trait ParamsAndFeaturesFallbackReadable[T <: HasFeatures] extends ParamsAndFeaturesReadable[T]
Enables loading models with params and features with a fallback mechanism. The fallbackLoad
function will be called in case there is an exception during Spark loading (i.e. missing
parameters or features).
Usually, you might want to call loadSavedModel
in the fallbackLoad
method to load a model
with default params.
- T
The type of the model that extends HasFeatures
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abstract
def
fallbackLoad(folder: String, spark: SparkSession): T
Fallback loader for when the main reader fails to load the model (e.g., missing params/features).
Fallback loader for when the main reader fails to load the model (e.g., missing params/features).
For example, we could use loadSavedModel to load a model with default parameters and features (if the model in the folder supports it).
- folder
the folder where the model is stored
- spark
the Spark session
- returns
an instance of the model with default parameters and features loaded
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addReader(reader: (T, String, SparkSession) ⇒ Unit): Unit
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load(path: String): T
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def
onRead(instance: T, path: String, session: SparkSession): Unit
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def
read: MLReader[T]
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val
readers: ArrayBuffer[(T, String, SparkSession) ⇒ Unit]
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