stable version

helloworld/maxcut/graph_max_cut_mcpg.py

@@ -58,7 +58,6 @@ def sampler_func(data, simulator, xs_sample,
 
     # local search
     for cnt in range(num_ls):
-
         for node_index in range(0, num_nodes):
             node0_id = data.sorted_degree_nodes[node_index]
             node1_ids = data.neighbors[node0_id]
@@ -72,7 +71,7 @@ def sampler_func(data, simulator, xs_sample,
 
     expected_cut_reshape = expected_cut.reshape((-1, total_mcmc_num))
     index = torch.argmin(expected_cut_reshape, dim=0)
-    index = torch.arange(total_mcmc_num) + index * total_mcmc_num
+    index = torch.arange(total_mcmc_num, device=device) + index * total_mcmc_num
     max_cut = expected_cut[index]
     temp_max = (num_edges - max_cut) / 2  # todo
 
@@ -223,16 +222,16 @@ def run():
     repeat_times = 128
     num_ls = 8
 
-    reset_epoch_num = 128
-    total_mcmc_num = 512
-    path = 'data/gset_14.txt'
+    # reset_epoch_num = 128
+    # total_mcmc_num = 512
+    # path = 'data/gset_14.txt'
     # path = 'data/gset_15.txt'
     # path = 'data/gset_49.txt'
     # path = 'data/gset_50.txt'
 
-    # reset_epoch_num = 192
-    # total_mcmc_num = 224
-    # path = 'data/gset_22.txt'
+    reset_epoch_num = 192
+    total_mcmc_num = 224
+    path = 'data/gset_22.txt'
 
     # reset_epoch_num = 128
     # total_mcmc_num = 256