Skip to content

[V1][Bugfix] Fix handing of second_per_grid_ts for Qwen2-VL & Qwen2.5-VL #14548

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 5 commits into from
Mar 10, 2025
Merged

[V1][Bugfix] Fix handing of second_per_grid_ts for Qwen2-VL & Qwen2.5-VL #14548

Changes from all commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
7daa358
fix
ywang96 Mar 10, 2025
71c7dde
fix
ywang96 Mar 10, 2025
e8c4809
fix typing for v0
ywang96 Mar 10, 2025
780a2eb
fix
ywang96 Mar 10, 2025
a03ba0c
fix
ywang96 Mar 10, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
15 changes: 10 additions & 5 deletions vllm/model_executor/layers/rotary_embedding.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -923,14 +923,19 @@ def forward(
def get_input_positions(
input_tokens: List[int],
hf_config: PretrainedConfig,
image_grid_thw: Union[List[List[int]], torch.Tensor],
video_grid_thw: Union[List[List[int]], torch.Tensor],
second_per_grid_ts: Optional[List[float]] = None,
image_grid_thw: Optional[Union[List[List[int]], torch.Tensor]],
video_grid_thw: Optional[Union[List[List[int]], torch.Tensor]],
second_per_grid_ts: Optional[List[float]],
context_len: int = 0,
seq_len: Optional[int] = None,
) -> Tuple[List[List[int]], int]:
"""Get mrope input positions and delta value."""

image_grid_thw = [] if image_grid_thw is None else image_grid_thw
video_grid_thw = [] if video_grid_thw is None else video_grid_thw
second_per_grid_ts = [] if second_per_grid_ts is None else \
second_per_grid_ts

llm_positions, mrope_position_delta = \
MRotaryEmbedding.get_input_positions_tensor(
input_tokens=input_tokens,
Expand All @@ -950,7 +955,7 @@ def get_input_positions_tensor(
hf_config: PretrainedConfig,
image_grid_thw: Union[List[List[int]], torch.Tensor],
video_grid_thw: Union[List[List[int]], torch.Tensor],
second_per_grid_ts: Optional[List[float]] = None,
second_per_grid_ts: List[float],
context_len: int = 0,
seq_len: Optional[int] = None,
) -> Tuple[torch.Tensor, int]:
Expand Down Expand Up @@ -1006,7 +1011,7 @@ def get_input_positions_tensor(
video_grid_thw[video_index][2],
)
video_second_per_grid_t = 1.0
if second_per_grid_ts is not None:
if second_per_grid_ts:
video_second_per_grid_t = second_per_grid_ts[video_index]
video_index += 1
remain_videos -= 1
Expand Down