Skip to content

[QuantizationModifier] NVFP4 bugfix -- fused layer update on all modules #1869

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 2 commits into from
Sep 26, 2025
+9 −2
Merged

[QuantizationModifier] NVFP4 bugfix -- fused layer update on all modules #1869

Changes from 1 commit
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
8b203e2
run fused layer update on all modules
brian-dellabetta Sep 26, 2025
a40d3bf
tqdm labels
brian-dellabetta Sep 26, 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
9 changes: 8 additions & 1 deletion src/llmcompressor/modifiers/quantization/quantization/base.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -79,8 +79,15 @@ def on_start(self, state: State, event: Event, **kwargs):
for _, module in tqdm.tqdm(named_modules):
update_weight_global_scale(module)

for _, module in tqdm.tqdm(named_modules, desc="Calibrating weights"):
# NOTE: update_fused_layer_weight_global_scales operates on Attention
# and MLP layers, not quantizable Linear layers. Rather than running
# on targeted modules, we need to run on all modules.
# Because this call is idempotent, setting all global_scales to the
# min value, it is ok to run potentially multiple times for all modules
for module in state.model.modules():
update_fused_layer_weight_global_scales(module)

for _, module in tqdm.tqdm(named_modules, desc="Calibrating weights"):
update_weight_zp_scale(module)

def on_event(self, state: State, event: Event, **kwargs):
Expand Down
Loading