Error loading "D:\Program Files\Python310\lib\site-packages\torch\lib\aoti_custo

service
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2026-01-17 19:52 #1031 by service

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->intel-extensi...问题详情： ->intel-extension-for-pytorch==2.5.10+xpu)(0.2.12) Installing collected packages: torch, torchvision, torchaudio, intel-extension-for-pytorch ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. sentence-transformers 5.2.0 requires transformers<6.0.0,>=4.41.0, but you have transformers 4.36.2 which is incompatible.回答（Answer）：很好！安装实际上已经成功了。这个

Code:

sentence-transformers

的版本冲突警告完全不重要，也不会影响你的XPU功能。✅ 安装成功确认看到

Code:

Installing collected packages: torch, torchvision, torchaudio, intel-extension-for-pytorch

这个信息，说明所有核心包都已正确安装。现在XPU应该可以正常工作了。🚀 立即测试XPU功能运行这个简单的测试脚本确认一切正常：

Code:

import torch
import intel_extension_for_pytorch as ipex

print("=" * 50)
print("PyTorch XPU 安装验证")
print("=" * 50)

# 基础信息
print(f"PyTorch版本:

{torch.__version__}
")
print(f"IPEX版本:

{ipex.__version__}
")

# XPU可用性
xpu_available = torch.xpu.is_available()
print(f"XPU是否可用: {'✅ 是' if xpu_available else '❌ 否'}")

if xpu_available:
# 设备信息
device_count = torch.xpu.device_count()
print(f"XPU设备数量:

{device_count}
")

for i in range(device_count):
print(f" 设备

{i}
:

{torch.xpu.get_device_name(i)}
")

# 简单计算测试
print("\n执行计算测试...")
x = torch.randn(1000, 1000).xpu()
y = torch.randn(1000, 1000).xpu()
result = torch.matmul(x, y)
print(f" 计算完成！结果形状:

{result.shape}
")
print(f" 结果设备:

{result.device}
")

# 内存信息
print(f"\nGPU内存信息:")
print(f" 已分配:

{torch.xpu.memory_allocated(0) / 1024**3:.2f}
GB")
print(f" 缓存:

{torch.xpu.memory_reserved(0) / 1024**3:.2f}
GB")

print("\n✅ PyTorch XPU 安装成功！可以正常使用。")
else:
print("\n❌ XPU不可用，需要进一步检查:")
print(" 1. 确认有Intel Arc GPU")
print(" 2. 安装最新Intel GPU驱动")
print(" 3. 重启系统")

📁 启动ComfyUI现在可以启动ComfyUI了：

Code:

cd E:\AI\ComfyUI\ComfyUI
python main.py

如果还有相同的

Code:

aoti_custom_ops.dll

错误，那可能是：

环境没有刷新：关闭所有终端，重新打开
路径问题：确保使用的是正确的Python环境

🔧 环境刷新检查运行这个命令确认当前Python环境：

Code:

where python
where pip
python -c "import sys; print(sys.executable)"

📌 关于sentence-transformers警告完全忽略这个警告：

Code:

transformers 4.36.2

是Intel PyTorch XPU的兼容版本
Code:

sentence-transformers

仍然可以正常工作
如果你想消除警告（可选）：

Code:

pip install transformers==4.41.0 --upgrade

🎯 下一步

先运行上面的XPU测试脚本，告诉我输出结果
如果测试成功，尝试启动ComfyUI
如果仍有

Code:

aoti_custom_ops.dll

错误，请运行环境检查命令

你的安装在技术上是成功的，现在需要确认运行环境是否正确。7、Traceback(most...问题详情： Traceback(most recent call last): File "E:\AI\ComfyUI\ComfyUI\main.py", line 135, in import comfy.utils File "E:\AI\ComfyUI\ComfyUI\comfy\utils.py", line 20, in import torch File "

\Program Files\Python310\lib\site-packages\torch_init_.py", line 262, in load_dll_libraries() File "\Program Files\Python310\lib\site-packages\torch_init.py", line 258, in _load_dll_libraries raise err OSError:[WinError 126] 找不到指定的模块。Error loading "

