[Megatron-FSDP] Test FP8 activations + parameter sharding with Megatron-FSDP fully-shard. Update README.

[cspades]

What does this PR do ?

• Add a unit test for Megatron-FSDP + FP8 Parameters for all existing FP8 recipes using fully_shard.
• Refactor and add documentation in the README for exactly how to use FP8 parameters with fully_shard.
• Nit: Refactor the fp8_model_init context manager to mixed_precision.py and try/except quantized_model_init for newer versions of TransformerEngine
• Update inline commentary, which also documents some gaps in the support matrix with FP8, particularly that we only support FP8 parameters when fully-sharding the compute parameters, but do not currently universally support FP8 parameters for un-sharded, optimizer-sharded, or optimizer/gradient-sharded models. Only optim_grads_params.

Testing

Testing mostly done for #2239 using both Llama-8B in Megatron-LM and a toy TransformerEngine model with fully_shard, which is now tested in CI/CD.

⚠️ For major changes (either in lines of code or in its impact), please make sure to first share a design doc with the team. If you're unsure what's the best way to do so, contact the @mcore-oncall.

Contribution process

flowchart LR
    A[Pre-checks] --> B[PR Tests]
    subgraph Code Review/Approval
        C1[Expert Review] --> C2[Final Review]
    end
    B --> C1
    C2 --> D[Merge]

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