KerasVectorTransformer

keras_vector_transformer.py

# Import transformer
from sparkdl.transformers import KerasVectorTransformer

# Create input DataFrame
data = [(Vectors.sparse(5, [(1, 1.0), (3, 7.0)]),),
        (Vectors.dense([2.0, 0.0, 3.0, 4.0, 5.0]),),
        (Vectors.dense([4.0, 0.0, 0.0, 6.0, 7.0]),)]
df = spark.createDataFrame(data, ["features"])

# Create KerasVectorTransformer
transformer = KerasVectorTransformer(inputCol="features",
    outputCol="transformed_features", modelFile="path/to/my/model.h5")

# Compute result, which has a column "transformed_features" of 
# DenseVectors corresponding to Keras model output
result = transformer.transform(df)