\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll" or one of its dependencies.回答（Answer）：看来问题确实出在系统路径或DLL依赖上。让我帮你一步步诊断和解决。🔍 问题诊断从错误信息看，

Code:

aoti_custom_ops.dll

文件存在但它的依赖项缺失。这通常是：

Intel运行时库没有正确安装
系统PATH环境变量缺少关键路径
DLL依赖链断裂

🛠️ 解决方案步骤步骤1：检查实际文件状态运行这些命令确认文件真实存在：

Code:

# 检查DLL文件
dir "D:\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll"

# 检查文件大小
powershell "Get-Item 'D:\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll' | Select-Object Length, LastWriteTime"

步骤2：检查依赖项（关键步骤）创建一个Python脚本检查依赖：

Code:

import os
import subprocess

dll_path = r"D:\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll"
print(f"检查DLL:

{dll_path}
")
print(f"文件存在:

{os.path.exists(dll_path)}
")

if os.path.exists(dll_path):
# 使用dumpbin检查依赖（需要Visual Studio或Windows SDK）
try:
result = subprocess.run(['dumpbin', '/dependents', dll_path],
capture_output=True, text=True, shell=True)
if result.returncode == 0:
print("\nDLL依赖项:")
print(result.stdout)
else:
print("无法运行dumpbin，尝试其他方法...")
except:
print("dumpbin不可用，安装Visual Studio或Windows SDK")

# 简单检查同目录下的其他DLL
lib_dir = os.path.dirname(dll_path)
print(f"\n同目录下DLL文件:")
for f in os.listdir(lib_dir):
if f.endswith('.dll'):
print(f" -

{f}
")

步骤3：手动安装Intel运行时依赖这是最可能的问题所在。尝试从Intel源安装这些包：

Code:

# 尝试安装关键依赖
pip install dpcpp-cpp-rt oneccl-bind-pt --index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/

步骤4：修复系统PATH（重要）Intel运行时需要特定的系统路径。手动添加：

Code:

# 检查当前PATH
python -c "import os; print('当前PATH:'); [print(p) for p in os.environ['PATH'].split(';') if 'intel' in p.lower() or 'oneapi' in p.lower()]"

如果没有Intel相关路径，需要：

下载并安装 Intel® oneAPI Base Toolkit
安装后重启系统
或者手动添加环境变量

步骤5：临时解决方案-使用虚拟环境创建一个干净的虚拟环境，避免系统环境干扰：

Code:

# 创建虚拟环境
cd E:\AI\ComfyUI\ComfyUI
python -m venv venv_xpu

# 激活虚拟环境
venv_xpu\Scripts\activate

# 在虚拟环境中安装
pip install torch==2.5.1+cxx11.abi torchvision==0.20.1+cxx11.abi torchaudio==2.5.1+cxx11.abi intel-extension-for-pytorch==2.5.10+xpu --index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/

# 测试
python -c "import torch; print(f'XPU可用:

{torch.xpu.is_available()}
')"

步骤6：诊断脚本（综合检查）运行这个完整诊断脚本：

Code:

import os
import sys
import subprocess

def check_system():
print("=" * 60)
print("PyTorch XPU 系统诊断")
print("=" * 60)

# 1. 检查Python环境
print("\n1. Python环境:")
print(f" 解释器:

{sys.executable}
")
print(f" 版本:

{sys.version}
")

# 2. 检查关键文件
dll_path = r"D:\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll"
print(f"\n2. 关键文件检查:")
print(f" aoti_custom_ops.dll:

{dll_path}
")

if os.path.exists(dll_path):
size_mb = os.path.getsize(dll_path) / (1024*1024)
print(f" ✅ 文件存在 (

{size_mb:.1f}
MB)")

# 检查目录内容
lib_dir = os.path.dirname(dll_path)
dll_count = sum(1 for f in os.listdir(lib_dir) if f.endswith('.dll'))
print(f" 同目录DLL数量:

{dll_count}
")
else:
print(f" ❌ 文件不存在")
# 查找可能的其他位置
print(f" 搜索torch目录...")
for root, dirs, files in os.walk(r"D:\Program Files\Python310\lib\site-packages"):
if "aoti_custom_ops.dll" in files:
print(f" 找到在:

