[GraphBolt] Enable CPUCachedFeature for r-gcn mag240M example.

[mfbalin]

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Project tracker: https://github.com/orgs/dmlc/projects/2

Description

Following:

dgl/examples/graphbolt/pyg/labor/node_classification.py

Lines 495 to 507 in f989f9d

	if args.num_cpu_cached_features > 0 and isinstance(
	features[("node", None, "feat")], gb.DiskBasedFeature
	):
	features[("node", None, "feat")] = gb.CPUCachedFeature(
	features[("node", None, "feat")],
	args.num_cpu_cached_features * feature_num_bytes,
	args.cpu_feature_cache_policy,
	args.feature_device == "pinned",
	)
	cpu_cached_feature = features[("node", None, "feat")]
	cpu_cache_miss_rate_fn = lambda: cpu_cached_feature._feature.miss_rate
	else:
	cpu_cache_miss_rate_fn = lambda: 1

we can update rgcn example to use new DiskBasedFeature and CPUCachedFeature.

dgl/examples/graphbolt/pyg/labor/load_dataset.py

Lines 50 to 58 in f989f9d

	dataset = gb.BuiltinDataset(dataset_name)
	if disk_based_feature_keys is None:
	disk_based_feature_keys = set()
	for feature in dataset.yaml_data["feature_data"]:
	feature_key = (feature["domain"], feature["type"], feature["name"])
	# Set the in_memory setting to False without modifying YAML file.
	if feature_key in disk_based_feature_keys:
	feature["in_memory"] = False
	dataset = dataset.load()

@Rhett-Ying

[mfbalin]

#7722 has an example on how to do it for hetero datasets.