Eliminate GPU sync overhead and CPU→GPU transfers across LTX2 pipeline

[ViktoriiaRomanova]

Fixes performance issues identified by profiling LTX2 with torch.profiler as part of #13401.

Optimises LTX2 by removing unnecessary GPU synchronisation points and replacing CPU tensor creation with on-device tensor operations across the decoding pipeline, transformer RoPE computations, scheduler, and connector padding logic.

Pipeline Denoising Optimisation

1. Added explicit set_begin_index(0) calls to both video and audio schedulers. This avoids the DtoH sync in _init_step_index. Uses the same pattern as the issue fixed in PR Avoid DtoH sync from access of nonzero() item in scheduler #11696.
   Before (eager mode):

After (eager mode, no sync gap):

Before (compile mode):

After (compile mode, no sync gap):

2. Replaced torch.tensor(..., device=device) with on-device torch.stack([torch.ones(...)*s for s in decode_noise_scale]). Avoids CPU tensor allocation and GPU transfers for decode noise scaling.

Transformer Model Optimisation

Replaced CPU tensor creation for patch sizes with on-device tensor construction.
Eliminates unnecessary CPU-to-GPU memcpy operations during RoPE coordinate preparation.

Connector Refactoring

Replaced list-comprehension-based padding logic with vectorised masking. This simplifies left-padding layout logic and eliminates unnecessary cudaStreamSynchronize calls.

Performance Results

Metric	Before	After
cudaStreamSynchronize calls (total)	18	6
Scheduler sync (eager mode)	233ms	eliminated
Scheduler sync (compiled mode)	573ms	eliminated
Other syncs total (eager mode)	88ms	25ms
Other syncs total (compiled mode)	93ms	25ms

Profiler trace

https://drive.google.com/drive/folders/1cZn1xw-8Eon22mA2zP1uoF1nE4YCC3Wo?usp=drive_link

Before submitting

• This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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• Was this discussed/approved via a GitHub issue or the forum? Please add a link to it if that's the case. Help us profile important pipelines and improve if needed #13401
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Who can review?

@sayakpaul @dg845