thd format is not supported with hierarchical CP implementation yet

Is your feature request related to a problem? Please describe.
ulysess sp + ring attention gives a good performance in SFT/RL training, which is called hierarchical CP here. But it doesn't support qkv_format 'thd' for packing now. Packing sequence is also a way to gain a good throughput.

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/transformer_engine/pytorch/attention/dot_product_attention/backends.py", line 659, in forward
[rank0]:     output = attn_forward_func_with_cp(
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/transformer_engine/pytorch/attention/dot_product_attention/context_parallel.py", line 3619, in attn_forward_func_with_cp
[rank0]:     out = AttnFuncWithCPAndKVP2P.apply(*args)
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/torch/autograd/function.py", line 575, in apply
[rank0]:     return super().apply(*args, **kwargs)  # type: ignore[misc]
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/transformer_engine/pytorch/attention/dot_product_attention/context_parallel.py", line 469, in forward
[rank0]:     qkv_format != "thd"
[rank0]: AssertionError: thd format is not supported with hierarchical CP implementation yet!

platform H800
pytorch 2.7
megatron-lm branch core_r0.13.0
transformer_engine 2.4.0
Describe the solution you'd like

I'm not very clear for now.

Describe alternatives you've considered

Closing packing maybe solves the error, but it will influence loss convergence.

Additional context

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