本文整理匯總了Python中utils.feature_reader方法的典型用法代碼示例。如果您正苦於以下問題:Python utils.feature_reader方法的具體用法?Python utils.feature_reader怎麽用?Python utils.feature_reader使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類utils
的用法示例。
在下文中一共展示了utils.feature_reader方法的4個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: main
# 需要導入模塊: import utils [as 別名]
# 或者: from utils import feature_reader [as 別名]
def main():
"""
Parsing command line parameters, reading data.
Doing sparsification, fitting a GWNN and saving the logs.
"""
args = parameter_parser()
tab_printer(args)
graph = graph_reader(args.edge_path)
features = feature_reader(args.features_path)
target = target_reader(args.target_path)
sparsifier = WaveletSparsifier(graph, args.scale, args.approximation_order, args.tolerance)
sparsifier.calculate_all_wavelets()
trainer = GWNNTrainer(args, sparsifier, features, target)
trainer.fit()
trainer.score()
save_logs(args, trainer.logs)
示例2: main
# 需要導入模塊: import utils [as 別名]
# 或者: from utils import feature_reader [as 別名]
def main():
"""
Parsing command line parameters, reading data.
Fitting an NGCN and scoring the model.
"""
args = parameter_parser()
torch.manual_seed(args.seed)
tab_printer(args)
graph = graph_reader(args.edge_path)
features = feature_reader(args.features_path)
target = target_reader(args.target_path)
trainer = Trainer(args, graph, features, target, True)
trainer.fit()
if args.model == "mixhop":
trainer.evaluate_architecture()
args = trainer.reset_architecture()
trainer = Trainer(args, graph, features, target, False)
trainer.fit()
示例3: main
# 需要導入模塊: import utils [as 別名]
# 或者: from utils import feature_reader [as 別名]
def main():
"""
Parsing command line parameters, reading data, graph decomposition, fitting a ClusterGCN and scoring the model.
"""
args = parameter_parser()
torch.manual_seed(args.seed)
tab_printer(args)
graph = graph_reader(args.edge_path)
features = feature_reader(args.features_path)
target = target_reader(args.target_path)
clustering_machine = ClusteringMachine(args, graph, features, target)
clustering_machine.decompose()
gcn_trainer = ClusterGCNTrainer(args, clustering_machine)
gcn_trainer.train()
gcn_trainer.test()
示例4: main
# 需要導入模塊: import utils [as 別名]
# 或者: from utils import feature_reader [as 別名]
def main():
"""
Parsing command line parameters, reading data, fitting an APPNP/PPNP and scoring the model.
"""
args = parameter_parser()
torch.manual_seed(args.seed)
tab_printer(args)
graph = graph_reader(args.edge_path)
features = feature_reader(args.features_path)
target = target_reader(args.target_path)
trainer = APPNPTrainer(args, graph, features, target)
trainer.fit()