Make dictionary transforms support different random parameters across keys

[surajpaib]

Is your feature request related to a problem? Please describe.
For current dictionary transforms, the random parameters are shared across keys.

E.g: see

MONAI/monai/transforms/intensity/dictionary.py

Line 1401 in ec63e06

# all the keys share the same random shift params

MONAI/monai/transforms/croppad/dictionary.py

Line 405 in ec63e06

self.randomize(first_item.peek_pending_shape() if isinstance(first_item, MetaTensor) else first_item.shape[1:])

Describe the solution you'd like
An option to have separate random parameters would be useful for non input-target dictionary structure. Eg: for dicts that contain views in self-supervised learning. An additional key to the random dict transforms would be ideal

[ibro45]

Here is an example (the YAML config) of where it would be useful - we needed to duplicate transforms to apply them to different keys independently from each other ("view_0" and "view_1").

[SomeUserName1]

TorchIO implements random parameters on a per transform basis: TorchIO Transform ABC
This would add this feature, however require a breaking change to the Randomizable and RandomTransform ABCs.