trainloader = torch.utils.data.DataLoader(trainset, batch_size=16, num_workers=2, sampler=train_sampler) return trainloader #---# # 训练 #---# def train(model, trainloader, optimizer, loss_func, lr_scheduler, epoch): model.train() iterator = tqdm(range(epoch)) # 为了进度条显示而已 ...
for step, (batchX, batchY) in enumerate(loader): print('Epoch: ', epoch, '| Step: ', step, '| batch x: ', batchX.numpy(), '| batch y: ', batchY.numpy()) 1. 2. 3. 4. 5. 输出: Epoch: 0 | Step: 0 | batch x: [ 4. 6. 7. 10. 8.] | batch y: [7. 5. 4....
train=False,transform=torchvision.transforms.ToTensor())#batch_size=4:每次从test_data中取4个数据集并打包test_loader=DataLoader(dataset=test_data,batch_size=4,shuffle=True,num_workers=0,drop_last=False)#测试数据集中第一章图片及targetimg,target=test_...
subset_size = int(0.2 * dataset_size) subset_indices = np.random.choice(dataset_size, subset_size, replace=False) subset = Subset(dataset, subset_indices) print(f"子集大小: {len(subset)}") # 使用子集创建新的DataLoader subset_loader = DataLoader(subset, batch_size=8, shuffle=True) 4、Co...
DataLoader(dataset, batch_size=1, shuffle=False, sampler=None, batch_sampler=None, num_workers=0, collate_fn=None, pin_memory=False, drop_last=False, timeout=0, worker_init_fn=None, multiprocessing_context=None) Data loader. Combines a dataset and a sampler, and provides an iterable over...
3.for循环从loader里面读取数据 train_data = torchvision.datasets.CIFAR10(root="../data", train=True,transform=torchvision.transforms.ToTensor(),download=True)train_dataloader = DataLoader(train_data, batch_size=8, num_workers=1, pin_memory=True)for data in train_dataloader: ...
stack(targets) return tensors, targets batch_size = 256 if device == "cuda": num_workers = 1 pin_memory = True else: num_workers = 0 pin_memory = False train_loader = torch.utils.data.DataLoader( train_set, batch_size=batch_size, shuffle=True, collate_fn=collate_fn, num_workers=...
有了Dataset就可以构建数据迭代器DataLoader,DataLoader传入的第一个参数是Dataset,也就是RMBDataset实例;第二个参数是batch_size;在训练集中的多了一个参数shuffle=True,作用是每一个epoch中样本都是乱序的。 # 构建DataLoder,shuffle=True,每一个epoch中样本都是乱序的 train_loader = DataLoader(dataset=train_data...
# 使用子集创建新的DataLoadersubset_loader = DataLoader(subset, batch_size=8, shuffle=True) 4、ConcatDataset ConcatDataset用于将多个数据集组合成一个单一的数据集。当有多个需要一起使用的数据集时,这个工具非常有用。它可以: 合并来自不同来...
1.5.0 data loader, with batch_size bug#10344 peterdudfieldopened this issueNov 3, 2021· 0 comments· Fixed by#10345 Copy link Contributor peterdudfieldcommentedNov 3, 2021 🐛 Bug When running a dataloader with batch_size None, i.e the dataset is already in batches, and error occurs on...