本文整理匯總了Python中utils.get_lr方法的典型用法代碼示例。如果您正苦於以下問題:Python utils.get_lr方法的具體用法?Python utils.get_lr怎麽用?Python utils.get_lr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.get_lr方法的1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 get_lr [as 別名]
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)