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[MISC] Clean up torch_npu (#688)

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torch_npu 2.5.1 support autoload now. This patch does:
1. remove useless torch_npu import
2. replace `torch_npu.npu` to `torch.npu`.

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
2025-04-29 18:03:38 +08:00
committed by GitHub
parent 0329fad927
commit b917361ca5
15 changed files with 18 additions and 47 deletions
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7
vllm_ascend/worker/model_runner.py
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@@ -28,7 +28,6 @@ from typing import (TYPE_CHECKING, Any, Callable, Dict, List, Optional, Set,
import numpy as np
import torch
import torch.nn as nn
import torch_npu
import vllm.envs as envs
from vllm.attention import AttentionMetadata, get_attn_backend
from vllm.attention.backends.utils import CommonAttentionState
@@ -1145,7 +1144,7 @@ class NPUModelRunnerBase(ModelRunnerBase[TModelInputForNPU]):
device=self.device)
self.execute_model(model_input, kv_caches, intermediate_tensors)
torch_npu.npu.synchronize()
torch.npu.synchronize()
return
def remove_all_loras(self):
@@ -1357,8 +1356,8 @@ class NPUModelRunner(NPUModelRunnerBase[ModelInputForNPUWithSamplingMetadata]):
if (self.observability_config is not None
and self.observability_config.collect_model_forward_time):
model_forward_start = torch_npu.npu.Event(enable_timing=True)
model_forward_end = torch_npu.npu.Event(enable_timing=True)
model_forward_start = torch.npu.Event(enable_timing=True)
model_forward_end = torch.npu.Event(enable_timing=True)
model_forward_start.record()
if not bypass_model_exec: