torch to realize that the model can help instruction on ascending. The aid status of the higher-buy APIs Employed in the model can be found listed here Supported Record.
方式一：采用即时编译装饰器jit，使能部分函数粒度表达模块以静态图模式执行。
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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 guidance: MindTorch TorchVision is a pc vision Device library migrated from PyTorch's official implementation. It continues to utilize PyTorch's official api style, and phone calls MindSpore operators for https://mindtorch.org/ calculations to obtain the same features as the original torchvision library.
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数据并行：对数据进行切分的并行模式，一般按照batch维度切分，将数据分配到各个计算单元中，进行模型计算。
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 information processing and model structure A part of the code, at present completely supports MindSpore's PYNATIVE mode coaching, A part of the network composition aid GRAPH method education.
MindTorch is MindSpore Resource for adapting the PyTorch interface, that's intended to make PyTorch code execute effectively on Ascend with out changing the patterns of the initial PyTorch consumers.
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MSAdapter can be a MindSpore ecological adaptation Device, which promptly migrates a few-occasion framework code which include PyTorch/JAX to the MindSpore ecosystem with out modifying the user's authentic usage patterns, helping users competently utilize the Ascend computing electric power with the China Computing Internet.