[Models] Remove GPU-CPU sync when do_pan_and_scan=false in Gemma3

[lgeiger]

When do_pan_and_scan=false we currently still doing a bit of extra preprocessing work, pass around a num_crops tensor and call num_patches.tolist(). This is not necessary and the latter causes GPU host synchronization, preventing some more CPU operations to be overlapped with GPU work:

This PR makes num_patches tensor optional and prevents splitting image_embeds wich removes a synchronization point.

At the moment this is only a very tiny performance improvement since {scatter, gather}_mm_placeholders also cause synchronization shortly after.
This could be prevented as well with the following patch:

diff --git a/vllm/v1/worker/gpu_model_runner.py b/vllm/v1/worker/gpu_model_runner.py
index 558325fa0..5501b7583 100644
--- a/vllm/v1/worker/gpu_model_runner.py
+++ b/vllm/v1/worker/gpu_model_runner.py
@@ -1059,6 +1059,8 @@ class GPUModelRunner(LoRAModelRunnerMixin):

                 if (is_embed := pos_info.is_embed) is not None:
                     is_embed = is_embed[start_idx:end_idx]
+                    is_embed = is_embed.nonzero().squeeze(1)
+                    is_embed = is_embed.to(encoder_output.device, non_blocking=True)

                 mm_embeds_item = gather_mm_placeholders(
                     encoder_output[start_idx:end_idx],
diff --git a/vllm/v1/worker/utils.py b/vllm/v1/worker/utils.py
index 70339ff2f..cd5380e8e 100644
--- a/vllm/v1/worker/utils.py
+++ b/vllm/v1/worker/utils.py
@@ -59,7 +59,8 @@ def scatter_mm_placeholders(
         (is_embed.shape[0], embeds.shape[-1]),
         fill_value=torch.nan,
     )
-    placeholders[is_embed] = embeds
+    indices = is_embed.nonzero().squeeze(1).to(embeds.device, non_blocking=True)
+    placeholders[indices] = embeds
     return placeholders

But I think this patch is a bit cumbersome so it's probably easier to wait for pytorch/pytorch#156384 which makes GPU tensor indexing with a boolean CPU mask non-blocking.

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[gemini-code-assist]

Summary of Changes

Hello @lgeiger, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces an optimization for the Gemma3 multimodal model within vLLM by removing an unnecessary GPU-CPU synchronization. It specifically targets the image processing pipeline when the do_pan_and_scan feature is not in use, streamlining the flow by making num_patches optional and avoiding redundant tensor operations and data splitting, which improves performance by allowing more CPU operations to overlap with GPU work.

Highlights

• Performance Optimization: Eliminated an unnecessary GPU-CPU synchronization point in the Gemma3 model's image processing pipeline. This occurs when do_pan_and_scan is false, by preventing the num_patches tensor from being converted to a list (tolist()) and avoiding the splitting of image_embeds.
• Optional num_patches Field: The num_patches field in the Gemma3ImagePixelInputs TypedDict has been made optional using typing_extensions.NotRequired, reflecting its conditional usage when pan-and-scan is not active.
• Streamlined Image Preprocessing: Adjusted _call_hf_processor, _get_mm_fields_config, _parse_and_validate_image_input, and _process_image_input to conditionally bypass num_crops and image_embeds splitting logic when do_pan_and_scan is disabled, reducing redundant computations and data transfers.

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[gemini-code-assist]

Code Review

The pull request removes GPU-CPU synchronization when do_pan_and_scan=false in Gemma3 by making the num_patches tensor optional and preventing the splitting of image_embeds. The changes look good, but I've suggested adding a few comments to improve code clarity and robustness.