{os.path.join(root, 'aoti_custom_ops.dll')}
")
break

# 3. 检查环境变量
print(f"\n3. 环境变量检查:")
path_vars = os.environ.get('PATH', '').split(';')
intel_paths = [p for p in path_vars if 'intel' in p.lower() or 'oneapi' in p.lower()]
if intel_paths:
print(f" 找到Intel相关路径:")
for p in intel_paths[:3]: # 只显示前3个
print(f" -

{p}
")
else:
print(f" ⚠️ 未找到Intel相关路径")

# 4. 尝试导入测试
print(f"\n4. 导入测试:")
try:
import torch
print(f" ✅ torch导入成功:

{torch.__version__}
")
try:
import intel_extension_for_pytorch as ipex
print(f" ✅ IPEX导入成功:

{ipex.__version__}
")
except ImportError as e:
print(f" ❌ IPEX导入失败:

{e}
")
except Exception as e:
print(f" ❌ torch导入失败:

{e}
")

if __name__ == "__main__":
check_system()

🎯 快速修复方案如果以上步骤太复杂，最简单的解决方案：方案A：使用conda（推荐）

Code:

# 安装miniconda后
conda create -n comfyui-xpu python=3.10
conda activate comfyui-xpu
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
# 或者尝试Intel的conda频道（如果有）

方案B：回退到CPU版本

Code:

pip uninstall torch torchvision torchaudio intel-extension-for-pytorch -y
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

📋 请提供以下信息请运行步骤2的依赖检查脚本或步骤6的综合诊断脚本，然后告诉我：

文件是否存在？
同目录下有多少个DLL文件？
系统中是否有Intel/oneAPI相关路径？

这样我能更精确地定位问题。8、PS E:\AI> # 检查D...问题详情： PS E:\AI> # 检查DLL文件

dir "\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll"检查文件大小powershell "Get-Item '\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll' | Select-Object Length, LastWriteTime"

\Program Files\Python310\lib\site-packages\torch\libMode LastWriteTime Length Name-a----2026/1/17 4:35 218624 aoti_custom_ops.dllLength LastWriteTime218624 2026/1/17 4:35:39;E:\AI>python check_deps.py 检查DLL:

\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll 文件存在: True 无法运行dumpbin，尝试其他方法...同目录下DLL文件: -aoti_custom_ops.dll -asmjit.dll -backend_with_compiler.dll -c10.dll -c10_xpu.dll -fbgemm.dll -jitbackend_test.dll -shm.dll -torch.dll -torchbind_test.dll -torch_cpu.dll -torch_global_deps.dll -torch_python.dll -torch_xpu.dll -torch_xpu_ops_aten.dll -torch_xpu_ops_sycl_activation_kernels.dll -torch_xpu_ops_sycl_binary_kernels.dll -torch_xpu_ops_sycl_foreach_kernels.dll -torch_xpu_ops_sycl_kernels.dll -torch_xpu_ops_sycl_reduce_kernels.dll -torch_xpu_ops_sycl_unary_kernels.dll回答（Answer）：很好！现在我知道问题了。

Code:

aoti_custom_ops.dll

文件存在，而且同目录下有

Code:

torch_xpu.dll

和其他Intel XPU相关的DLL。问题在于

Code:

aoti_custom_ops.dll

缺少某个系统级的依赖项。🎯 问题根源从你的输出可以看到：

✅

Code:

aoti_custom_ops.dll

文件存在(218KB)
✅ Intel XPU相关的DLL都在同一目录
❌ 但加载时缺少某个系统级依赖

这个缺失的依赖很可能是：

Intel DPCPP运行时(最可能)
Microsoft VC++ Redistributable
Intel GPU驱动组件

🛠️ 解决方案方案1：安装Intel运行时（最可能解决问题）

Code:

# 尝试安装这些关键包
pip install dpcpp-cpp-rt oneccl-bind-pt --index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/

方案2：使用Dependency Walker检查（可视化工具）

下载 Dependency Walker
打开

Code:

D:\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll
它会显示红色标记的缺失DLL

方案3：安装必要的系统组件运行这些安装程序：

Microsoft Visual C++ Redistributable (必须)
Intel GPU驱动 (最新版)
Intel oneAPI Base Toolkit (完整运行时)

