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[contrib] Add Wan 2.2 T2V-A14B NeuronX port#159

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[contrib] Add Wan 2.2 T2V-A14B NeuronX port#159
lutfanm-aws wants to merge 3 commits into
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contrib/wan2.2-t2v-a14b

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Summary

  • Adds NeuronX T2V implementation of Wan-AI/Wan2.2-T2V-A14B-Diffusers
  • Context-parallel (CP=4) on trn2.48xlarge
  • Equivalence: cosine=0.982 vs CPU fp32 reference
  • 19 NeuronCores, ~300 GB HBM total

Video Output

13 frames at 480×832, ~7 min total pipeline time

Neuron Core Usage

Component Cores HBM/Core
T1 backbone (CP=4, split) 0–7 ~16 GB
T2 backbone (CP=4, split) 8–15 ~16 GB
Text encoder (UMT5, TP=2) 16–17 ~13 GB
VAE decoder (hybrid) 20–21 ~17 GB

Validation

  • Per-component equivalence: text encoder 1.000, T1 0.999, T2 0.999, VAE 0.999
  • Full pipeline cosine: 0.982
  • Multi-prompt semantic: 5/5 pass
  • Integration tests: 7/7 pass

Files

  • contrib/models/wan2.2-t2v-a14b/src/ — Model + application code
  • contrib/models/wan2.2-t2v-a14b/scripts/ — Compile + inference scripts
  • contrib/models/wan2.2-t2v-a14b/test/ — Integration tests (all passing)
  • contrib/models/wan2.2-t2v-a14b/README.md — Full documentation

🤖 Generated with Kiro

Ubuntu and others added 3 commits May 7, 2026 15:32
Context-parallel (CP=4) implementation of Wan-AI/Wan2.2-T2V-A14B-Diffusers
for text-to-video generation on trn2.48xlarge. 19 NeuronCores, ~7 min per video.

Co-Authored-By: Kiro <noreply@amazon.com>
@lutfanm-aws lutfanm-aws marked this pull request as ready for review May 7, 2026 20:55
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