diff --git a/graph_dit/datasets/dataset.py b/graph_dit/datasets/dataset.py
index dbd64f2..8f21f7e 100644
--- a/graph_dit/datasets/dataset.py
+++ b/graph_dit/datasets/dataset.py
@@ -359,15 +359,15 @@ def new_graphs_to_json(graphs, filename):
 
     node_name_list = []
     node_count_list = []
+    node_name_list.append('*')
     
     for op_name in op_type:
         node_name_list.append(op_name)
         node_count_list.append(0) 
     
-    node_name_list.append('*')
     node_count_list.append(0)
     n_nodes_per_graph = [0] * num_graph
-    edge_count_list = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+    edge_count_list = [0, 0] 
     valencies = [0] * (len(op_type) + 1)
     transition_E = np.zeros((len(op_type) + 1, len(op_type) + 1, 2))
 
@@ -388,16 +388,16 @@ def new_graphs_to_json(graphs, filename):
 
         for op in ops:
             node = op
-            if node == '*':
-                node_count_list[-1] += 1
-                cur_node_count_arr[-1] += 1
-            else:
-                node_count_list[op_type[node]] += 1
-                cur_node_count_arr[op_type[node]] += 1
-                try:
-                    valencies[int(op_type[node])] += 1
-                except:
-                    print('int(op_type[node])', int(op_type[node]))
+            # if node == '*':
+            #     node_count_list[-1] += 1
+            #     cur_node_count_arr[-1] += 1
+            # else:
+            node_count_list[node] += 1
+            cur_node_count_arr[node] += 1
+            try:
+                valencies[node] += 1
+            except:
+                print('int(op_type[node])', int(node))
         
         transition_E_temp = np.zeros((len(op_type) + 1, len(op_type) + 1, 2))
         for i in range(n_node):
@@ -406,8 +406,8 @@ def new_graphs_to_json(graphs, filename):
                     continue
                 start_node, end_node = i, j
                 
-                start_index = op_type[ops[start_node]]
-                end_index = op_type[ops[end_node]]
+                start_index = ops[start_node]
+                end_index = ops[end_node]
                 bond_index = 1
                 edge_count_list[bond_index] += 2
                 
@@ -418,7 +418,7 @@ def new_graphs_to_json(graphs, filename):
 
         edge_count_list[0] += n_node * (n_node - 1) - n_edge * 2
         cur_tot_edge = cur_node_count_arr.reshape(-1,1) * cur_node_count_arr.reshape(1,-1) * 2
-        print(f"cur_tot_edge={cur_tot_edge}, shape: {cur_tot_edge.shape}")
+        # print(f"cur_tot_edge={cur_tot_edge}, shape: {cur_tot_edge.shape}")
         cur_tot_edge = cur_tot_edge - np.diag(cur_node_count_arr) * 2
         transition_E[:, :, 0] += cur_tot_edge - transition_E_temp.sum(axis=-1)
         assert (cur_tot_edge > transition_E_temp.sum(axis=-1)).sum() >= 0
@@ -460,7 +460,7 @@ def new_graphs_to_json(graphs, filename):
         'transition_E': transition_E.tolist(),
     }
 
-    with open(f'{filename}.meta.json', 'w') as f:
+    with open(f'/home/stud/hanzhang/nasbenchDiT/graph_dit/nasbench-201-meta.json', 'w') as f:
         json.dump(meta_dict, f)
     
     return meta_dict
@@ -683,15 +683,41 @@ class Dataset(InMemoryDataset):
             active_nodes = set()
             for i in range(len_data):
                 arch_info = self.api.query_meta_info_by_index(i)
+                results = self.api.query_by_index(i, 'cifar100')
                 nodes, edges = parse_architecture_string(arch_info.arch_str)
                 adj_matrix, ops = create_adj_matrix_and_ops(nodes, edges)
                 for op in ops:
                     if op not in active_nodes:
                         active_nodes.add(op)
+                
                 graph_list.append({
                     "adj_matrix": adj_matrix,
                     "ops": ops,
-                    "idx": i
+                    "idx": i,
+                    "train": [{
+                        "iepoch": result.get_train()['iepoch'],
+                        "loss": result.get_train()['loss'],
+                        "accuracy": result.get_train()['accuracy'],
+                        "cur_time": result.get_train()['cur_time'],
+                        "all_time": result.get_train()['all_time'],
+                        "seed": seed,
+                    }for seed, result in results.items()],
+                    "valid": [{
+                        "iepoch": result.get_eval('x-valid')['iepoch'],
+                        "loss": result.get_eval('x-valid')['loss'],
+                        "accuracy": result.get_eval('x-valid')['accuracy'],
+                        "cur_time": result.get_eval('x-valid')['cur_time'],
+                        "all_time": result.get_eval('x-valid')['all_time'],
+                        "seed": seed,
+                    }for seed, result in results.items()],
+                    "test": [{
+                        "iepoch": result.get_eval('x-test')['iepoch'],
+                        "loss": result.get_eval('x-test')['loss'],
+                        "accuracy": result.get_eval('x-test')['accuracy'],
+                        "cur_time": result.get_eval('x-test')['cur_time'],
+                        "all_time": result.get_eval('x-test')['all_time'],
+                        "seed": seed,
+                    }for seed, result in results.items()]
                 })
                 data = graph_to_graph_data((adj_matrix, ops)) 
                 data_list.append(data)
@@ -925,8 +951,9 @@ class DataInfos(AbstractDatasetInfos):
 
             adj_ops_pairs = []
             for item in data:
-                adj_matrix = np.array(item['adjacency_matrix'])
-                ops = item['operations']
+                adj_matrix = np.array(item['adj_matrix'])
+                ops = item['ops']
+                ops = [op_type[op] for op in ops]
                 adj_ops_pairs.append((adj_matrix, ops))
             
             return adj_ops_pairs
@@ -944,7 +971,7 @@ class DataInfos(AbstractDatasetInfos):
             #         ops_type[op] = len(ops_type)
             # len_ops.add(len(ops))
             # graphs.append((adj_matrix, ops))
-        graphs = read_adj_ops_from_json(f'nasbench-201.meta.json')
+        graphs = read_adj_ops_from_json(f'/home/stud/hanzhang/nasbenchDiT/graph_dit/nasbench-201-graph.json')
 
         # check first five graphs
         for i in range(5):
@@ -1158,7 +1185,7 @@ def compute_meta(root, source_name, train_index, test_index):
         'transition_E': tansition_E.tolist(),
         }
 
-    with open(f'{root}/{source_name}.meta.json', "w") as f:
+    with open(f'/home/stud/hanzhang/nasbenchDiT/graph_dit/nasbench201.meta.json', "w") as f:
         json.dump(meta_dict, f)
     
     return meta_dict