Raise an error if Standardize outcome transform's untransform_posterior is used without first calling the transform on outcomes
#1569
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This pull request was exported from Phabricator. Differential Revision: D42039100 |
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…erior` is used without first calling the transform on outcomes (meta-pytorch#1569) Summary: Pull Request resolved: meta-pytorch#1569 Say someone does the following bad thing: > tf = Standardize(m=1) > tf.untransform_posterior(posterior) Old behavior: - means and standard deviations are initialized in `Standarize.__init__` with a tensor of zeros, with 'device' not set - With a posterior on the CPU, the posterior would be nonsensically untransformed with means and standard deviations of zero - With a posterior on the GPU, this would cause an error about tensors on different devices, e.g. https://www.internalfb.com/diff/D42019721?dst_version_fbid=1618282175279712&selected_signal=dGVzdF9pZDo1NjI5NTAwMjcwNTY2NTk%3D&selected_signal_verification_phase=1 New behavior: - means and standard deviations are initialized as None - An informative error is raised Reviewed By: saitcakmak, Balandat Differential Revision: D42039100 fbshipit-source-id: c479a326ad615a42cf0553ecc675aaf10f320925
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This pull request was exported from Phabricator. Differential Revision: D42039100 |
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This pull request has been merged in 3f89c29. |
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Summary:
Say someone does the following bad thing:
Old behavior:
Standarize.__init__with a tensor of zeros, with 'device' not setNew behavior:
Reviewed By: saitcakmak, Balandat
Differential Revision: D42039100