GitHub - pytorch/data: A PyTorch repo for data loading and utilities to be shared by the PyTorch domain libraries. (original) (raw)
TorchData
What is TorchData? | Stateful DataLoader |Install guide | Contributing | License
What is TorchData?
The TorchData project is an iterative enhancement to the PyTorch torch.utils.data.DataLoader and torch.utils.data.Dataset/IterableDataset to make them scalable, performant dataloading solutions. We will be iterating on the enhancements under the torchdata repo.
Our first change begins with adding checkpointing to torch.utils.data.DataLoader, which can be found instateful_dataloader, a drop-in replacement for torch.utils.data.DataLoader, by definingload_state_dict and state_dict methods that enable mid-epoch checkpointing, and an API for users to track custom iteration progress, and other custom states from the dataloader workers such as token buffers and/or RNG states.
Stateful DataLoader
torchdata.stateful_dataloader.StatefulDataLoader is a drop-in replacement for torch.utils.data.DataLoader which provides state_dict and load_state_dict functionality. Seethe Stateful DataLoader main page for more information and examples. Also check out the examplesin this Colab notebook.
torchdata.nodes
torchdata.nodes is a library of composable iterators (not iterables!) that let you chain together common dataloading and pre-proc operations. It follows a streaming programming model, although "sampler + Map-style" can still be configured if you desire. See torchdata.nodes main page for more details. Stay tuned for tutorial on torchdata.nodes coming soon!
Installation
Version Compatibility
The following is the corresponding torchdata versions and supported Python versions.
| torch | torchdata | python |
|---|---|---|
| master / nightly | main / nightly | >=3.9, <=3.13 |
| 2.6.0 | 0.11.0 | >=3.9, <=3.13 |
| 2.5.0 | 0.10.0 | >=3.9, <=3.12 |
| 2.5.0 | 0.9.0 | >=3.9, <=3.12 |
| 2.4.0 | 0.8.0 | >=3.8, <=3.12 |
| 2.0.0 | 0.6.0 | >=3.8, <=3.11 |
| 1.13.1 | 0.5.1 | >=3.7, <=3.10 |
| 1.12.1 | 0.4.1 | >=3.7, <=3.10 |
| 1.12.0 | 0.4.0 | >=3.7, <=3.10 |
| 1.11.0 | 0.3.0 | >=3.7, <=3.10 |
Local pip or conda
First, set up an environment. We will be installing a PyTorch binary as well as torchdata. If you're using conda, create a conda environment:
conda create --name torchdata conda activate torchdata
If you wish to use venv instead:
python -m venv torchdata-env source torchdata-env/bin/activate
Install torchdata:
Using pip:
Using conda:
conda install -c pytorch torchdata
From source
In case building TorchData from source fails, install the nightly version of PyTorch following the linked guide on thecontributing page.
From nightly
The nightly version of TorchData is also provided and updated daily from main branch.
Using pip:
pip install --pre torchdata --index-url https://download.pytorch.org/whl/nightly/cpu
Using conda:
conda install torchdata -c pytorch-nightly
Contributing
We welcome PRs! See the CONTRIBUTING file.
Beta Usage and Feedback
We'd love to hear from and work with early adopters to shape our designs. Please reach out by raising an issue if you're interested in using this tooling for your project.
License
TorchData is BSD licensed, as found in the LICENSE file.