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  1. torch.utils.data — PyTorch 2.9 documentation

    Jun 13, 2025 · Data loader combines a dataset and a sampler, and provides an iterable over the given dataset. The DataLoader supports both map-style and iterable-style datasets with single …

  2. Datasets & DataLoaders — PyTorch Tutorials 2.9.0+cu128 …

    PyTorch provides two data primitives: torch.utils.data.DataLoader and torch.utils.data.Dataset that allow you to use pre-loaded datasets as well as your own data.

  3. Writing Custom Datasets, DataLoaders and Transforms - PyTorch

    PyTorch provides many tools to make data loading easy and hopefully, to make your code more readable. In this tutorial, we will see how to load and preprocess/augment data from a non …

  4. Training with PyTorch — PyTorch Tutorials 2.9.0+cu128 …

    The DataLoader pulls instances of data from the Dataset (either automatically or with a sampler that you define), collects them in batches, and returns them for consumption by your training …

  5. Reproducibility — PyTorch 2.9 documentation

    Sep 11, 2018 · Completely reproducible results are not guaranteed across PyTorch releases, individual commits, or different platforms. Furthermore, results may not be reproducible …

  6. A guide on good usage of - PyTorch

    PyTorch notoriously provides a DataLoader class whose constructor accepts a pin_memory argument. Considering our previous discussion on pin_memory, you might wonder how the …

  7. Datasets — Torchvision 0.24 documentation

    Built-in datasets All datasets are subclasses of torch.utils.data.Dataset i.e, they have __getitem__ and __len__ methods implemented. Hence, they can all be passed to a …

  8. Quickstart — PyTorch Tutorials 2.9.0+cu128 documentation

    PyTorch has two primitives to work with data: torch.utils.data.DataLoader and torch.utils.data.Dataset. Dataset stores the samples and their corresponding labels, and …

  9. Performance Tuning Guide — PyTorch Tutorials 2.9.0+cu128 …

    torch.utils.data.DataLoader supports asynchronous data loading and data augmentation in separate worker subprocesses. The default setting for DataLoader is num_workers=0, which …

  10. DataLoader parallelization/synchronization with zarr ... - PyTorch …

    Mar 29, 2023 · I’m interested in how this interacts with the multithreading in Pytorch: for example does setting my dask config to ‘synchronous’ interfere at all with using multiple workers in my …