tf.contrib.feature_column.sequence_categorical_column_with_vocabulary_list

View source on GitHub

A sequence of categorical terms where ids use an in-memory list.

tf.contrib.feature_column.sequence_categorical_column_with_vocabulary_list(
    key,
    vocabulary_list,
    dtype=None,
    default_value=-1,
    num_oov_buckets=0
)

Pass this to embedding_column or indicator_column to convert sequence categorical data into dense representation for input to sequence NN, such as RNN.

Example:

colors = sequence_categorical_column_with_vocabulary_list(
    key='colors', vocabulary_list=('R', 'G', 'B', 'Y'),
    num_oov_buckets=2)
colors_embedding = embedding_column(colors, dimension=3)
columns = [colors_embedding]

features = tf.io.parse_example(..., features=make_parse_example_spec(columns))
input_layer, sequence_length = sequence_input_layer(features, columns)

rnn_cell = tf.compat.v1.nn.rnn_cell.BasicRNNCell(hidden_size)
outputs, state = tf.compat.v1.nn.dynamic_rnn(
    rnn_cell, inputs=input_layer, sequence_length=sequence_length)

Args:

  • key: A unique string identifying the input feature.
  • vocabulary_list: An ordered iterable defining the vocabulary. Each feature is mapped to the index of its value (if present) in vocabulary_list. Must be castable to dtype.
  • dtype: The type of features. Only string and integer types are supported. If None, it will be inferred from vocabulary_list.
  • default_value: The integer ID value to return for out-of-vocabulary feature values, defaults to -1. This can not be specified with a positive num_oov_buckets.
  • num_oov_buckets: Non-negative integer, the number of out-of-vocabulary buckets. All out-of-vocabulary inputs will be assigned IDs in the range [len(vocabulary_list), len(vocabulary_list)+num_oov_buckets) based on a hash of the input value. A positive num_oov_buckets can not be specified with default_value.

Returns:

A _SequenceCategoricalColumn.

Raises:

  • ValueError: if vocabulary_list is empty, or contains duplicate keys.
  • ValueError: num_oov_buckets is a negative integer.
  • ValueError: num_oov_buckets and default_value are both specified.
  • ValueError: if dtype is not integer or string.