【Paddle Toolkit Development Competition No.3】 Paddle 适配 neuralopfiles via upload #985
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| tensorly支持Paddle后端，但是在编写代码时发生了如下错误： | ||
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| ```python | ||
| import tensorly as tl | ||
| tl.set_backend('paddle') | ||
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| ValueError:Unknown backend name 'paddle', known backends are ['numpy', 'mxnet', 'pytorch', 'tensorflow', 'cupy', 'jax'] | ||
| ``` |
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tensorly可能需要使用源码安装的方式，因为paddle支持的代码tensoly官方尚未发布到pypi上
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| `neuraloperator`源代码实现的8个模型分别为, `FNO1d`, `FNO2d`, `FNO3d`, `SFNO`, `UNO`, `TFNO1d`, `TFNO2d`, `TFNO3d`。 | ||
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8个模型只是一部分吧，neuralop需要适配的内容应该是除了training外的所有代码
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我们针对模型的数量是8个 但其他所有文件也都适配了 而且我们也适配了training过程
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| 由于模型`UFNO(layers=1)`时的训练结果是对齐的，因此初步判断模型UFNO（layers=5）时出现的问题是由误差累积引起的。目前该问题尚未解决。 |
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误差累积不太可能会这么大，可以尝试使用https://github.com/PaddlePaddle/PaDiff工具，定位一下具体的误差累积在哪一层，然后看下是什么API的计算导致的误差变化
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hello @Kai-Qi 可以修改一RFC的内容，在文档中补充需要适配的API列表和单测列表 |
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飞桨适配 nueralop
https://competition.atomgit.com/competitionInfo?id=805ad94637707d062f24e54265d85731