Sequence estimators for Tensorflow
Project description
tfseqestimator
Sequence estimators for TensorFlow.
Available estimators
- FullSequenceClassifier: one class for a whole sequence
- FullSequenceRegressor: one value for a whole sequence
- SequenceItemsClassifier: one class for each sequence item
- SequenceItemsRegressor: one value for each sequence item
Usage
from tfseqestimator import FullSequenceClassifier, RnnType import tensorflow.contrib.feature_column as contrib_features token_sequence = contrib_features.sequence_categorical_column_with_hash_bucket(...) token_emb = contrib_features.embedding_column(categorical_column=token_sequence, ...) estimator = FullSequenceClassifier( sequence_feature_columns=[token_emb], rnn_type=RnnType.REGULAR_STACKED_LSTM, rnn_layers=[32, 16] ) # Input builders def input_fn_train: # returns x, y pass estimator.train(input_fn=input_fn_train, steps=100) def input_fn_eval: # returns x, y pass metrics = estimator.evaluate(input_fn=input_fn_eval, steps=10) def input_fn_predict: # returns x, None pass predictions = estimator.predict(input_fn=input_fn_predict)
Project details
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