[FSDP2] Cast model to uniform dtype before fully_shard to fix mixed-dtype AssertionError

[roycho96]

What does this PR do?

When mixed_precision is enabled, casts model parameters to uniform dtype before fully_shard() to prevent _init_mp_dtypes() AssertionError.

Problem

FSDP2's _init_mp_dtypes() requires uniform orig_dtype across all trainable parameters in a param group. With mixed dtypes, the first forward call crashes:

AssertionError: FSDP expects uniform original parameter dtype but got {torch.bfloat16, torch.float32}

FSDP2's fsdp2_prepare_model() currently passes the mixed-dtype model directly to fully_shard() without normalizing dtypes.

Fix

Cast all parameters to the mixed precision param_dtype before fully_shard(), after model_has_params4bit detection. Params4bit models are skipped to avoid destroying quantized weights.

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Who can review?

@SunMarc