Misc inference fixes

[sidsingh-nvidia]

What does this PR do ?

1. Tune ssm inference update kernel for blackwell machines - fewer blocks, with larger number of warps. This is applicable to nemotron models.
2. Fix the completions API to return usage statistics and accept ignore_eos.
3. Initialize sq_relu output buffers with torch.empty

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[wdykas]

I have seen this trick before but does this change numerics at all, as in is accuracy of models training without it giving the same accuracy? also assuming this is used for both training and inference so we dont get larger train/inference diff

[sidsingh-nvidia]

I am not sure if these kernels are used in training. I do not see a backwards pass here, so I assume they are not.

Concerns about numerics are valid. This trick is borrowed from vLLM, so atleast it has some precedent.

[santhnm2]

Can we verify that our functional tests still pass at least?

[santhnm2]

Can we verify that our functional tests still pass at least?

[santhnm2]

LGTM assuming functional tests pass (i.e., no meaningful difference in numerics as a result of the fast_exp change)

[svcnvidia-nemo-ci]

🔄 Merge queue validation started!

You can track the progress here: https://github.com/NVIDIA/Megatron-LM/actions/runs/24816508234