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OpenDAS
vllm_cscc
Commits
fcba05c4
Unverified
Commit
fcba05c4
authored
Sep 11, 2025
by
Wentao Ye
Committed by
GitHub
Sep 11, 2025
Browse files
[Bug] Fix Layer `weight_block_size` Assertion Issue (#24674)
Signed-off-by:
yewentao256
<
zhyanwentao@126.com
>
parent
7a30fa87
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vllm/model_executor/layers/quantization/fp8.py
vllm/model_executor/layers/quantization/fp8.py
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vllm/model_executor/layers/quantization/fp8.py
View file @
fcba05c4
...
...
@@ -450,10 +450,10 @@ class Fp8LinearMethod(LinearMethodBase):
# Activations not quantized for marlin.
del
layer
.
input_scale
# On B
200
, if E8M0 for DeepGemm is used, we need to
# On B
lackwell or Hopper
, if E8M0 for DeepGemm is used, we need to
# requantize the weight and input to the specific scale
# at the same time.
if
is_deep_gemm_e8m0_used
():
if
is_deep_gemm_e8m0_used
()
and
self
.
block_quant
:
assert
layer
.
weight_block_size
is
not
None
block_sz
=
tuple
(
layer
.
weight_block_size
)
requant_weight_ue8m0_inplace
(
...
...
@@ -905,7 +905,7 @@ class Fp8MoEMethod(FusedMoEMethodBase):
del
layer
.
w13_input_scale
del
layer
.
w2_input_scale
if
is_deep_gemm_e8m0_used
():
if
is_deep_gemm_e8m0_used
()
and
self
.
block_quant
:
assert
layer
.
weight_block_size
is
not
None
# Re-quantise the expert weights so their scales are UE8M0.
block_sz
=
tuple
(
layer
.
weight_block_size
)
...
...
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