Adds an example for Hierarchical Sampling #7244
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It compares one epoch of training with and without Hierarchical Sampling.
With pyg-lib>0.1.0 we return the sampled number of nodes/edges in neighbor_sampler.py
Leveraging this, the training_benchmark.py refers to
BasicGNN
base class, in which the forward pass does the trimming if required (using the--trim
flag withtraining_benchmark.py
).Therefore, this is an example that mimics what is being done in the
training_benchmark.py,
to make evident for the user what this trimming/Hierarchical Sampling is about, how to test it, and have an idea of the advantage.