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
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
time_series_reader: A TimeSeriesReader object.
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).