全球AI开源社区,致力于进一步开发和丰富AI软硬件应用生态。
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<img src="docs/MindSpore-architecture.png" alt="MindSpore Architecture" width="600"/>
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欲了解更多详情,请查看我们的[总体架构](https://www.mindspore.cn/docs/zh-CN/master/architecture.html)。
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@ -70,6 +67,7 @@ MindSpore提供跨多个后端的构建选项:
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| | EulerOS-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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| | Windows-x86 | ✔️ |
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使用`pip`命令安装,以`CPU`和`Ubuntu-x86`build版本为例:
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@ -178,7 +176,7 @@ MindSpore的Docker镜像托管在[Docker Hub](https://hub.docker.com/r/mindspore
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from mindspore import Tensor
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from mindspore.ops import functional as F
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context.set_context(device_target="GPU")
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
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x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
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y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
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@ -226,7 +224,6 @@ MindSpore的Docker镜像托管在[Docker Hub](https://hub.docker.com/r/mindspore
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欢迎参与贡献。更多详情,请参阅我们的[贡献者Wiki](CONTRIBUTING.md)。
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## 版本说明
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版本说明请参阅[RELEASE](RELEASE.md)。
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@ -28,7 +28,7 @@
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* change IndexedSlices to RowTensor([!4031](https://gitee.com/mindspore/mindspore/pulls/4031))
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* Must set or change parallel mode before any Initializer created([!4801](https://gitee.com/mindspore/mindspore/pulls/4801))
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* Executor and performance optimization
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* Minspore graph compilation process performance improved by 20%.
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* MindSpore graph compilation process performance improved by 20%.
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* Decoupling C++ and Python modules to achieve separate compilation of core modules.
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* Data processing, augmentation, and save format
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* Support automatic data augmentation
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@ -52,7 +52,7 @@
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### MindSpore Lite
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* Converter
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* Support third party model, including TFLite/Caffe/ONNX.
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* Support third-party models, including TFLite/Caffe/ONNX.
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* Add 93 TFLite op.
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* Add 24 Caffe op.
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* Add 62 ONNX op.
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