take back DGL example changes.

examples/graphbolt/rgcn/hetero_rgcn.py

@@ -58,7 +58,6 @@
 import torch.nn as nn
 import torch.nn.functional as F
 from dgl.nn import HeteroEmbedding
-from evaluator import IGB_Evaluator
 from ogb.lsc import MAG240MEvaluator
 from ogb.nodeproppred import Evaluator
 from tqdm import tqdm
@@ -142,10 +141,6 @@ def create_dataloader(
     if name == "ogb-lsc-mag240m":
         node_feature_keys["author"] = ["feat"]
         node_feature_keys["institution"] = ["feat"]
-    if "igb-het" in name:
-        node_feature_keys["author"] = ["feat"]
-        node_feature_keys["institute"] = ["feat"]
-        node_feature_keys["fos"] = ["feat"]
     datapipe = datapipe.fetch_feature(features, node_feature_keys)
 
     # Create a DataLoader from the datapipe.
@@ -163,7 +158,7 @@ def extract_embed(node_embed, input_nodes):
 
 def extract_node_features(name, block, data, node_embed, device):
     """Extract the node features from embedding layer or raw features."""
-    if name == "ogbn-mag" or "igb-het" in name:
+    if name == "ogbn-mag":
         input_nodes = {
             k: v.to(device) for k, v in block.srcdata[dgl.NID].items()
         }
@@ -429,9 +424,7 @@ def evaluate(
     model.eval()
     category = "paper"
     # An evaluator for the dataset.
-    if "igb-het" in name:
-        evaluator = IGB_Evaluator(name=name, num_tasks=1, eval_metric="acc")
-    elif name == "ogbn-mag":
+    if name == "ogbn-mag":
         evaluator = Evaluator(name=name)
     else:
         evaluator = MAG240MEvaluator()
@@ -595,7 +588,7 @@ def main(args):
     # `institution` are generated in advance and stored in the feature store.
     # For `ogbn-mag`, we generate the features on the fly.
     embed_layer = None
-    if args.dataset == "ogbn-mag" or "igb-het" in args.dataset:
+    if args.dataset == "ogbn-mag":
         # Create the embedding layer and move it to the appropriate device.
         embed_layer = rel_graph_embed(g, feat_size).to(device)
         print(
@@ -670,15 +663,8 @@ def main(args):
         "--dataset",
         type=str,
         default="ogbn-mag",
-        choices=[
-            "ogbn-mag",
-            "ogb-lsc-mag240m",
-            "igb-het-tiny",
-            "igb-het-small",
-            "igb-het-medium",
-        ],
-        help="Dataset name. Possible values: ogbn-mag, ogb-lsc-mag240m, "
-        " igb-het-[tiny|small|medium].",
+        choices=["ogbn-mag", "ogb-lsc-mag240m"],
+        help="Dataset name. Possible values: ogbn-mag, ogb-lsc-mag240m",
     )
     parser.add_argument("--num_epochs", type=int, default=3)
     parser.add_argument("--num_workers", type=int, default=0)