Comments (4)
Can I pick the GPU that I want to run on?
Certainly, you can sellect GPU by
python run_recbole.py --gpu_id=1
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Currently, RecBole has not developed or tested to adapt to distributed training and evaluation. We may add this feature in the future. Track #486 to keep an eye on this.
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Can I pick the GPU that I want to run on?
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Hello @dxjjhm , we have released the 1.1.1 version of RecBole on Oct 5 2022, and the distributed training and evaluation is supported in our framework now. You can refer to our documentation for more details and running examples.
Thank you very much for your attention and kindly advice! The suggestions and feedback from open source users are our driving force for continuous updating. We welcome you very much to use our library again and give your valuable comments.
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Related Issues (20)
- 请问现在伯乐支持少样本学习吗?
- [🐛BUG] LightGCN在ml-100k数据集上性能不佳 HOT 6
- Parameters of HyperTuning
- [🐛BUG] Error running LightGCN
- [🐛BUG] 顺序推荐模型在使用带有label标签的数据集并且使用排序评价指标(如NDCG)的时候会发生报错。 HOT 2
- 数据集想加入除了user_id和item_id的特征,应该修改哪部份代码呢?
- [🐛BUG] Handling scores on training items when evaluating based on ranking
- [🐛BUG] recbole1.2.0与recbole-cdr兼容问题 HOT 2
- 尝试用General recommendation models进行个性化试题推荐发现效果不太好,求助 HOT 1
- 关于recbole中知识图谱数据集的问题请教 HOT 2
- run_hyper训练未完成 HOT 1
- [🐛BUG] Context-aware recommenders not properly embedding float sequences. HOT 1
- 在训练的每一轮结束后释放显存缓冲区
- 想请问如何取出数据集的一部分进行训练?(小白)
- Context-aware DeepFM not learning HOT 2
- 我想请教一个ml-1m知识图谱数据集的配置信息问题 HOT 1
- 请问序列推荐时如何实现每一个时间步都进行预测
- [🐛BUG] Migration errors in SASRec
- 使用recbole1.2.0自动下载知识图谱数据集ml-1m时发生错误
- 使用recbole1.2.0时发现ml-1m的数据数量对不上
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