PyTorch version of https://github.com/torchnet/torchnet
torchnet is a framework for torch which provides a set of abstractions aiming at encouraging code re-use as well as encouraging modular programming.
Most of the modules support NumPy arrays as well as PyTorch tensors on input, so could potentially be used with other frameworks.
Make sure you have PyTorch installed, then do:
pip install git+https://github.com/pytorch/tnt.git@master
What's been ported so far:
- Datasets:
- BatchDataset
- ListDataset
- ResampleDataset
- ShuffleDataset
- TensorDataset [new]
- TransformDataset
- Meters:
- AverageValueMeter
- AUCMeter
- ClassErrorMeter
- ConfusionMeter
- MovingAverageValueMeter
- MSEMeter
- TimeMeter
- Engines:
- Engine
- Transforms
Any dataset can now be plugged into torch.utils.DataLoader
, or called
.parallel(num_workers=8)
to utilize multiprocessing.