Qualcomm AI Engine Direct - Gemma4 Text model enablement

[DannyYuyang-quic]

Summary

Gemma4 Text model enablement

Test plan

python examples/qualcomm/oss_scripts/llama/llama.py --build_folder build-android --device ${SERIAL_NUM} --soc_model ${SOC_MODEL} --temperature 0 --model_mode kv--max_seq_len 1024 --prefill_ar_len 128 --decoder_model gemma4-e2b --prompt "I would like to learn python, could you teach me with a simple example?" --calib_tasks wikitext --calib_limit 1 --embedding-quantize '4,32'

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20979

• 📄 Preview Python docs built from this PR

Note: Links to docs will display an error until the docs builds have been completed.

❌ 1 New Failure, 1 Unrelated Failure, 1 Unclassified Failure

As of commit 507a79d with merge base 5bfbe1d ():

NEW FAILURE - The following job has failed:

• pull / test-sqnr-static-llm-qnn-linux (smollm2_135m) / linux-job (gh)
  test_static_llm_model

UNCLASSIFIED FAILURE - DrCI could not classify the following job because the workflow did not run on the merge base. The failure may be pre-existing on trunk or introduced by this PR:

• Test QNN Windows MSVC build / build-qnn-windows-msvc / windows-job (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
  Process completed with exit code 1.

FLAKY - The following job failed but was likely due to flakiness present on trunk:

• Test Vulkan Backend / test-vulkan / test-backend-linux (vulkan, models) / linux-job (gh) (matched linux rule in flaky-rules.json)
  The process '/usr/bin/git' failed with exit code 128

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[DannyYuyang-quic]

@psiddh Hi,
This PR adds support for the Gemma4 text model.

We chose a standalone implementation because Gemma4's architecture differs substantially from the current static_llama architecture.

Once more Gemma 4-like architectures (e.g., YOCO or per-layer embedding variants) are supported, perhaps around 4-5 models, it may make sense to revisit the design and refactor them into a unified architecture (static llama path).

cc: @shewu-quic @winskuo-quic @haowhsu-quic @chenweng-quic @abhinaykukkadapu

[DannyYuyang-quic]

@pytorchbot label "release notes: qualcomm"

[psiddh]

cc @digantdesai @Gasoonjia @JacobSzwejbka