Skip to content

[BUGFIX ] fix undefined silu_and_mul_nvfp4_quant #23929

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
simon-mo merged 3 commits into from
Aug 29, 2025
Merged

[BUGFIX ] fix undefined silu_and_mul_nvfp4_quant #23929

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
5f206c3
fix undefined silu_and_mul_nvfp4_quant
Aug 29, 2025
551ea65
update
zou3519 Aug 29, 2025
72bbc90
Merge branch 'main' into hc/fix_undefined_symbol
zou3519 Aug 29, 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
4 changes: 2 additions & 2 deletions csrc/ops.h
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -130,8 +130,8 @@ void silu_and_mul(torch::Tensor& out, torch::Tensor& input);
void silu_and_mul_quant(torch::Tensor& out, torch::Tensor& input,
torch::Tensor& scale);

#ifndef USE_ROCM

#if (defined(ENABLE_NVFP4_SM100) && ENABLE_NVFP4_SM100) || \
(defined(ENABLE_NVFP4_SM120) && ENABLE_NVFP4_SM120)
void silu_and_mul_nvfp4_quant(torch::Tensor& out,
torch::Tensor& output_block_scale,
torch::Tensor& input,
Expand Down
3 changes: 2 additions & 1 deletion csrc/torch_bindings.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -115,7 +115,8 @@ TORCH_LIBRARY_EXPAND(TORCH_EXTENSION_NAME, ops) {
"silu_and_mul_quant(Tensor! result, Tensor input, Tensor scale) -> ()");
ops.impl("silu_and_mul_quant", torch::kCUDA, &silu_and_mul_quant);

#ifndef USE_ROCM
#if (defined(ENABLE_NVFP4_SM100) && ENABLE_NVFP4_SM100) || \
(defined(ENABLE_NVFP4_SM120) && ENABLE_NVFP4_SM120)
ops.def(
"silu_and_mul_nvfp4_quant(Tensor! result, Tensor! result_block_scale, "
"Tensor input, Tensor input_global_scale) -> ()");
Expand Down
4 changes: 3 additions & 1 deletion vllm/compilation/fix_functionalization.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -97,7 +97,9 @@ def __call__(self, graph: torch.fx.Graph):
node,
mutated_args,
args=('result', 'input', 'scale'))
elif at_target == torch.ops._C.silu_and_mul_nvfp4_quant.default:
elif current_platform.has_device_capability(
100
) and at_target == torch.ops._C.silu_and_mul_nvfp4_quant.default:

@gemini-code-assist gemini-code-assist Bot Aug 29, 2025

Copy link
Copy Markdown
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

critical

The check current_platform.has_device_capability(100) is incorrect. The has_device_capability method compares its integer argument with the major version of the CUDA compute capability. For Blackwell GPUs (SM 10.0), the major version is 10. Therefore, the check 10 >= 100 will always evaluate to false, preventing this code path from ever being taken on the intended hardware. This should be has_device_capability(10) to correctly target devices with compute capability 10.x and above.

Suggested change
elif current_platform.has_device_capability(
100
) and at_target == torch.ops._C.silu_and_mul_nvfp4_quant.default:
elif current_platform.has_device_capability(
10
) and at_target == torch.ops._C.silu_and_mul_nvfp4_quant.default:

@zou3519 zou3519 Aug 29, 2025 •
edited
Loading

Copy link
Copy Markdown
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Easier way to check here is "if hasattr(torch.ops._C, silu_and_mul_nvfp4_quant)"

@youkaichao youkaichao Aug 29, 2025

Copy link
Copy Markdown
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

i feel if hasattr(torch.ops._C, silu_and_mul_nvfp4_quant) makes more sense.

mutated_args = {1: 'result', 2: 'result_block_scale'}
self.defunctionalize(graph,
node,
Expand Down