tf.contrib.timeseries.saved_model_utils.predict_continuation( continue_from, signatures, session, steps=None, times=None, exogenous_features=None )
Defined in tensorflow/contrib/timeseries/python/timeseries/saved_model_utils.py
.
Perform prediction using an exported saved model.
Analogous to _input_pipeline.predict_continuation_input_fn, but operates on a saved model rather than feeding into Estimator's predict method.
continue_from
: A dictionary containing the results of either an Estimator's evaluate method or filter_continuation. Used to determine the model state to make predictions starting from.signatures
: The MetaGraphDef
protocol buffer returned from tf.saved_model.loader.load
. Used to determine the names of Tensors to feed and fetch. Must be from the same model as continue_from
.session
: The session to use. The session's graph must be the one into which tf.saved_model.loader.load
loaded the model.steps
: The number of steps to predict (scalar), starting after the evaluation or filtering. If times
is specified, steps
must not be; one is required.times
: A [batch_size x window_size] array of integers (not a Tensor) indicating times to make predictions for. These times must be after the corresponding evaluation or filtering. If steps
is specified, times
must not be; one is required. If the batch dimension is omitted, it is assumed to be 1.exogenous_features
: Optional dictionary. If specified, indicates exogenous features for the model to use while making the predictions. Values must have shape [batch_size x window_size x ...], where batch_size
matches the batch dimension used when creating continue_from
, and window_size
is either the steps
argument or the window_size
of the times
argument (depending on which was specified).A dictionary with model-specific predictions (typically having keys "mean" and "covariance") and a feature_keys.PredictionResults.TIMES key indicating the times for which the predictions were computed.
ValueError
: If times
or steps
are misspecified.
© 2018 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/api_docs/python/tf/contrib/timeseries/saved_model_utils/predict_continuation