fix: use swap_tensors

[yuki-97]

1. v.data = v.data.to(device) will cause the below error for gemma3. https://github.com/NVIDIA-NeMo/RL/pull/1563/changes#r2626166513

   RuntimeError: Attempted to set the storage of a tensor on device "cuda:0" to a storage on different device "cpu". This is no longer allowed; the devices must match.

2. v = v.to(device) can't update the reference of v, so the old tensor on GPU isn't released, this will cause the below error. https://github.com/NVIDIA-NeMo/RL/actions/runs/20744518055/job/59648725289?pr=1726

   assert current_allocated == 0.0, "Memory should be 0 after refit completed"

torch.utils.swap_tensors(v, v.to(device)) could solve both error above.

[github-actions]

ℹ️ File Consistency Check

Check based on commit: 9fb51bc (PR #1734 from yukih/pr-1726)

✅ DTensor Policy Worker Synchronization Check

Both DTensor policy worker files were modified in this PR:

• nemo_rl/models/policy/workers/dtensor_policy_worker.py
• nemo_rl/models/policy/workers/dtensor_policy_worker_v2.py

Please ensure that the changes are consistent between both files where applicable.

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