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c

com.linkedin.feathr.common

FeatureTypeConfig

class FeatureTypeConfig extends Serializable

This class encapsulates the type definition for a feature. This implementation supports Feathr's high level semantic type system (e.g. NUMERIC, BOOLEAN, VECTOR) and the new Tensor type system which includes additional metadata such as category, dimensions, shape, value type and etc.

When the feature type annotation from the feature definition is processed, the following scenarios are expected: 1. No type annotated --> (FeatureType=UNSPECIFIED, TensorType=null) 2. High level semantic NON-TENSOR feature types --> (FeatureType=<some value>, TensorType=<mapped from feature type via auto-TZ>) 3. Parameterized Tensor type annotated --> (FeatureTypes = TENSOR, TensorType = <some value>)

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Instance Constructors

  1. new FeatureTypeConfig(featureType: FeatureTypes, tensorType: TensorType, documentation: String)

    Package private constructor where both the legacy type and tensor types are passed in.

    Package private constructor where both the legacy type and tensor types are passed in. This constructor is reserved for internal use only and does not provide any of consistency checking between legacy types and TensorType from the other pubic constructors

  2. new FeatureTypeConfig(tensorType: TensorType)

    Constructs a new instance with the new TensorType.

    Constructs a new instance with the new TensorType. The corresponding the legacy FeatureTypes will be populated as FeatureTypes.TENSOR

  3. new FeatureTypeConfig(featureType: FeatureTypes)

    Constructs a new instance with the legacy FeatureTypes.

    Constructs a new instance with the legacy FeatureTypes. The corresponding TensorType will be populated

  4. new FeatureTypeConfig()

Value Members

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  10. def getDocumentation(): String
  11. def getFeatureType(): FeatureTypes
  12. def getTensorType(): TensorType
  13. def hasTensorType(): Boolean
  14. def hashCode(): Int
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