tf.contrib.timeseries.NumpyReader
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A time series parser for feeding Numpy arrays to a TimeSeriesInputFn
.
tf.contrib.timeseries.NumpyReader(
data, read_num_records_hint=4096
)
Avoids embedding data in the graph as constants.
Args |
data
|
A dictionary mapping feature names to Numpy arrays, with two
possible shapes (requires keys TrainEvalFeatures.TIMES and
TrainEvalFeatures.VALUES ): Univariate; TIMES and VALUES are both
vectors of shape [series length] Multivariate; TIMES is a vector of
shape [series length], VALUES has shape [series length x number of
features]. In any case, VALUES and any exogenous features must have
their shapes prefixed by the shape of the value corresponding to the
TIMES key.
|
read_num_records_hint
|
The maximum number of samples to read at one time,
for efficiency.
|
Methods
check_dataset_size
View source
check_dataset_size(
minimum_dataset_size
)
Raise an error if the dataset is too small.
read
View source
read()
Returns a large chunk of the Numpy arrays for later re-chunking.
read_full
View source
read_full()
Returns Tensor
versions of the full Numpy arrays.
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Last updated 2020-10-01 UTC.
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