Megatron FSDP does not work with CPU_OFFLOADING

**Describe the bug**

Megatron-FSDP with EP8 tries to shard the pin_memory ops,

A clear and concise description of what the bug is.

```
2025-10-27 19:28:30 WARNING: one_logger package is required to enable e2e metrics tracking. please go to https://confluence.nvidia.com/display/MLWFO/Package+Repositories for details to install it
2025-10-27 19:39:50 [rank2047]: Traceback (most recent call last):
2025-10-27 19:39:50 [rank2047]: File "/mnt/sharefs/users/runner/joshcopy/a2aoverlap/Megatron-MoE-ModelZoo/Megatron-LM/pretrain_gpt.py", line 233, in
2025-10-27 19:39:50 [rank2047]: pretrain(
2025-10-27 19:39:50 [rank2047]: File "/mnt/sharefs/users/runner/joshcopy/a2aoverlap/Megatron-MoE-ModelZoo/Megatron-LM/megatron/training/training.py", line 666, in pretrain
2025-10-27 19:39:50 [rank2047]: model, optimizer, opt_param_scheduler = setup_model_and_optimizer(
2025-10-27 19:39:50 [rank2047]: ^^^^^^^^^^^^^^^^^^^^^^^^^^
2025-10-27 19:39:50 [rank2047]: File "/mnt/sharefs/users/runner/joshcopy/a2aoverlap/Megatron-MoE-ModelZoo/Megatron-LM/megatron/training/training.py", line 1104, in setup_model_and_optimizer
2025-10-27 19:39:50 [rank2047]: optimizer = get_megatron_optimizer(
2025-10-27 19:39:50 [rank2047]: ^^^^^^^^^^^^^^^^^^^^^^^
2025-10-27 19:39:50 [rank2047]: File "/mnt/sharefs/users/runner/joshcopy/a2aoverlap/Megatron-MoE-ModelZoo/Megatron-LM/megatron/core/optimizer/__init__.py", line 565, in get_megatron_optimizer
2025-10-27 19:39:50 [rank2047]: _get_megatron_optimizer_based_on_param_groups(
2025-10-27 19:39:50 [rank2047]: File "/mnt/sharefs/users/runner/joshcopy/a2aoverlap/Megatron-MoE-ModelZoo/Megatron-LM/megatron/core/optimizer/__init__.py", line 341, in _get_megatron_optimizer_based_on_param_groups
2025-10-27 19:39:50 [rank2047]: optimizer = HybridDeviceOptimizer(
2025-10-27 19:39:50 [rank2047]: ^^^^^^^^^^^^^^^^^^^^^^
2025-10-27 19:39:50 [rank2047]: File "/mnt/sharefs/users/runner/joshcopy/a2aoverlap/Megatron-MoE-ModelZoo/Megatron-LM/megatron/core/optimizer/cpu_offloading/hybrid_optimizer.py", line 80, in __init__
2025-10-27 19:39:50 [rank2047]: self._init_sub_optimizers()
2025-10-27 19:39:50 [rank2047]: File "/mnt/sharefs/users/runner/joshcopy/a2aoverlap/Megatron-MoE-ModelZoo/Megatron-LM/megatron/core/optimizer/cpu_offloading/hybrid_optimizer.py", line 188, in _init_sub_optimizers
2025-10-27 19:39:50 [rank2047]: ) = self._get_sub_optimizer_param_groups(self.offload_fraction)
2025-10-27 19:39:50 [rank2047]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2025-10-27 19:39:50 [rank2047]: File "/mnt/sharefs/users/runner/joshcopy/a2aoverlap/Megatron-MoE-ModelZoo/Megatron-LM/megatron/core/optimizer/cpu_offloading/hybrid_optimizer.py", line 274, in _get_sub_optimizer_param_groups
2025-10-27 19:39:50 [rank2047]: param = param.detach().clone().cpu().pin_memory()
2025-10-27 19:39:50 [rank2047]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2025-10-27 19:39:50 [rank2047]: File "/usr/local/lib/python3.12/dist-packages/torch/_compile.py", line 51, in inner
2025-10-27 19:39:50 [rank2047]: return disable_fn(*args, **kwargs)
2025-10-27 19:39:50 [rank2047]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^
2025-10-27 19:39:50 [rank2047]: File "/usr/local/lib/python3.12/dist-packages/torch/_dynamo/eval_frame.py", line 850, in _fn
2025-10-27 19:39:50 [rank2047]: return fn(*args, **kwargs)
2025-10-27 19:39:50 [rank2047]: ^^^^^^^^^^^^^^^^^^^
2025-10-27 19:39:50 [rank2047]: File "/usr/local/lib/python3.12/dist-packages/torch/distributed/tensor/_api.py", line 350, in __torch_dispatch__
2025-10-27 19:39:50 [rank2047]: return DTensor._op_dispatcher.dispatch(
2025-10-27 19:39:50 [rank2047]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2025-10-27 19:39:50 [rank2047]: File "/usr/local/lib/python3.12/dist-packages/torch/distributed/tensor/_dispatch.py", line 160, in dispatch
2025-10-27 19:39:50 [rank2047]: self.sharding_propagator.propagate(op_info)
2025-10-27 19:39:50 [rank2047]: File "/usr/local/lib/python3.12/dist-packages/torch/distributed/tensor/_sharding_prop.py", line 266, in propagate
2025-10-27 19:39:50 [rank2047]: OutputSharding, self.propagate_op_sharding(op_info.schema)
2025-10-27 19:39:50 [rank2047]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2025-10-27 19:39:50 [rank2047]: File "/usr/local/lib/python3.12/dist-packages/torch/distributed/tensor/_sharding_prop.py", line 45, in __call__
2025-10-27 19:39:50 [rank2047]: return self.cache(*args, **kwargs)
2025-10-27 19:39:50 [rank2047]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^
2025-10-27 19:39:50 [rank2047]: File "/usr/local/lib/python3.12/dist-packages/torch/distributed/tensor/_sharding_prop.py", line 486, in propagate_op_sharding_non_cached
2025-10-27 19:39:50 [rank2047]: raise NotImplementedError(
2025-10-27 19:39:50 [rank2047]: NotImplementedError: Operator aten.is_pinned.default does not have a sharding strategy registered.
```

**Steps/Code to reproduce bug**

Please list *minimal* steps or code snippet for us to be able to reproduce the bug.

A helpful guide on on how to craft a minimal bug report http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports.

**Expected behavior**

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**Additional context**

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