You need to wrap the iterable with tqdm, as their documentation clearly says: Instantly make your loops show a smart progress meter - just ... ... <看更多>

from torch.utils.data import Dataset, DataLoader from tqdm import tqdm class MinDataset(Dataset): def __init__(self): super(). ... <看更多>

tqdm is a Python library for adding progress bar. ... batch_size = 64 train_loader = DataLoader(dataset, batch_size=batch_size, num_workers=1 ... ... <看更多>

from torch.utils.data import DataLoader ... Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console) ... for data,_ in tqdm(dataloader): ... <看更多>

... tqdm(DataLoader(dataset, batch_size=1, pin_memory=True)): File "/home/ubuntu/anaconda3/envs/modnet_offline_5/lib/python3.6/site-packages/tqdm/std.py", ... ... <看更多>

... shuffle=True, num_workers=args.workers, pin_memory=True) decom_optim.param_groups[0]['lr'] = lr[epoch] for data in tqdm.tqdm(dataloader): print(data)`. ... <看更多>

... segmentation. notebook import tqdm from tcn import TCN class MiniRocketFeatures. ... 1 , activation = 'relu' , n_layers = 1 ) :: Module 1: Dataloader. ... <看更多>