[Feature] Tensorclass support for IQLLoss

[aehebald]

Description

Makes IQLLoss/DiscreteIQLLoss accept tensorclass inputs, not just TensorDict.
First loss converted as a template for the rest of #1062.

• Read keys with .get() instead of td[key] ([] is positional indexing on a tensorclass).
• Add _make_writable() in objectives/utils.py; route network scratch selections through it
  (a tensorclass rejects undeclared out_keys, so convert to TensorDict; dynamic containers pass through).
• Parametrize test_iql over a tensorclass input + add a tensorclass/TensorDict parity test.

Motivation and Context

#1062 asks for tensorclass support across all losses. This does IQL first so the
approach can be reviewed before applying it to the rest.

Part of #1062

• I have raised an issue to propose this change

Types of changes

• New feature (non-breaking change which adds core functionality)

Checklist

• 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.

[pytorch-bot]

🔗 Helpful Links

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