【Hackathon 8th No.1】add lu_solve api for paddle
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感谢你贡献飞桨文档，文档预览构建中，Docs-New 跑完后即可预览，预览链接：http://preview-pr-7052.paddle-docs-preview.paddlepaddle.org.cn/documentation/docs/zh/api/index_cn.html |
不用了，该写的都写了 |
zhwesky2010
reviewed
Mar 10, 2025
| - **b** (Tensor) - 输入的欲进行线性方程组求解的右值，类型为 Tensor。 ``b`` 的形状应为 ``[*, M, K]``，其中 ``*`` 为零或更大的批次维度，数据类型为 float32， float64。 | ||
| - **lu** (Tensor) - LU 分解结果矩阵，由 L、U 拼接组成，类型为 Tensor。 ``lu`` 的形状应为 ``[*, M, M]``，其中 ``*`` 为零或更大的批次维度。数据类型和 ``b`` 相同。 | ||
| - **pivots** (Tensor) - LU 分解结果的主元信息，类型为 Tensor。 ``pivots`` 的形状应为 ``[*, M]``，其中 ``*`` 为零或更大的批次维度。数据类型为 int32。 | ||
| - **trans** (str，可选) - 是否对 A 进行转置，默认值为 N。 |
| .. math:: | ||
| b = A * X | ||
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| 当 `trans` 为 `T` 时，公式为： |
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| | PyTorch | PaddlePaddle | 备注 | | ||
| | ------- | ------------ | ----------------------------------------------------- | | ||
| | B | b | 表示欲进行线性方程组求解的右值 Tensor ，仅参数名不一致。 | |
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参数顺序以Pytorch的为主，第一个是LU
| | B | b | 表示欲进行线性方程组求解的右值 Tensor ，仅参数名不一致。 | | ||
| | pivots | pivots | 表示 LU 分解结果的主元信息 Tensor 。 | | ||
| | LU | lu | 表示 LU 分解结果矩阵，由 L、U 拼接组成，仅参数名不一致。 | | ||
| | left | - | 表示待求解向量是否在左侧， Paddle 无此参数，暂无转写方式。| |
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这个可以转写吧，根据你之前的描述，可以利用转置来变换公式，将左边变换到右边
| | pivots | pivots | 表示 LU 分解结果的主元信息 Tensor 。 | | ||
| | LU | lu | 表示 LU 分解结果矩阵，由 L、U 拼接组成，仅参数名不一致。 | | ||
| | left | - | 表示待求解向量是否在左侧， Paddle 无此参数，暂无转写方式。| | ||
| | adjoint | trans | 表示是否使用转置 LU 分解结果， PyTorch 为 bool 类型，Paddle 为 str 类型，需要转写。| |
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这个应该是共轭转置？adjoint=True时对应tranc='C'
| | LU | lu | 表示 LU 分解结果矩阵，由 L、U 拼接组成，仅参数名不一致。 | | ||
| | left | - | 表示待求解向量是否在左侧， Paddle 无此参数，暂无转写方式。| | ||
| | adjoint | trans | 表示是否使用转置 LU 分解结果， PyTorch 为 bool 类型，Paddle 为 str 类型，需要转写。| | ||
| | out | - | 表示输出的 Tensor 元组 ， Paddle 无此参数，需要转写。 | |
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有四种情况下的转写，看看是不是这样变换的：
x=torch.linalg.lu_solve(lu, pivots, b) -> x=paddle.lu_solve(b, lu, pivots)
x=torch.linalg.lu_solve(lu, pivots, b, adjoint=True) -> x=paddle.lu_solve(b, lu, pivots, trans=‘C’)
x=torch.linalg.lu_solve(lu, pivots, b, left=False) -> x=paddle.lu_solve(b^H, lu, pivots, trans=‘C’)^H
X A=b -> A^H X^H=b^H
x=torch.linalg.lu_solve(lu, pivots, b, left=False, adjoint=True) -> x=paddle.lu_solve(b^H, lu, pivots)^H
X A^H=b -> A X^H=b^H
| paddle.assign(y, A) | ||
| ``` | ||
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| #### adjoint |
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adjoint与left的四种组合情况转写
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adjoint与left的四种组合情况转写
已经都改好了
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