[Feature Request]: AnomalyDetection with non-numeric features

[charlespnh]

What would you like to happen?

It seems like currently Beam's anomaly detection module only supports numeric features, e.g. beam.Row(f1=0.1, f2=0.2, ...) - https://github.com/apache/beam/blob/master/sdks/python/apache_beam/ml/anomaly/detectors/pyod_adapter.py#L80

For use cases with vector embedding, e.g. beam.Row(embedding=[0.1, 0.2, ...]), then the pipeline will fail with the following error:

np_batch.append(np.fromiter(row, dtype=np.float64))
TypeError: float() argument must be a string or a real number, not 'list'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

Issue Priority

Priority: 2 (default / most feature requests should be filed as P2)

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[charlespnh]

CC @chamikaramj and @shunping

[vijay-x-Raj]

hey I have created a pr as requested #35884.
I updated the batching logic in run_inference to flatten both scalar and vector fields in each beam.Row. This enables anomaly detection to support vector features like embeddings without errors.

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