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Affine input transforms should error with data of incorrect dimension, even in eval mode #2510
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           This pull request was exported from Phabricator. Differential Revision: D62318530  | 
    
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           This pull request was exported from Phabricator. Differential Revision: D62318530  | 
    
…, even in eval mode (meta-pytorch#2510) Summary: Pull Request resolved: meta-pytorch#2510 Context: meta-pytorch#2509 gives a clear overview This PR: * Checks the shape of the `X` provided to an `AffineInputTransform` when it transforms the data, regardless of whether it is updating the coefficients. Makes some unrelated changes: * Fixes the example in the docstring for `batched_multi_output_to_single_output` * fixes an incorrect shape in `test_approximate_gp` * Makes data and transform batch shapes match in `TestConverters`, since those usages will now (appropriately) error Differential Revision: D62318530
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           This pull request was exported from Phabricator. Differential Revision: D62318530  | 
    
…, even in eval mode (meta-pytorch#2510) Summary: Pull Request resolved: meta-pytorch#2510 Context: meta-pytorch#2509 gives a clear overview This PR: * Checks the shape of the `X` provided to an `AffineInputTransform` when it transforms the data, regardless of whether it is updating the coefficients. Makes some unrelated changes: * Fixes the example in the docstring for `batched_multi_output_to_single_output` * fixes an incorrect shape in `test_approximate_gp` * Makes data and transform batch shapes match in `TestConverters`, since those usages will now (appropriately) error Reviewed By: saitcakmak Differential Revision: D62318530
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    …, even in eval mode (meta-pytorch#2510) Summary: Pull Request resolved: meta-pytorch#2510 Context: meta-pytorch#2509 gives a clear overview This PR: * Checks the shape of the `X` provided to an `AffineInputTransform` when it transforms the data, regardless of whether it is updating the coefficients. Makes some unrelated changes: * Fixes the example in the docstring for `batched_multi_output_to_single_output` * fixes an incorrect shape in `test_approximate_gp` * Makes data and transform batch shapes match in `TestConverters`, since those usages will now (appropriately) error Reviewed By: saitcakmak Differential Revision: D62318530
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    | 
           This pull request was exported from Phabricator. Differential Revision: D62318530  | 
    
…, even in eval mode (meta-pytorch#2510) Summary: Pull Request resolved: meta-pytorch#2510 Context: meta-pytorch#2509 gives a clear overview This PR: * Checks the shape of the `X` provided to an `AffineInputTransform` when it transforms the data, regardless of whether it is updating the coefficients. Makes some unrelated changes: * Fixes the example in the docstring for `batched_multi_output_to_single_output` * fixes an incorrect shape in `test_approximate_gp` * Makes data and transform batch shapes match in `TestConverters`, since those usages will now (appropriately) error Reviewed By: saitcakmak Differential Revision: D62318530
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           This pull request was exported from Phabricator. Differential Revision: D62318530  | 
    
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           @esantorella has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.  | 
    
          Codecov ReportAll modified and coverable lines are covered by tests ✅ 
 Additional details and impacted files@@           Coverage Diff           @@
##             main    #2510   +/-   ##
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  Coverage   99.98%   99.98%           
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  Files         193      193           
  Lines       16941    16941           
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  Hits        16939    16939           
  Misses          2        2           ☔ View full report in Codecov by Sentry.  | 
    
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           @esantorella merged this pull request in 33e11f4.  | 
    
Summary:
Context: #2509 gives a clear overview
This PR:
Xprovided to anAffineInputTransformwhen it transforms the data, regardless of whether it is updating the coefficients.Makes some unrelated changes:
batched_multi_output_to_single_outputtest_approximate_gpTestConverters, since those usages will now (appropriately) errorDifferential Revision: D62318530