[英]sagemaker - factorization machines - deserialize model
I estimated a factorization machine model in sagemaker and it saved a file model.tar.gz
into an s3 folder.我在 sagemaker 中估计了一个分解机模型,并将文件
model.tar.gz
保存到 s3 文件夹中。
Is there a way I can load this file in Python and access the parameter of the model, ie the factors, directly?有没有办法可以在 Python 中加载这个文件并直接访问模型的参数,即因子?
Thanks谢谢
As of April 2019: yes.截至 2019 年 4 月:是的。 An official AWS blog post was created to show how to open the SageMaker Factorization Machines artifact and extract its parameters: https://aws.amazon.com/blogs/machine-learning/extending-amazon-sagemaker-factorization-machines-algorithm-to-predict-top-x-recommendations/
创建了一篇官方 AWS 博客文章以展示如何打开 SageMaker Factorization Machines 工件并提取其参数: https ://aws.amazon.com/blogs/machine-learning/extending-amazon-sagemaker-factorization-machines-algorithm- to-predict-top-x-recommendations/
That being said, be aware that Amazon SageMaker built-in algorithm are primarily built for deployment on AWS, and only SageMaker XGBoost and SageMaker BlazingText are designed to produce artifacts interoperable with their open-source equivalent.话虽如此,请注意 Amazon SageMaker 内置算法主要是为在 AWS 上部署而构建的,只有SageMaker XGBoost和SageMaker BlazingText旨在生成可与其开源等效项互操作的工件。
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