Description

This PR proposes to set strict=False for the tensordict.select() calls in the objective classes.

The logic behind this is that in some situations the Actors and Value networks should still be able to run through the losses without some of the in_keys.

Examples are:

1. RNN without the recurrent_state key can still be called when the is_init is True.
2. Transformer networks may need a mask during inference but not during training.
3. More generally, users could make custom TensorDict modules that have optional parameters.

Motivation and Context

Why is this change required? What problem does it solve?
If it fixes an open issue, please link to the issue here.
You can use the syntax close #15213 if this solves the issue #15213

• I have raised an issue to propose this change (required for new features and bug fixes)

Types of changes

What types of changes does your code introduce? Remove all that do not apply:

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds core functionality)
• Breaking change (fix or feature that would cause existing functionality to change)
• Documentation (update in the documentation)
• Example (update in the folder of examples)

Checklist

Go over all the following points, and put an x in all the boxes that apply.
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• I have read the CONTRIBUTION guide (required)
• My change requires a change to the documentation.
• I have updated the tests accordingly (required for a bug fix or a new feature).
• I have updated the documentation accordingly.