Implement evaluation mode for model evaluations #705
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FelixLehn
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adekusar-drl
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Pull Request Test Coverage Report for Build 6709715079
💛 - Coveralls |
Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com>
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You're right. It is otherwise explained twice. |
oscar-wallis
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Feb 16, 2024
* Code Update 05_torch_connector.ipynb * Typo 05_torch_connector.ipynb * Update docs/tutorials/05_torch_connector.ipynb Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com> --------- Co-authored-by: Anton Dekusar <62334182+adekusar-drl@users.noreply.github.com>
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Summary
In PART 1 of the tutorial, the classification and regression models use the model.train() setting but not the model.eval() setting with torch.no_grad().
Details and comments
The model.eval() setting with torch.no_grad() is used in PART 2, which makes sense as no test data is used in PART 1, but for the overall understanding and the PyTorch alignment, shouldn't it be there, too?