方案4：手动修复PATH环境变量创建一个修复脚本

Code:

fix_path.py

：

Code:

import os
import sys

# 获取当前PATH
path = os.environ.get('PATH', '')

# 需要添加的Intel相关路径
intel_paths = [
r"C:\Program Files (x86)\Intel\oneAPI", # 常见oneAPI安装路径
r"C:\Program Files\Intel\oneAPI",
r"C:\Windows\System32", # 系统DLL
]

print("当前PATH中的Intel相关路径:")
for p in path.split(';'):
if 'intel' in p.lower() or 'oneapi' in p.lower():
print(f" -

{p}
")

print("\n建议检查的路径:")
for suggested in intel_paths:
if os.path.exists(suggested):
print(f" ✅

{suggested}
(存在)")
else:
print(f" ❌

{suggested}
(不存在)")

方案5：简单临时解决方案如果上面的方案太复杂，可以先在Python中禁用DLL加载检查来启动ComfyUI：创建一个启动脚本

Code:

start_comfyui.py

：

Code:

import os
import sys

# 添加torch库路径
torch_lib = r"D:\Program Files\Python310\lib\site-packages\torch\lib"
if torch_lib not in os.environ.get('PATH', ''):
os.environ['PATH'] = torch_lib + ';' + os.environ.get('PATH', '')

print(f"PATH已更新，包含:

{torch_lib}
")

# 现在导入torch
try:
import torch
print(f"✅ torch导入成功:

{torch.__version__}
")

# 检查XPU
if hasattr(torch, 'xpu') and torch.xpu.is_available():
print(f"✅ XPU可用:

{torch.xpu.get_device_name(0)}
")
else:
print("⚠️ XPU不可用，将使用CPU")

# 启动ComfyUI
import subprocess
print("\n启动ComfyUI...")
subprocess.run([sys.executable, "main.py"])

except Exception as e:
print(f"❌ 错误:

{e}
")
print("\n尝试直接启动ComfyUI...")
subprocess.run([sys.executable, "main.py"])

然后在ComfyUI目录运行：

Code:

python start_comfyui.py

方案6：最彻底的解决方案-全新虚拟环境

Code:

# 1. 创建全新环境
cd E:\AI\ComfyUI\ComfyUI
python -m venv venv_xpu

# 2. 激活
venv_xpu\Scripts\activate

# 3. 升级pip
python -m pip install --upgrade pip

# 4. 先安装基础依赖
pip install wheel setuptools

# 5. 安装Intel PyTorch（带所有依赖）
pip install torch==2.5.1+cxx11.abi torchvision==0.20.1+cxx11.abi torchaudio==2.5.1+cxx11.abi intel-extension-for-pytorch==2.5.10+xpu dpcpp-cpp-rt oneccl-bind-pt --index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/

# 6. 测试
python -c "import torch; print(f'XPU可用:

{torch.xpu.is_available()}
')"

📋 建议的执行顺序

首先尝试方案1：

Code:

pip install dpcpp-cpp-rt oneccl-bind-pt
如果不行，下载并安装方案3 的VC++ Redistributable和Intel GPU驱动
再尝试方案6 的虚拟环境方法
最后用方案5 的启动脚本测试

🚨 重要检查运行这个命令看看是否已经安装了必要的组件：

Code:

# 检查已安装的Intel相关包
pip list | findstr -i "dpcpp|oneccl|intel"

请先尝试方案1，然后告诉我结果。如果

Code:

dpcpp-cpp-rt

安装失败，我会给你更具体的解决方案。9、E:\AI>pip insta...问题详情： E:\AI>pip install dpcpp-cpp-rt oneccl-bind-pt--index-url [url] pytorch-extension.intel.com/release-whl/stable/xpu/us/ [/url] Looking in indexes: [url] pytorch-extension.intel.com/release-whl/stable/xpu/us/ [/url] Requirement already satisfied: dpcpp-cpp-rt in d:\program files\python310\lib\site-packages(2025.0.4) ERROR: Could not find a version that satisfies the requirement oneccl-bind-pt(from versions: none) ERROR: No matching distribution found for oneccl-bind-pt回答（Answer）：很好！

