[jira] [Created] (MADLIB-1332) DL: Support mini-batched validation data for fit/evaluate

["Domino Valdano (JIRA)" <ji...@apache.org>]

Domino Valdano created MADLIB-1332:
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             Summary: DL: Support mini-batched validation data for fit/evaluate
                 Key: MADLIB-1332
                 URL: https://issues.apache.org/jira/browse/MADLIB-1332
             Project: Apache MADlib
          Issue Type: Improvement
          Components: Deep Learning
            Reporter: Domino Valdano
             Fix For: v1.16


Currently, `keras_evaluate()` is implemented by calling `internal_keras_evaluate() as a UDF.  This requires the validation table passed to `keras_fit()` to be in a format with only 1 image per row, even though the training table is in a different format, with a batch of images in every row.  This is potentially confusing and cumbersome for users to deal with, and based on some preliminary testing it seems that passing only 1 image at a time to `keras_evaluate()` is also slowing down performance.

We can solve this by converting `internal_keras_evaluate()` into a UDA, so that it runs on a minibatched validation table in the same form as the training table.

 

Tasks:
 * Convert the {{internal_keras_evaluate}} UDF to a UDA and perform weighted averaging of loss and accuracy.
 * Since x and y will now be minibatched, we don't need to add another dimension to {{x and y}} np arrays in {{internal_keras_evaluate}}.
 * Compare UDF to UDA and verify that the UDA results in a speed improvement

 



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