worker_init_fn (callable, optional): 每个worker初始化函数 If not None, this will be called on each worker subprocess with the worker id (an int in[0, num_workers - 1]) as input, after seeding and before data loading.
num_workers (int, optional): 这个参数决定了有几个进程来处理data loading。0意味着所有的数据都会被load进主进程。(默认为0) collate_fn (callable, optional): 将一个list的sample组成一个mini-batch的函数 pin_memory (bool, optional): 如果设置为True,那么data loader将会在返回它们之前,将tensors拷贝到C...
worker_init_fn(callable, optional) – If not None, this will be called on each worker subprocess with the worker id (an int in [0, num_workers – 1]) as input, after seeding and before data loading. (default: None) 1.1 dataset 只支持两种类型的数据集:map-style datasets,iterable-style...
class DataLoader(object): r""" Data loader. Combines a dataset and a sampler, and provides single- or multi-process iterators over the dataset. Arguments: dataset (Dataset): dataset from which to load the data. batch_size (int, optional): how many samples per batch to load (default: 1...
先介绍一下DataLoader(object)的参数: dataset(Dataset): 传入的数据集 batch_size(int, optional): 每个batch有多少个样本 shuffle(bool, optional): 在每个epoch开始的时候,对数据进行重新排序 sampler(Sampler, optional): 自定义从数据集中取样本的策略,如果指定这个参数,那么shuffle必须为False ...
num_workers (int, optional) :数据加载的子进程数目。如果是 0,表示从主进程加载数据。 collate_fn (callable, optional):从一个小批次( mini-batch)张量中合并出一个样本列表。当从 map-style 数据集做批量加载时候使用。 pin_memory (bool, optional) : 如果为true,则在返回张量之前把张量拷贝到CUDA固定内...
class DataLoader(Generic[T_co]): def __init__( self, dataset: Dataset[T_co], batch_size: Optional[int] = 1, shuffle: bool = False, sampler: Optional[Sampler[int]] = None, batch_sampler: Optional[Sampler[Sequence[int]]] = None, num_workers: int = 0, ...
先介绍一下DataLoader(object)的参数: dataset(Dataset): 传入的数据集 batch_size(int, optional): 每个batch有多少个样本 shuffle(bool, optional): 在每个epoch开始的时候,对数据进行重新排序 sampler(Sampler, optional): 自定义从数据集中取样本的策略,如果指定这个参数,那么shuffle必须为False ...
num_workers(python:int, optional) – 多少个子程序同时工作来获取数据,多线程。 (default: 0)collate_fn(callable, optional) – 合并样本列表以形成小批量。pin_memory(bool, optional) – 如果为True,数据加载器在返回前将张量复制到CUDA固定内存中。drop_last(bool, optional) – 如果数据集大小不能被batch...
size()) if i == 3: break # 下面三个类都需要实现 __call__ 函数 class Rescale(object): """Rescale the image in a sample to a given size. Args: output_size (tuple or int): Desired output size. If tuple, output is matched to output_size. If int, smaller of image edges is ...