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.
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. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/feature_column/sequence_categorical_column_with_vocabulary_list