Skip to content

[Docs] Fix griffe warnings in vllm/lora/ops #25369

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 1 commit into from
Sep 23, 2025
Merged

[Docs] Fix griffe warnings in vllm/lora/ops #25369

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
6 changes: 3 additions & 3 deletions vllm/lora/ops/triton_ops/lora_kernel_metadata.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -83,8 +83,8 @@ def prepare_tensors(self, token_lora_mapping: torch.Tensor) -> None:
Prepare kernel metadata tensors for the current forward pass.

Args:
token_lora_tensor (torch.Tensor): Tensor containing lora indices
for each input token.
token_lora_mapping (torch.Tensor): Tensor containing lora indices
for each input token.
"""

self._reset()
Expand Down Expand Up @@ -136,7 +136,7 @@ def meta_args(

Args:
token_nums (int): Number of input tokens in the current forward
pass.
pass of the kernel.
"""
return (
self.token_lora_mapping[:token_nums],
Expand Down
1 change: 0 additions & 1 deletion vllm/lora/ops/xla_ops/lora_ops.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -93,7 +93,6 @@ def bgmv_shrink(
inputs (torch.Tensor): Input tensor of shape [num_tokens, hidden_size].
lora_b_weights (torch.Tensor): LoRA weights of shape
[num_loras, lora_rank, hidden_size].
output_tensor (torch.Tensor): (Unused) output tensor (placeholder).
lora_indices_tensor (torch.Tensor): Tensor of shape [num_tokens]
indicating which LoRA matrix to use for each token.
scaling (float, optional): Scalar multiplier applied to the output.
Expand Down