EngineX/xc-llm-ascend
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[improve] Remove redundant parentheses in pangu_moe.py (#2081)

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### What this PR does / why we need it?

Remove redundant parentheses in pangu_moe.py.

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Local.

- vLLM version: v0.10.0
- vLLM main:
099c046463

Signed-off-by: xleoken <xleoken@163.com>
This commit is contained in:
xleoken
2025-08-19 11:00:18 +08:00
committed by GitHub
parent 6335fe39ea
commit d91c6daf89
2 changed files with 3 additions and 3 deletions
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2
setup.py
View File

@@ -364,7 +364,7 @@ setup(
version=VERSION, version=VERSION,
author="vLLM-Ascend team", author="vLLM-Ascend team",
license="Apache 2.0", license="Apache 2.0",
description=("vLLM Ascend backend plugin"), description="vLLM Ascend backend plugin",
long_description=read_readme(), long_description=read_readme(),
long_description_content_type="text/markdown", long_description_content_type="text/markdown",
url="https://github.com/vllm-project/vllm-ascend", url="https://github.com/vllm-project/vllm-ascend",

4
vllm_ascend/models/pangu_moe.py
View File

@@ -122,7 +122,7 @@ class CustomMergedColumnParallelLinear(LinearBase):
input_size=self.input_size, input_size=self.input_size,
output_size=self.output_size, output_size=self.output_size,
params_dtype=self.params_dtype, params_dtype=self.params_dtype,
weight_loader=(self.weight_loader)) weight_loader=self.weight_loader)
if bias: if bias:
self.bias = Parameter( self.bias = Parameter(
torch.empty(self.output_size_per_partition, torch.empty(self.output_size_per_partition,
@@ -227,7 +227,7 @@ class CustomRowParallelLinear(LinearBase):
input_size=self.input_size, input_size=self.input_size,
output_size=self.output_size, output_size=self.output_size,
params_dtype=self.params_dtype, params_dtype=self.params_dtype,
weight_loader=(self.weight_loader)) weight_loader=self.weight_loader)
if not reduce_results and (bias and not skip_bias_add): if not reduce_results and (bias and not skip_bias_add):
raise ValueError("When not reduce the results, adding bias to the " raise ValueError("When not reduce the results, adding bias to the "
"results can lead to incorrect results") "results can lead to incorrect results")