data.Dataset.from_tensor_slices((test_images[5000:], test_labels[5000:])) # 定义数据集大小 TRAIN_DATASET_SIZE = len(train_dataset) VALIDATION_DATASET_SIZE = len(validation_dataset) TEST_DATASET_SIZE = len(test_dataset) BATCH_SIZE = 128 # 打乱并批量处理训练数据集 train_dataset = train_...
dataset = np.concatenate(dataset) labelset = np.concatenate(labelset) return dataset, labelset def get_CIFAR10_dataset(root=""): train_dataset, label_dataset = get_cifar10_train_data_and_label(root=root) test_dataset, test_label_dataset = get_cifar10_train_data_and_label(root=root) retu...
0.5)) ])train_dataset = dsets.CIFAR10(root='/ml/pycifar', # 选择数据的根目录train=True, # 选择训练集transform=transform,download=True)test_dataset = dsets.CIFAR10(root='/ml/pycifar',train=False,# 选择测试集transform=transform,download=True)trainloader = DataLoader(train_dataset,batch_s...
(size,3,32,32)).transpose(0,2,3,1).astype("int32")return data,labelsdefsave_single_iamge(image,image_path):""" 这是保存单张图像的函数 :param image: 图像 :param image_path: 图像地址 :return: """ print(image_path) cv2.imwrite(image_path,...
valid_loader = DataLoader(valid_set, batch_size=batch_size, shuffle=False) dataloaders = { 'train': train_loader, 'valid': valid_loader, # 'test': dataloader_test } dataset_sizes = { 'train': len(train_set), 'valid': len(valid_set), ...
If you're going to use this dataset, please cite the tech report at the bottom of this page. Version Size md5sumCIFAR-10python version163MB c58f30108f718f92721af3b95e74349aCIFAR-10Matlab version175MB70270af85842c9e89bb428ec9976c926CIFAR-10binary version (suitableforC programs)162MB c32a...
train=False,transform=trans,download=False)returntorch.utils.data.DataLoader(train_data,batch_size=batch_size,num_workers=0),torch.utils.data.DataLoader(test_data,batch_size=batch_size,num_workers=0)# train_iter, test_iter = load_cifar_10("../data/",128)# print(train_iter.dataset.data....
If you're going to use this dataset, please cite the tech report at the bottom of this page. Version Size md5sumCIFAR-10python version163MB c58f30108f718f92721af3b95e74349aCIFAR-10Matlab version175MB70270af85842c9e89bb428ec9976c926CIFAR-10binary version (suitableforC programs)162MB c32a...
dataset = torchvision.datasets.CIFAR10(root="../data", train=is_train,transform=augs, download=True) # num_workers是设置多线程加载数据 dataloader = torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=is_train, num_workers=d2l.get_dataloader_workers()) ...