tf.contrib.timeseries.WholeDatasetInputFn
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Supports passing a full time series to a model for evaluation/inference.
tf.contrib.timeseries.WholeDatasetInputFn(
time_series_reader
)
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.
Args |
time_series_reader
|
A TimeSeriesReader object.
|
Methods
create_batch
View source
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.
|
__call__
View source
__call__()
Call self as a function.
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Last updated 2020-10-01 UTC.
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