GitLab

* docs: Add comprehensive Getting Started guide with benchmarks

- Add new Getting Started documentation with PyTorch and JAX tutorials
- Include benchmark scripts demonstrating TE performance benefits
- Add CSS styling for code output and tabs
- Replace old quickstart notebooks with improved documentation
- Add transformer layer diagram (SVG)
- Update docs configuration and workflow
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* 2026 in copyright
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* Tutorial for integration te/jax quantization into an existing framework
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* add todos
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* support nvfp4 sr rng key, move wrapper module into TE itself, fix bfloat16 cast
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* update docstrings
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* Fix QKV proj and out proj in Flax example transformer layer
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* Use fused attention in quickstart_jax example
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* Fix notebook title
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* Fix lint
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* Add explanation of flax module wrapper
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* Add generic stripe_height support for load balancing
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* Modify test code for CP + AG + THD + stripe height greater than 1
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* Add stripe_height arg to fused attn and fused attn fwd API. Add appropriate mask checks for AG+THD+CP and pick BRCM to be executed per rank. Add Fused Attn Primitive for CP + THD +AG + Striping. Add a method to reorder and all gather segment ids and offsets for kv
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* Rename stripe_height to stripe_size
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* Code clean up and add additional comments
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* Fix seqoffsets length to be passed onto FusedAttn primitive as it is b and not b+1 needed by cuDNN
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* Skip THD test cases for CP + AG + Dual chunk. Skip BSHD cases for CP + AG + Striped>1. Correct the layout and shapr parameters passed to the tests
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* nit: Correct the ID for the test dist fused attn tests to account for cp*2 which is done under the hood
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* Set num_segments_per_seq defaults to None instead of 0
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* Remove incorrectly added file
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* Explicitly pass zero sized arrays for seg ids and pos in the CP + AG + Striped primitive rather than using the seqlens or the offsets as placeholders
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* Add a deep dive doc for CP+THD+AG+Stripe>1+SWA regarding design considerations and decisions
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