Add Gemma 4 E2B/E4B support (text-only)

[Phineas1500]

Summary

Add native text-only Gemma 4 support for google/gemma-4-E2B and google/gemma-4-E4B in the ExecuTorch LLM export path.

Why

Gemma 4 E2B/E4B do not fit the existing Llama/Qwen config-only path. Supporting them required new model/runtime behavior plus a checkpoint conversion path, not just new repo IDs and JSON configs.

What Changed

• Register gemma4_e2b and gemma4_e4b as first-class export targets.
• Add a new examples/models/gemma4 package with configs, converter, BUCK target, and README.
• Extend the native text runtime for Gemma 4-specific behavior, including:
  • layer-type-aware sliding/full attention
  • dual RoPE behavior
  • shared-KV reuse
  • per-layer input embeddings / scaling
  • GELU-tanh MLP support
  • post-attention and post-FFN norms
  • layer scaling and final logit softcapping
• Carry Gemma 4 attention scaling through the custom-SDPA export path.
• Add focused regression coverage for Gemma 4 support.
• Add two small supporting fixes discovered during validation:
  • source-tree import cleanup in examples/models/model_factory.py
  • source-tree flatbuffer schema fallback in exir/_serialize/_flatbuffer.py

Validation

Ran:

conda activate et_pt211_clean
export PYTHONNOUSERSITE=1
export PYTHONPATH=..
python -m unittest \
  executorch.examples.models.test.test_model_factory \
  executorch.exir._serialize.test.test_flatbuffer \
  executorch.examples.models.llama.tests.test_gemma4_support \
  executorch.examples.models.qwen3_5.tests.test_convert_weights

Result: Ran 31 tests ... OK

Also validated with real HF checkpoint conversion/export/runtime smoke tests for both google/gemma-4-E2B and google/gemma-4-E4B, including broad greedy-decoding parity checks against HF.

Prompt benchmark summary:

• E4B: exact match on 11/12 prompts, first-token match on 12/12 prompts
• E2B: exact match on 8/12 prompts, first-token match on 10/12 prompts

The remaining E2B drift was concentrated in open-ended near-tie generations rather than structural export failures.

Not Included In This PR

• Gemma 4 multimodal support
• Qualcomm/QNN or other backend-specific bring-up
• A dedicated Gemma 4 runner / example app beyond the native text export path
• CI end-to-end export coverage with real HF weights
• Performance or memory tuning work beyond correctness bring-up