fix(gemma3, gemma4): default token_type_ids to zeros for text-only training

[jashshah999]

Summary

When using Gemma 3 or Gemma 4 for text-only supervised fine-tuning (no images), the forward pass raises a ValueError because token_type_ids / mm_token_type_ids is not provided. This happens because AutoTokenizer does not produce these fields -- only the multimodal Processor does.

The fix defaults to all-zeros when token_type_ids / mm_token_type_ids is None during training, instead of raising. When all zeros, is_vision is entirely False, so the bidirectional vision mask branch is skipped and a standard causal mask is produced -- which is exactly correct for text-only input.

Changes

• modeling_gemma4.py / modular_gemma4.py: default mm_token_type_ids to torch.zeros(...) instead of raising ValueError
• modeling_gemma3.py / modular_gemma3.py: same fix for token_type_ids (same root cause)

Fixes #45200

[github-actions]

[For maintainers] Suggested jobs to run (before merge)

run-slow: gemma3, gemma4

[zucchini-nlp]

See #45200 (comment)

[mingxiang1006]

this fix is helpful, would be good to merge to main branch

[zucchini-nlp]

I think the user who opened a PR is a bot, so I will merge a fix myself today. Thanks for ping @mingxiang1006

[jashshah999]

Hey. Not a bot I can do it still should I?

[zucchini-nlp]

Hey @jashshah999

I didn’t hear back on the previous comment, so I assumed it is a pure code-agent PR 😅 . Gemma4 model is pretty important to keep working correctly, and I went ahead and pushed a fix in a separate PR to unblock things faster (#45454)

Thanks for putting in effort tho, and hope this doesn't discourage you from contributing in the future!