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Creates an extractor for extracting features.
tfma.EvalConfig, tensor_representations: Optional[Mapping[Text, schema_pb2.TensorRepresentation]] = None ) ->
The extractor acts as follows depending on the existence of certain keys within the incoming extracts:
1) Extracts contains tfma.ARROW_RECORD_BATCH_KEY
The features stored in the RecordBatch will be extracted and added to the output extract under the key tfma.FEATURES_KEY and the raw serialized inputs will be added under the tfma.INPUT_KEY. Any extracts that already exist will be merged with the values from the RecordBatch with the RecordBatch values taking precedence when duplicate keys are detected. The tfma.ARROW_RECORD_BATCH_KEY key will be removed from the output extracts.
2) Extracts contains tfma.FEATURES_KEY (but not tfma.ARROW_RECORD_BATCH_KEY)
The operation will be a no-op and the incoming extracts will be passed as is to the output.
3) Extracts contains neither tfma.FEATURES_KEY | tfma.ARROW_RECORD_BATCH_KEY
An exception will be raised.
||Optional tensor representations to use when parsing the data. If tensor_representations are not passed or a representation is not found for a given feature name a default representation will be used where possible, otherwise an exception will be raised.|
|Extractor for extracting features.|