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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tfseqestimator-2.0.0.tar.gz
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