Supports passing a full time series to a model for evaluation/inference.
Note that this
TimeSeriesInputFn is not designed for high throughput, and should not be used for training. It allows for sequential evaluation on a full dataset (with sequential in-sample predictions), which then feeds naturally into
predict_continuation_input_fn for making out-of-sample predictions. While this is useful for plotting and interactive use,
RandomWindowInputFn is better suited to training and quantitative evaluation.
time_series_reader: A TimeSeriesReader object.
Call self as a function.
input_fn for an
A dictionary mapping feature names to
Tensors, each shape prefixed by [1, data set size] (i.e. a batch size of 1).
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.