Class WholeDatasetInputFn
Defined in tensorflow/contrib/timeseries/python/timeseries/input_pipeline.py.
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.
__init__
__init__(time_series_reader)
Initialize the TimeSeriesInputFn.
Args:
time_series_reader: A TimeSeriesReader object.
Methods
tf.contrib.timeseries.WholeDatasetInputFn.__call__
__call__()
Call self as a function.
tf.contrib.timeseries.WholeDatasetInputFn.create_batch
create_batch()
A suitable input_fn for an Estimator's evaluate().
Returns:
A dictionary mapping feature names to Tensors, each shape
prefixed by 1, data set size.