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tf.data.Dataset to an iterable of NumPy arrays.
tfds.as_numpy( dataset, graph=None )
Note that because TensorFlow has support for ragged tensors and NumPy has
no equivalent representation,
are left as-is for the user to deal with them (e.g. using
In TF 1 (i.e. graph mode),
tf.RaggedTensors are returned as
dataset: a possibly nested structure of
tf.Graph, optional, explicitly set the graph to use.