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7条答案
按热度按时间tp5buhyn1#
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!
vlurs2pr2#
只要GPU支持FP16的精度就可以实现AMP,看看您的gpu型号是否支持fp16,(补充需要Tensor Core)
9nvpjoqh3#
我用Tesla P100-SXM2,支持FP16,但用AMP后发现训练速度没什么变化,内存也是。
dojqjjoe4#
请问您的代码是怎么写的?
混合精度训练的代码可以参考: https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/performance_improving/amp_cn.html
5jdjgkvh5#
请问您的代码是怎么写的?
混合精度训练的代码可以参考: https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/performance_improving/amp_cn.html
我是训练ocr,按照这个指令训练的,没改到代码
https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.5/doc/doc_ch/recognition.md (“2.4 混合精度训练")
cwxwcias6#
在使用相同的超参数下,混合精度训练使用半精度浮点(FP16)和单精度(FP32)浮点即可达到与使用纯单精度训练相同的准确率,并可加速模型的训练速度,这主要得益于英伟达从Volta架构开始推出的Tensor Core技术。
paddleocr的问题,可以在ocr的repo提交issue。 https://github.com/PaddlePaddle/PaddleOCR/issues
a64a0gku7#
好的,谢谢!