Consistent argument names for video datasets and VideoClips class

First of all, the new support for Video data is amazing. Really useful. 😃

Just when I was going through the code of the video datasets and utilities, I found this a bit confusing.

Sample Dataset: https://github.com/pytorch/vision/blob/8635be94d1216f10fb8302da89233bd86445e449/torchvision/datasets/ucf101.py#L27-L36

VideoClips class: https://github.com/pytorch/vision/blob/8635be94d1216f10fb8302da89233bd86445e449/torchvision/datasets/video_utils.py#L43-L49

From what I understand, the argument frames_per_clip from the dataset is the same as clip_length_in_frames from the VideoClips class.

Similarly, step_between_clips <-> frames_between_clips.

Is there a reason for this difference. Or did I understand it wrong?

Would it be better if both, the video datasets and the VideoClips class had consistent arguments?

In my opinion, frames_per_clip looks better than clip_length_in_frames. And frames_between_clips can be favored over step_between_clips since the former feels more intuitive.

Any suggestions? @fmassa