torch to understand that the product can guidance schooling on ascending. The help position of the upper-order APIs Utilized in the design are available here Supported Checklist.
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自动并行：融合了数据并行、算子级模型并行的分布式并行模式，可以自动建立代价模型，找到训练时间较短的并行策略，为用户选择合适的并行模式。仅支持在图模式下使用。
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TorchVision interface aid: MindTorch TorchVision is a pc eyesight Device library migrated from PyTorch's official implementation. It continues to make use of PyTorch's official api design, and phone calls MindSpore operators for calculations to obtain a similar capabilities as the initial torchvision library.
PyTorch interface help: MindTorch aims to assistance the first expression of PyTorch syntax, end users just want to replace import torch in PyTorch resource code with import mindtorch.
from mindtorch.instruments import mstorch_enable # It has to be utilized right before https://mindtorch.org/ importing torch linked modules in the most crucial method
动态图模式下，程序按照代码的编写顺序执行，在执行正向过程中根据反向传播的原理，动态生成反向执行图。动态图模式方便编写和调试神经网络模型。
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PyTorch interface guidance scope: MindTorch is now mainly adapted to PyTorch data processing and model composition part of the code, currently totally supports MindSpore's PYNATIVE mode training, part of the community composition guidance GRAPH method schooling.
MindTorch is MindSpore Device for adapting the PyTorch interface, that's created to make PyTorch code execute effectively on Ascend with out changing the patterns of the initial PyTorch consumers.
Consult with the Person Guidebook, you will speedily get started and finish the transformation from PyTorch code, in addition to get rolling with numerous State-of-the-art optimization abilities; Additional over, Should you have requirements for precision and functionality tuning, be sure to make reference to the Debugging and Tuning Information.
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