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@kAIto47802 @not522 |
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Thank you for your PR. I confirmed that its behavior almost matches that of master.
I add small comment. Could you check them?
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| # We need to clamp the variance to avoid negative values due to numerical errors. | ||
| return mean, torch.clamp(var, min=0.0) | ||
| return mean_tensor.item(), var_tensor.item() |
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How about rename mean_tensor and var_tensor to mean and var?
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Thank you for the PR. It almost looks good to me. I'll take another look once the above comments are resolved. |
Co-authored-by: Naoto Mizuno <naotomizuno@preferred.jp>
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@not522 @kAIto47802 |
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Oct 27, 2025
Co-authored-by: Naoto Mizuno <naotomizuno@preferred.jp>
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Oct 27, 2025
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Motivation
Since EMMR duplicates the identical functionality as the Gaussian process module, this PR eliminates the duplication.
This PR is a follow-up of:
np.linalg.invwithnp.linalg.choleskyto speed upGPSamplerfornumpy>=2.0.0#6296Description of the changes