[CI] fix device configure when run on GPU (dmlc#5154)

XiaoYixin7132 · Jan 13, 2023 · f65bd2d · f65bd2d
1 parent cdfd1e3
commit f65bd2d
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Showing 4 changed files with 14 additions and 9 deletions.
diff --git a/benchmarks/benchmarks/api/bench_edge_subgraph.py b/benchmarks/benchmarks/api/bench_edge_subgraph.py
@@ -9,7 +9,6 @@
 from .. import utils
 
 
-@utils.skip_if_gpu()
 @utils.benchmark("time")
 @utils.parametrize("graph_name", ["livejournal", "reddit"])
 @utils.parametrize("format", ["coo"])
@@ -20,15 +19,16 @@ def track_time(graph_name, format, seed_egdes_num):
     graph = graph.to(device)
 
     seed_edges = np.random.randint(0, graph.num_edges(), seed_egdes_num)
+    seed_edges = torch.from_numpy(seed_edges).to(device)
 
     # dry run
     for i in range(3):
         dgl.edge_subgraph(graph, seed_edges)
 
     # timing
-
+    num_iters = 50
     with utils.Timer() as t:
-        for i in range(3):
+        for i in range(num_iters):
             dgl.edge_subgraph(graph, seed_edges)
 
-    return t.elapsed_secs / 3
+    return t.elapsed_secs / num_iters
diff --git a/benchmarks/benchmarks/api/bench_in_subgraph.py b/benchmarks/benchmarks/api/bench_in_subgraph.py
@@ -19,14 +19,16 @@ def track_time(graph_name, format, seed_nodes_num):
     graph = graph.to(device)
 
     seed_nodes = np.random.randint(0, graph.num_nodes(), seed_nodes_num)
+    seed_nodes = torch.from_numpy(seed_nodes).to(device)
 
     # dry run
     for i in range(3):
         dgl.in_subgraph(graph, seed_nodes)
 
     # timing
+    num_iters = 50
     with utils.Timer() as t:
-        for i in range(3):
+        for i in range(num_iters):
             dgl.in_subgraph(graph, seed_nodes)
 
-    return t.elapsed_secs / 3
+    return t.elapsed_secs / num_iters
diff --git a/benchmarks/benchmarks/api/bench_node_subgraph.py b/benchmarks/benchmarks/api/bench_node_subgraph.py
@@ -19,14 +19,16 @@ def track_time(graph_name, format, seed_nodes_num):
     graph = graph.to(device)
 
     seed_nodes = np.random.randint(0, graph.num_nodes(), seed_nodes_num)
+    seed_nodes = torch.from_numpy(seed_nodes).to(device)
 
     # dry run
     for i in range(3):
         dgl.node_subgraph(graph, seed_nodes)
 
     # timing
+    num_iters = 50
     with utils.Timer() as t:
-        for i in range(3):
+        for i in range(num_iters):
             dgl.node_subgraph(graph, seed_nodes)
 
-    return t.elapsed_secs / 3
+    return t.elapsed_secs / num_iters
diff --git a/benchmarks/benchmarks/api/bench_sample_neighbors.py b/benchmarks/benchmarks/api/bench_sample_neighbors.py
@@ -17,10 +17,11 @@
 @utils.parametrize("fanout", [5, 20, 40])
 def track_time(graph_name, format, seed_nodes_num, fanout):
     device = utils.get_bench_device()
-    graph = utils.get_graph(graph_name, format)
+    graph = utils.get_graph(graph_name, format).to(device)
 
     edge_dir = "in"
     seed_nodes = np.random.randint(0, graph.num_nodes(), seed_nodes_num)
+    seed_nodes = torch.from_numpy(seed_nodes).to(device)
 
     # dry run
     for i in range(3):