API improvement for paddle.linalg.svd_lowrank #62876
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你的PR提交成功，感谢你对开源项目的贡献! |
| C = self.random_matrix(rank, columns, *batch_dims, **kwargs) | ||
| return B.matmul(C) | ||
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| def run_subtest( |
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numpy有计算svd_lowrank的API吗，如果有的话，单测对比结果时 可以简洁一些
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numpy没有直接计算svd_lowrank的API，这个是复用了test_pca_lowrank的代码，是不是直接在test_pca_lowrank增加svd_lowrank测试案例更好一点
zhwesky2010
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Sorry to inform you that ccdb50c's CIs have passed for more than 7 days. To prevent PR conflicts, you need to re-run all CIs manually. |
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@NKNaN 看一下CI未通过的原因 |
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@zhwesky2010 是超过7天，Paddle-bot自动标记fail了，重新rerun或者merge下develop就好了 |
python/paddle/tensor/linalg.py
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| zero or more batch dimensions. N and M can be arbitrary positive number. | ||
| The data type of ``x`` should be float32 or float64. | ||
| q (int, optional): A slightly overestimated rank of :math:`X`. | ||
| Default value is :math:`q=min(6,N,M)`. |
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这里的默认值，和在函数定义 def svd_lowrank(x, q=None, niter=2, M=None, name=None): 里 q=None 是不是冲突了？辛苦看一下
* add svd lowrank api * add test * fix param M * fix test timeout * update docs
PR Category
User Experience
PR Types
Improvements
Description
将 paddle 的 linalg.py 中已有的 svd_lowrank 函数计算逻辑公开出来，对照 pytorch: https://pytorch.org/docs/stable/generated/torch.svd_lowrank.html