tf.feature_column.sequence_categorical_column_with_vocabulary_file

A sequence of categorical terms where ids use a vocabulary file.

View aliases

Compat aliases for migration

tf.compat.v1.feature_column.sequence_categorical_column_with_vocabulary_file

tf.feature_column.sequence_categorical_column_with_vocabulary_file(
    key, vocabulary_file, vocabulary_size=None, num_oov_buckets=0,
    default_value=None, dtype=tf.dtypes.string
)

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:

states = sequence_categorical_column_with_vocabulary_file(
    key='states', vocabulary_file='/us/states.txt', vocabulary_size=50,
    num_oov_buckets=5)
states_embedding = embedding_column(states, dimension=10)
columns = [states_embedding]

features = tf.io.parse_example(..., features=make_parse_example_spec(columns))
sequence_feature_layer = SequenceFeatures(columns)
sequence_input, sequence_length = sequence_feature_layer(features)
sequence_length_mask = tf.sequence_mask(sequence_length)

rnn_cell = tf.keras.layers.SimpleRNNCell(hidden_size)
rnn_layer = tf.keras.layers.RNN(rnn_cell)
outputs, state = rnn_layer(sequence_input, mask=sequence_length_mask)

Args
`key`	A unique string identifying the input feature.
`vocabulary_file`	The vocabulary file name.
`vocabulary_size`	Number of the elements in the vocabulary. This must be no greater than length of `vocabulary_file`, if less than length, later values are ignored. If None, it is set to the length of `vocabulary_file`.
`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 `[vocabulary_size, vocabulary_size+num_oov_buckets)` based on a hash of the input value. A positive `num_oov_buckets` can not be specified with `default_value`.
`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`.
`dtype`	The type of features. Only string and integer types are supported.

Returns
A `SequenceCategoricalColumn`.

Raises
`ValueError`	`vocabulary_file` is missing or cannot be opened.
`ValueError`	`vocabulary_size` is missing or < 1.
`ValueError`	`num_oov_buckets` is a negative integer.
`ValueError`	`num_oov_buckets` and `default_value` are both specified.
`ValueError`	`dtype` is neither string nor integer.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/feature_column/sequence_categorical_column_with_vocabulary_file