Comments (4)
Hi @ip-iulia, the current implementation of BiVAE is itself not Multithreaded, we can therefore not specify the number of threads. However, it is possible that some predefined functions used in BiVAE code are multithreaded, but still currently we do not have control over the number of threads for those functions.
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@ip-iulia the implementation of BiVAE uses PyTorch as backend so it's up to PyTorch to obtain best efficiency based on your available resources. Any particular reason why you want to set a specific number of threads?
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Hi @saghiles, @tqtg, thank you for your replies. I was curious to see if the number of threads could be configured rather than allowing PyTorch to determine it based on the available resources.
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@ip-iulia you can use torch.set_num_threads(int) API. However, it also depends on what parallelization library being used on your machine and needed to be configured properly. More details can be found here.
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Related Issues (20)
- [FEATURE] Add next-item recommendation models HOT 1
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- [FEATURE] Support for multiple generic FeatureModalities for items HOT 1
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- [ASK] HOT 3
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- [FEATURE] Allow running evaluation on validation set during training or right after training is done HOT 4
- [BUG] Trirank documentation X&Y HOT 2
- [BUG] Add amazon_digital_music to datasets init HOT 1
- [BUG] Having a failed unit test for SPop
- [BUG] Crash when using cornac with Numpy 2.0 HOT 3
- [BUG] Attribute Error with csr_matrix using Recommender based models HOT 2
- [ASK] Installing Cornac on Mac after Forking the repo lead to ModuleNotFoundError HOT 3
- [ASK] adding user demographics as feature for training HOT 5
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