torch.utils.data.Subset(dataset, indices) 这个函数可以根据索引indices将数据集dataset分割。 代码语言:javascript 复制 >>>even=[iforiinrange(100)ifi%2==0]>>>new1=torch.utils.data.Subset(samples,even)>>>print(new1[:5])tensor([0,2,4,6,8]) torch.utils.data.random_split(dataset, lengths...
data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/x/anaconda3/envs/dae_env/lib/python3.7/site-packages/torch/utils/data/dataset.py", line 272, in __getitem__ return self.dataset[self.indices[idx]] File "/home/x/workspace/project/datasets.py", line 99, in ...
(3)Subset()函数 Subset(dataset, indices):从dataset中提取子集 注意:Dataset.__getitem__()方法返回的是具体数据(tuple 类型),而Subset()函数返回的是Dataset类 实例: d4 = tud.Subset(mydataset, [1,2,3,4])print(d4.__len__())# Output: 4 3.2 随机采样 SubsetRandomSampler(indices, generator=No...
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DataLoadersubset_loader=DataLoader(subset, batch_size=8, shuffle=True) 4、ConcatDataset ConcatDataset...
Dataset 1. 类能够处理各种数据格式和来源。 代码示例: importtorch fromtorch.utils.dataimportDataset classCustomDataset(Dataset): def__init__(self, data, labels): self.data=data self.labels=labels def__len__(self): returnlen(self.data)
class torch.utils.data.Subset(dataset, indices): 获取指定一个索引序列对应的子数据集。 class torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=False, sampler=None, batch_sampler=None, num_workers=0, collate_fn=<function default_collate>, pin_memory=False, drop_last=False, timeout=0...
torch.utils.data.RandomSampler(data_source, replacement=False, num_samples=None) torch.utils.data.SubsetRandomSampler(indices) torch.utils.data.WeightedRandomSampler(weights, num_samples, replacement=True) torch.utils.data.BatchSampler(sampler, batch_size, drop_last) ...
fromtorch.utils.dataimportSubset importnumpyasnp # 创建一个子集,包含原始数据集的前20%的数据dataset_size=len(dataset)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)}") ...
torch.utils.data.ChainDataset : 用于连接多个 IterableDataset 数据集,在 IterableDataset 的__add__() 方法中被调用 torch.utils.data.Subset: 用于获取指定一个索引序列对应的子数据集 class Subset(Dataset[T_co]): dataset: Dataset[T_co] indices: Sequence[int] def __init__(self, dataset: Dataset...
理解Python的迭代器是解读PyTorch 中 torch.utils.data模块的关键。在Dataset,Sampler和DataLoader这三个类中都会用到 python 抽象类的魔法方法,包括__len__(self),__getitem__(self)和__iter__(self) __len__(self): 定义当被 len() 函数调用时的行为,一般返回迭代器中元素的个数 ...