How to use tensorflow feature_columns as input to a keras model

Question

Tensorflow\'s feature_columns API is quite useful for non-numerical feature processing. However, the current API doc is more about using feature_columns with tensorflow Estimato

Answer 1

If you use tensorflow dataset API, that code could do well.

featurlayer = keras.layers.DenseFeatures(feature_columns=feature_columns)
train_dataset = train_dataset.map(lambda x, y: (featurlayer(x), y))
test_dataset = test_dataset.map(lambda x, y: (featurlayer(x), y))

model.fit(train_dataset, epochs=, steps_per_epoch=, # all_data/batch_num = 
     validation_data=test_dataset,
     validation_steps=)