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

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Merged
merged 2 commits into from
Sep 26, 2025
+9 −2
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[QuantizationModifier] NVFP4 bugfix -- fused layer update on all modules #1869

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8b203e2
run fused layer update on all modules
brian-dellabetta Sep 26, 2025
a40d3bf
tqdm labels
brian-dellabetta Sep 26, 2025
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11 changes: 9 additions & 2 deletions src/llmcompressor/modifiers/quantization/quantization/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,11 +76,18 @@ def on_start(self, state: State, event: Event, **kwargs):
# TODO: this step can be combined with update_weight_zp_scale
# once update_fused_layer_weight_global_scales is removed
# and not required by vLLM
for _, module in tqdm.tqdm(named_modules):
for _, module in tqdm.tqdm(named_modules, desc="Updating global scales"):
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 tqdm.tqdm(state.model.modules(), desc="Fusing global scales"):
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):
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