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A generator supports creating sequences for input into graph machine learning algorithms via the `flow` method.
Returns the number of batch dimensions in returned tensors (_not_ the batch size itself).
For instance, for full batch methods like GCN, the feature has shape ``1 × number of nodes ×
feature size``, where the 1 is a "dummy" batch dimension and ``number of nodes`` is the real
batch size (every node in the graph).
def flow(self, *args, **kwargs):
Create a Keras Sequence or similar input, appropriate for a graph machine learning model.
[docs] def default_corrupt_input_index_groups(self):
Optionally returns the indices of input tensors that can be shuffled for
:class:`.CorruptedGenerator` to use in :class:`.DeepGraphInfomax`.
If this isn't overridden, this method returns None, indicating that the generator doesn't
have a default or "canonical" set of indices that can be corrupted for Deep Graph Infomax.