Torchvision 0.4 with Support for Video
Video is now a first-class citizen in torchvision, with support for data loading, datasets, pre-trained models, and transforms. The 0.4 release of torchvision includes:

Efficient IO primitives for reading/writing video files (including audio), with support for arbitrary encodings and formats.
Standard video datasets, compatible with torch.utils.data.Dataset and torch.utils.data.DataLoader.
Pre-trained models built on the Kinetics-400 dataset for action classification on videos (including the training scripts).
Reference training scripts for training your own video models.

We wanted working with video data in PyTorch to be as straightforward as possible, without compromising too much on performance.
As such, we avoid the steps that would require re-encoding the videos beforehand, as it would involve:

A preprocessing step which duplicates the dataset in order to re-encode it.
An overhead in time and space because this re-encoding is time-consuming.
