torch.utils.data.DataLoader与迭代器转换操作

from torch.utils.data import DataLoader
from torchvision import datasets
from torchvision.transforms import ToTensor
import matplotlib.pyplot as plt

training_data = datasets.FashionMNIST(
    root="data",
    train=True,
    download=True,
    transform=ToTensor()
)

test_data = datasets.FashionMNIST(
    root="data",
    train=False,
    download=True,
    transform=ToTensor()
)

train_dataloader = DataLoader(training_data, batch_size=64, shuffle=True)
test_dataloader = DataLoader(test_data, batch_size=64, shuffle=True)

print(type(train_dataloader))  # <class 'torch.utils.data.dataloader.DataLoader'>

print(type(iter(train_dataloader)))# <class 'torch.utils.data.dataloader._SingleProcessDataLoaderIter'>

train_features, train_labels = next(iter(train_dataloader))
print(f"Feature batch shape: {train_features.size()}")
print(f"Labels batch shape: {train_labels.size()}")
img = train_features[0].squeeze()
label = train_labels[0]
plt.imshow(img, cmap="gray")
plt.show()
print(f"Label: {label}")

Feature batch shape: torch.Size([64, 1, 28, 28])
Labels batch shape: torch.Size([64])
Label: 2

for train_features, train_labels in train_dataloader: 
    print(train_features.shape) # torch.Size([64, 1, 28, 28])
    print(train_features[0].shape) # torch.Size([1, 28, 28])
    print(train_features[0].squeeze().shape) # torch.Size([28, 28])
    
    img = train_features[0].squeeze()
    label = train_labels[0]
    plt.imshow(img, cmap="gray")
    plt.show()
    print(f"Label: {label}")

torch.Size([64, 1, 28, 28])
torch.Size([1, 28, 28])
torch.Size([28, 28])
Label: 7
torch.Size([64, 1, 28, 28])
torch.Size([1, 28, 28])
torch.Size([28, 28])
Label: 4
torch.Size([64, 1, 28, 28])
torch.Size([1, 28, 28])
torch.Size([28, 28])
Label: 1

for train_features, train_labels in train_dataloader:

for train_features, train_labels in iter(train_dataloader):

train_iterator = iter(train_dataloader)
try:
    while True:
        train_features, train_labels = next(train_iterator)
except StopIteration:
    pass

for x in [1, 2, 3, 4]:

list_iterator = iter([1, 2, 3, 4])
try:
    while True:
        x = next(list_iterator)
except StopIteration:
    pass