[Doc] Add thumbnails to multi-GPU tutorials (#3141)

tutorials/blitz/1_introduction.py

@@ -216,5 +216,5 @@ train(g, model)
 # 
 
 
-# Thumbnail Courtesy: Stanford CS224W Notes
+# Thumbnail credits: Stanford CS224W Notes
 # sphinx_gallery_thumbnail_path = '_static/blitz_1_introduction.png'

tutorials/blitz/2_dglgraph.py

@@ -226,5 +226,5 @@ print(sg2)
 # 
 
 
-# Thumbnail Courtesy: Wikipedia
+# Thumbnail credits: Wikipedia
 # sphinx_gallery_thumbnail_path = '_static/blitz_2_dglgraph.png'

tutorials/blitz/3_message_passing.py

@@ -354,5 +354,5 @@ def mean_udf(nodes):
 # 
 
 
-# Thumbnail Courtesy: Representation Learning on Networks, Jure Leskovec, WWW 2018
+# Thumbnail credits: Representation Learning on Networks, Jure Leskovec, WWW 2018
 # sphinx_gallery_thumbnail_path = '_static/blitz_3_message_passing.png'

tutorials/blitz/4_link_predict.py

@@ -340,5 +340,5 @@ with torch.no_grad():
     print('AUC', compute_auc(pos_score, neg_score))
 
 
-# Thumbnail Courtesy: Link Prediction with Neo4j, Mark Needham
+# Thumbnail credits: Link Prediction with Neo4j, Mark Needham
 # sphinx_gallery_thumbnail_path = '_static/blitz_4_link_predict.png'

tutorials/blitz/5_graph_classification.py

@@ -208,5 +208,5 @@ print('Test accuracy:', num_correct / num_tests)
 # 
 
 
-# Thumbnail Courtesy: DGL
+# Thumbnail credits: DGL
 # sphinx_gallery_thumbnail_path = '_static/blitz_5_graph_classification.png'

tutorials/blitz/6_load_data.py

@@ -223,5 +223,5 @@ graph, label = dataset[0]
 print(graph, label)
 
 
-# Thumbnail Courtesy: (Un)common Use Cases for Graph Databases, Michal Bachman
+# Thumbnail credits: (Un)common Use Cases for Graph Databases, Michal Bachman
 # sphinx_gallery_thumbnail_path = '_static/blitz_6_load_data.png'

tutorials/large/L0_neighbor_sampling_overview.py

@@ -115,5 +115,5 @@ By the end of this tutorial, you will be able to
 #
 
 
-# Thumbnail Courtesy: Understanding graph embedding methods and their applications, Mengjia Xu
+# Thumbnail credits: Understanding graph embedding methods and their applications, Mengjia Xu
 # sphinx_gallery_thumbnail_path = '_static/large_L0_neighbor_sampling_overview.png'

tutorials/large/L1_large_node_classification.py

@@ -343,5 +343,5 @@ for epoch in range(10):
 #
 
 
-# Thumbnail Courtesy: Stanford CS224W Notes
+# Thumbnail credits: Stanford CS224W Notes
 # sphinx_gallery_thumbnail_path = '_static/blitz_1_introduction.png'

tutorials/large/L2_large_link_prediction.py

@@ -365,5 +365,5 @@ for epoch in range(1):
 #
 
 
-# Thumbnail Courtesy: Link Prediction with Neo4j, Mark Needham
+# Thumbnail credits: Link Prediction with Neo4j, Mark Needham
 # sphinx_gallery_thumbnail_path = '_static/blitz_4_link_predict.png'

tutorials/large/L4_message_passing.py

@@ -389,5 +389,5 @@ class SAGEConvForBoth(nn.Module):
             return self.linear(h_total)
 
 
-# Thumbnail Courtesy: Representation Learning on Networks, Jure Leskovec, WWW 2018
+# Thumbnail credits: Representation Learning on Networks, Jure Leskovec, WWW 2018
 # sphinx_gallery_thumbnail_path = '_static/blitz_3_message_passing.png'

tutorials/multi/1_graph_classification.py

@@ -245,3 +245,6 @@ if __name__ == '__main__':
         procs.append(p)
     for p in procs:
         p.join()
+
+# Thumbnail credits: DGL
+# sphinx_gallery_thumbnail_path = '_static/blitz_5_graph_classification.png'

tutorials/multi/2_node_classification.py

@@ -259,3 +259,5 @@ for proc_id in range(num_gpus):
 for p in procs:
     p.join()
 
+# Thumbnail credits: Stanford CS224W Notes
+# sphinx_gallery_thumbnail_path = '_static/blitz_1_introduction.png'