Tensorflow feature column for variable list of values

Question

From the TensorFlow docs it\'s clear how to use tf.feature_column.categorical_column_with_vocabulary_list to create a feature column which takes as input some strin

Answer 1

Here is an example how to feed data to the indicator column:

features = {'letter': [['A','A'], ['C','D'], ['E','F'], ['G','A'], ['X','R']]}

letter_feature = tf.feature_column.categorical_column_with_vocabulary_list(
                "letter", ["A", "B", "C"], dtype=tf.string)

indicator = tf.feature_column.indicator_column(letter_feature)
tensor = tf.feature_column.input_layer(features, [indicator])

with tf.Session() as session:
    session.run(tf.global_variables_initializer())
    session.run(tf.tables_initializer())
    print(session.run([tensor]))

Which outputs:

[array([[2., 0., 0.],
       [0., 0., 1.],
       [0., 0., 0.],
       [1., 0., 0.],
       [0., 0., 0.]], dtype=float32)]