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add read swap csv codes

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This commit is contained in:
mhz 2024-08-29 09:25:15 +02:00
parent c86db9b6ba
commit 82183d3df7
1 changed files with 11 additions and 14 deletions
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25
graph_dit/datasets/dataset.py
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@ -771,9 +771,10 @@ class Dataset(InMemoryDataset):
edge_type = torch.tensor(edge_type, dtype=torch.long)
edge_attr = edge_type
# y = torch.tensor([0, 0], dtype=torch.float).view(1, -1)
y = get_nasbench201_idx_score(idx, train_loader, searchspace, args, device)
# y = get_nasbench201_idx_score(idx, train_loader, searchspace, args, device)
y = self.swap_scores[idx]
print(y, idx)
if y > 1600:
if y > 60000:
print(f'idx={idx}, y={y}')
y = torch.tensor([1, 1], dtype=torch.float).view(1, -1)
data = Data(x=x, edge_index=edge_index, edge_attr=edge_attr, y=y, idx=i)
@ -812,6 +813,14 @@ class Dataset(InMemoryDataset):
args.num_labels = 1
searchspace = nasspace.get_search_space(args)
train_loader = dt.get_data(args.dataset, args.data_loc, args.trainval, args.batch_size, args.augtype, args.repeat, args)
self.swap_scores = []
import csv
# with open('/nfs/data3/hanzhang/nasbenchDiT/graph_dit/swap_results.csv', 'r') as f:
with open('/nfs/data3/hanzhang/nasbenchDiT/graph_dit/swap_results_cifar100.csv', 'r') as f:
reader = csv.reader(f)
header = next(reader)
data = [row for row in reader]
self.swap_scores = [float(row[0]) for row in data]
device = torch.device('cuda:2')
with tqdm(total = len_data) as pbar:
active_nodes = set()
@ -823,14 +832,8 @@ class Dataset(InMemoryDataset):
flex_graph_path = '/nfs/data3/hanzhang/nasbenchDiT/graph_dit/flex-nasbench201-graph.json'
for graph in graph_list:
print(f'iterate every graph in graph_list, here is {i}')
# arch_info = self.api.query_meta_info_by_index(i)
# results = self.api.query_by_index(i, 'cifar100')
arch_info = graph['arch_str']
# results =
# nodes, edges = parse_architecture_string(arch_info.arch_str)
# ops, adj_matrix = parse_architecture_string(arch_info.arch_str, padding=4)
ops, adj_matrix, ori_nodes, ori_adj = parse_architecture_string(arch_info, padding=4)
# adj_matrix, ops = create_adj_matrix_and_ops(nodes, edges)
for op in ops:
if op not in active_nodes:
active_nodes.add(op)
@ -839,12 +842,6 @@ class Dataset(InMemoryDataset):
if data is None:
pbar.update(1)
continue
# with open(flex_graph_path, 'a') as f:
# flex_graph = {
# 'adj_matrix': adj_matrix,
# 'ops': ops,
# }
# json.dump(flex_graph, f)
flex_graph_list.append({
'adj_matrix':adj_matrix,
'ops': ops,