Python utils.evaluate方法代码示例

2023-03-12 04:26| 来源: 网络整理| 查看: 265

本文整理汇总了Python中utils.evaluate方法的典型用法代码示例。如果您正苦于以下问题：Python utils.evaluate方法的具体用法？Python utils.evaluate怎么用？Python utils.evaluate使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类utils的用法示例。

在下文中一共展示了utils.evaluate方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Python代码示例。

示例1: load_apilog # 需要导入模块: import utils [as 别名] # 或者: from utils import evaluate [as 别名] def load_apilog(self, log_fname, limit): with open(log_fname, 'rb') as f: data = f.read().split('\n')[:-1] if len(data) %2 !=0: data = data[:-1] idx = 0 apilogs = [] while idx < len(data) and idx < limit*2: if data[idx][:2] == 'IN': il = utils.evaluate(data[idx][2:]) else: utils.error('load_apilog: parse IN error') if data[idx+1][:3] == 'OUT' : ol = utils.evaluate(data[idx+1][3:]) else: utils.error('load_apilog: parse OUT error') apilog = log.ApiLog(self.apis[il[0]], il, ol) apilogs.append(apilog) idx+=2 return apilogs 开发者ID:SoftSec-KAIST，项目名称:IMF，代码行数:23，代码来源:apifuzz.py 示例2: main # 需要导入模块: import utils [as 别名] # 或者: from utils import evaluate [as 别名] def main(args): """Run testing.""" test_data = utils.read_data(args, "test") print("total test samples:%s" % test_data.num_examples) if args.random_other: print("warning, testing mode with 'random_other' will result in " "different results every run...") model = models.get_model(args, gpuid=args.gpuid) tfconfig = tf.ConfigProto(allow_soft_placement=True) tfconfig.gpu_options.allow_growth = True tfconfig.gpu_options.visible_device_list = "%s" % ( ",".join(["%s" % i for i in [args.gpuid]])) with tf.Session(config=tfconfig) as sess: utils.initialize(load=True, load_best=args.load_best, args=args, sess=sess) # load the graph and variables tester = models.Tester(model, args, sess) perf = utils.evaluate(test_data, args, sess, tester) print("performance:") numbers = [] for k in sorted(perf.keys()): print("%s, %s" % (k, perf[k])) numbers.append("%s" % perf[k]) print(" ".join(sorted(perf.keys()))) print(" ".join(numbers)) 开发者ID:google，项目名称:next-prediction，代码行数:33，代码来源:test.py 示例3: main # 需要导入模块: import utils [as 别名] # 或者: from utils import evaluate [as 别名] def main(): args = parse_args() C = importlib.import_module(args.config).TrainConfig print("MODEL ID: {}".format(C.model_id)) summary_writer = SummaryWriter(C.log_dpath) train_iter, val_iter, test_iter, vocab = build_loaders(C) model = build_model(C, vocab) optimizer = torch.optim.Adam(model.parameters(), lr=C.lr, weight_decay=C.weight_decay, amsgrad=True) lr_scheduler = ReduceLROnPlateau(optimizer, mode='min', factor=C.lr_decay_gamma, patience=C.lr_decay_patience, verbose=True) best_val_scores = { 'CIDEr': 0. } best_epoch = 0 best_ckpt_fpath = None for e in range(1, C.epochs + 1): ckpt_fpath = C.ckpt_fpath_tpl.format(e) """ Train """ print("\n") train_loss = train(e, model, optimizer, train_iter, vocab, C.decoder.rnn_teacher_forcing_ratio, C.reg_lambda, C.recon_lambda, C.gradient_clip) log_train(C, summary_writer, e, train_loss, get_lr(optimizer)) """ Validation """ val_loss = test(model, val_iter, vocab, C.reg_lambda, C.recon_lambda) val_scores = evaluate(val_iter, model, model.vocab) log_val(C, summary_writer, e, val_loss, val_scores) if e >= C.save_from and e % C.save_every == 0: print("Saving checkpoint at epoch={} to {}".format(e, ckpt_fpath)) save_checkpoint(e, model, ckpt_fpath, C) if e >= C.lr_decay_start_from: lr_scheduler.step(val_loss['total']) if e == 1 or val_scores['CIDEr'] > best_val_scores['CIDEr']: best_epoch = e best_val_scores = val_scores best_ckpt_fpath = ckpt_fpath """ Test with Best Model """ print("\n\n\n[BEST]") best_model = load_checkpoint(model, best_ckpt_fpath) test_scores = evaluate(test_iter, best_model, best_model.vocab) log_test(C, summary_writer, best_epoch, test_scores) save_checkpoint(best_epoch, best_model, C.ckpt_fpath_tpl.format("best"), C) 开发者ID:hobincar，项目名称:RecNet，代码行数:51，代码来源:train.py

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