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Batching of input instances is now done automatically and dynamically.
Added analyzers to compute covarance matrices (tft.covariance) and
principal components for PCA (tft.pca).
CombinerSpec and combine_analyzer now accept multiple inputs/outputs.
Bug Fixes and Other Changes
Depends on apache-beam[gcp]>=2.3,<3.
Fixes a bug where TransformDataset would not return correct output if the
output DatasetMetadata contained deferred values (such as vocabularies).
Added checks that the prepreprocessing function's outputs all have the same
size in the batch dimension.
Added tft.apply_buckets which takes an input tensor and a list of bucket
boundaries, and returns bucketized data.
tft.bucketize and tft.apply_buckets now set metadata for the output
tensor, which means the resulting tf.Metadata for the output of these
functions will contain min and max values based on the number of buckets,
and also be set to categorical.
Testing helper function assertAnalyzeAndTransformResults can now also test
the content of vocabulary files and other assets.
Reduces the number of beam stages needed for certain analyzers, which can be
a performance bottleneck when transforming many features.
Performance improvements in tft.uniques.
Fix a bug in tft.bucketize where the bucket boundary could be same as a
min/max value, and was getting dropped.
Allows scaling individual components of a tensor independently with tft.scale_by_min_max, tft.scale_to_0_1, and tft.scale_to_z_score.
Fix a bug where apply_saved_transform could only be applied in the global
name scope.
Add warning when frequency_threshold that are <= 1. This is a no-op and
generally reflects mistaking frequency_threshold for a relative frequency
where in fact it is an absolute frequency.
Breaking changes
The interfaces of CombinerSpec and combine_analyzer have changed to allow
for multiple inputs/outputs.