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[Model] Remove unnecessary CUDA sync of GLM-4.1V image and video preprocess #24332

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Merged
merged 4 commits into from
Sep 8, 2025
Merged

[Model] Remove unnecessary CUDA sync of GLM-4.1V image and video preprocess #24332

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b3ee609
fix: process_image_input
what-in-the-nim Sep 5, 2025
457da99
fix: process_video_input
what-in-the-nim Sep 5, 2025
609d531
Merge branch 'main' into glm4_1v_fix
ywang96 Sep 5, 2025
c7a7a2f
Merge branch 'main' into glm4_1v_fix
what-in-the-nim Sep 6, 2025
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12 changes: 8 additions & 4 deletions vllm/model_executor/models/glm4_1v.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1457,6 +1457,7 @@ def _process_image_input(
self, image_input: Glm4vImageInputs) -> tuple[torch.Tensor, ...]:
grid_thw = image_input["image_grid_thw"]
assert grid_thw.ndim == 2
grid_thw_list = grid_thw.tolist()

if image_input["type"] == "image_embeds":
image_embeds = image_input["image_embeds"].type(self.visual.dtype)
Expand All @@ -1471,13 +1472,15 @@ def _process_image_input(
image_embeds = self.visual(pixel_values,
grid_thw=grid_thw.tolist())
merge_size = self.visual.spatial_merge_size
sizes = grid_thw.prod(-1) // merge_size // merge_size
return image_embeds.split(sizes.tolist())
sizes = (torch.tensor(grid_thw_list, dtype=torch.long).prod(-1) //
(merge_size * merge_size)).tolist()
Comment on lines +1475 to +1476
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Copilot AI Sep 5, 2025

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Creating a new tensor from the list and then converting back to list is inefficient. Consider using numpy operations or native Python calculations since grid_thw_list is already a Python list.

Copilot uses AI. Check for mistakes.
return image_embeds.split(sizes)

def _process_video_input(
self, video_input: Glm4vVideoInputs) -> tuple[torch.Tensor, ...]:
grid_thw = video_input["video_grid_thw"]
assert grid_thw.ndim == 2
grid_thw_list = grid_thw.tolist()

if video_input["type"] == "video_embeds":
video_embeds = video_input["video_embeds"].type(self.visual.dtype)
Expand All @@ -1494,8 +1497,9 @@ def _process_video_input(
grid_thw=grid_thw.tolist())
# Split concatenated embeddings for each video item.
merge_size = self.visual.spatial_merge_size
sizes = grid_thw.prod(-1) // merge_size // merge_size
return video_embeds.split(sizes.tolist())
sizes = (torch.tensor(grid_thw_list, dtype=torch.long).prod(-1) //
(merge_size * merge_size)).tolist()
Comment on lines +1500 to +1501
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Copilot AI Sep 5, 2025

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Creating a new tensor from the list and then converting back to list is inefficient. Consider using numpy operations or native Python calculations since grid_thw_list is already a Python list.

Copilot uses AI. Check for mistakes.
return video_embeds.split(sizes)

def _parse_and_validate_multimodal_inputs(self, **kwargs: object) -> dict:
mm_input_by_modality = {}
Expand Down