我使用的是tqdm库,它没有给我提供进度条,相反,它给我的输出看起来像这样,它只是告诉我迭代:
251it [01:44, 2.39it/s]
你知道为什么代码会这样做吗?我想这可能是因为我向它传递了一个生成器,但我再次使用了过去有效的生成器。我以前从来没有真正弄乱过tdqm格式化。以下是部分源代码:
train_iter = zip(train_x, train_y) #train_x and train_y are just lists of elements
....
def train(train_iter, model, criterion, optimizer):
model.train()
total_loss = 0
for x, y in tqdm(train_iter):
x = x.transpose(0, 1)
y = y.transpose(0, 1)
optimizer.zero_grad()
bloss = model.forward(x, y, criterion)
bloss.backward()
torch.nn.utils.clip_grad_norm(model.parameters(), args.clip)
optimizer.step()
total_loss += bloss.data[0]
return total_loss发布于 2018-02-23 04:09:13
tqdm需要知道将执行多少次iter(总量)才能显示进度条。
您可以尝试这样做:
from tqdm import tqdm
train_x = range(100)
train_y = range(200)
train_iter = zip(train_x, train_y)
# Notice `train_iter` can only be iter over once, so i get `total` in this way.
total = min(len(train_x), len(train_y))
with tqdm(total=total) as pbar:
for item in train_iter:
# do something ...
pbar.update(1)发布于 2021-04-20 16:53:05
用长度填充"total“参数对我来说很有效。现在出现进度条。
from tqdm import tqdm
# ...
for imgs, targets in tqdm( train_dataloader, total=len(train_dataloader)):
# ...https://stackoverflow.com/questions/48935907
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