[Feature Request] Prebuilt models

Motivation

It can be unnecessary tedious to write actors (and value) models.
A possible solution would be to have pre-built TensorDictSequence subclasses.
Here are a few examples:

from torchrl.modules import Architectures

# builds an actor with a TanhNormal distribution with [-1, 1] bound
actor = TanhActor(
   out_features=4,
   backbone=Architectures.MLP
)
# builds an actor with a Categorical distribution with 8 degrees of freedom bound
actor = CategoricalActor(
   out_features=4,
   backbone=Architectures.MLP
)
# builds an actor with a Categorical distribution for pixels with 8 degrees of freedom bound
actor = CategoricalActor(
   out_features=4,
   backbone=Architectures.CNN
)
# builds an actor with a Categorical distribution with a default LSTM with 8 degrees of freedom bound
actor = CategoricalActor(
   out_features=4,
   backbone=Architectures.LSTM
)
# builds an DQN for 8 actions
actor = DQNActor(
   out_features=4,
   backbone=Architectures.MLP
)

The "in-features" will be determined dynamically using lazy modules.

Thoughts?

cc @matteobettini @albertbou92 @BY571 @smorad