【开源实习】香橙派github仓中的在线推理案例05-ShuffleNet基于PyNative模式改写成以mint接口实现 #107
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Contributor
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部分方法没有修改成mint接口，包括但不限于nn.BatchNorm2d，nn.Conv2d等，需要再排查一遍以确保全部可以替换的均替换成mint接口实现。 |
Contributor
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案例中“运行环境设置”部分不必要的设置还是没有删除，尤其要求是动态图模式下执行该案例，只需要保留混合精度的设置ascend.op_precision.precision_mode("allow_mix_precision")。 |
Contributor
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目录orange-pi-mindspore，orange-pi-mindspore/Online, orange-pi-mindspore/Online/inference下的readme中均需修改案例版本信息 |
Contributor
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mindspore.mint.transpose(x, 2, 1)在CANN 8.1.RC1中会提示缺少算子，在CANN 8.1.RC1.beta1中可以正常运行--------针对这个问题transpose接口保持原接口实现即可 |
Author
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Contributor
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修改nn.BatchNorm2d以后会影响精度---针对这个问题，基于nn.BatchNorm2d和mint.nn.BatchNorm2d构造下单算子用例，然后同样的输入，开确定性，比一下输出 |
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任务
任务编号：#ICJ91O
任务链接：【开源实习】香橙派github仓中的在线推理案例05-ShuffleNet基于PyNative模式改写成以mint接口实现
版本信息:
Python 3.9 + MindSpore 2.6.0 + CANN 8.1.RC1
OrangePi AiPro 8G 8T
实现内容：
香橙派github仓中在线推理案例 05-ShuffleNet 基于MindSpore2.6.0的PyNative模式下可以在香橙派开发板正常流畅运行。
推理正常：
补充：
mindspore.mint.transpose(x, 2, 1)在CANN 8.1.RC1中会提示缺少算子，在CANN 8.1.RC1.beta1中可以正常运行