tf.contrib.timeseries.NumpyReader

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

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read()

Returns a large chunk of the Numpy arrays for later re-chunking.

read_full

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read_full()

Returns Tensor versions of the full Numpy arrays.