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paddle.linalg.expm API #36563
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您好,我们已经收到了您的问题,会安排技术人员尽快解答您的问题,请耐心等待。请您再次检查是否提供了清晰的问题描述、复现代码、环境&版本、报错信息等。同时,您也可以通过查看官网API文档、常见问题、历史Issue、AI社区来寻求解答。祝您生活愉快~ Hi! We've received your issue and please be patient to get responded. We will arrange technicians to answer your questions as soon as possible. Please make sure that you have posted enough message to demo your request. You may also check out the API,FAQ,Github Issue and AI community to get the answer.Have a nice day! |
您好,您的反馈对产品非常有价值,我们内部会安排评估,未来有计划尽快回复。目前Paddle2.1及以上的动态图支持 |
可以试下 paddle.linalg.matrix_power 文档:https://www.paddlepaddle.org.cn/documentation/docs/zh/api/paddle/linalg/matrix_power_cn.html torch
paddle
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@firestonelib 这个应该是目前SOTA的matrix exponential的算法。 如果您有开发这个API的计划,我们可以更进一步进行一下细节上的交流。 @firestonelib That is why torch implement the algorithm in the paper "Bader, P.; Blanes, S.; Casas, F. Computing the Matrix Exponential with an Optimized Taylor Polynomial Approximation. Mathematics 2019, 7, 1174." Although there is a lot of algorithms to calcuate matrix exponential, it's seems like the Bader's paper is the state-of-the-art solution. If you have a plan for this API, we can have a further discussion about the implemetaion details. |
You are very welcome to submit implementation of this API to us. You can refer to the requirements of the new API(such as rfc, code and docs) in our current Hackathon, and we can arrange experts to review and discuss. |
请问paddle 预期什么时候实现 paddle.linalg.expm 这个api
等同于
scipy.linalg.expm
以及:
torch.matrix_exp
https://pytorch.org/docs/stable/generated/torch.matrix_exp.html
e的矩阵次方
或者动态图开放类似于 torch.autograd.Function 的功能,可以自己python定义op,不用写c再编译。
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