Code:

dpcpp-cpp-rt

已经安装成功了。这说明关键的Intel运行时库已经在系统中了。🎯 当前状态分析✅

Code:

dpcpp-cpp-rt==2025.0.4

已安装-这是Intel XPU运行时的核心依赖 ❌

Code:

oneccl-bind-pt

找不到-但这个可能不是必需（除非你需要分布式训练）现在的问题很可能是系统PATH没有包含Intel运行时库的路径，或者需要重启Python进程/系统。🛠️ 立即生效的解决方案方案1：更新系统PATH并测试创建并运行这个脚本

Code:

test_xpu_fix.py

：

Code:

import os
import sys
import subprocess

def fix_and_test():
print("=" * 60)
print("Intel XPU 环境修复与测试")
print("=" * 60)

# 1. 添加torch库路径到系统PATH（当前会话）
torch_lib = r"D:\Program Files\Python310\lib\site-packages\torch\lib"
current_path = os.environ.get('PATH', '')

if torch_lib not in current_path:
os.environ['PATH'] = torch_lib + ';' + current_path
print(f"✅ 已将torch库添加到PATH:

{torch_lib}
")
else:
print(f"✅ torch库已在PATH中")

# 2. 查找dpcpp运行时的位置
print("\n搜索dpcpp运行时库...")
dpcpp_paths = []

# 常见安装位置
search_paths = [
r"D:\Program Files\Python310\Lib\site-packages",
r"D:\Program Files\Python310\Lib\site-packages\dpcpp_cpp_rt",
r"C:\Program Files (x86)\Intel\oneAPI",
r"C:\Program Files\Intel\oneAPI",
]

for path in search_paths:
if os.path.exists(path):
print(f" 检查:

{path}
")
# 递归查找.dll文件
for root, dirs, files in os.walk(path):
if any(f.endswith('.dll') and 'dpcpp' in f.lower() for f in files):
if root not in current_path and root not in dpcpp_paths:
dpcpp_paths.append(root)
print(f" ✅ 找到:

{root}
")

# 3. 添加找到的路径到PATH
for path in dpcpp_paths:
if path not in os.environ.get('PATH', ''):
os.environ['PATH'] = path + ';' + os.environ.get('PATH', '')
print(f"✅ 已添加dpcpp路径:

{path}
")

# 4. 现在尝试导入torch
print("\n尝试导入torch...")
try:
import torch
print(f"✅ torch导入成功! 版本:

{torch.__version__}
")

# 检查扩展属性
print(f"torch模块属性包含'xpu': {'xpu' in dir(torch)}")

# 尝试访问xpu
if hasattr(torch, 'xpu'):
print("✅ torch.xpu 属性存在")
try:
available = torch.xpu.is_available()
print(f"✅ torch.xpu.is_available() =

{available}
")

if available:
print(f"🎉 XPU设备:

{torch.xpu.get_device_name(0)}
")
return True
else:
print("⚠️ XPU不可用，但torch.xpu模块加载成功")
return True
except Exception as e:
print(f"❌ torch.xpu.is_available() 失败:

{e}
")
return False
else:
print("❌ torch.xpu 属性不存在")
return False

except Exception as e:
print(f"❌ torch导入失败:

{e}
")
return False

if __name__ == "__main__":
success = fix_and_test()

if success:
print("\n" + "=" * 60)
print("✅ 环境修复成功！现在可以启动ComfyUI")
print("=" * 60)

# 询问是否立即启动ComfyUI
response = input("\n立即启动ComfyUI? (y/n): ")
if response.lower() == 'y':
comfy_path = r"E:\AI\ComfyUI\ComfyUI"
if os.path.exists(os.path.join(comfy_path, "main.py")):
print(f"\n启动ComfyUI...")
os.chdir(comfy_path)
os.system("python main.py")
else:
print(f"未找到ComfyUI主文件:

{comfy_path}
")
else:
print("\n" + "=" * 60)
print("❌ 需要进一步修复")
print("=" * 60)

方案2：使用加载劫持技术如果上面的方法不行，这个脚本会在导入torch前预加载必要的DLL：

Code:

import os
import sys
import ctypes

# 预加载可能的依赖DLL
def preload_dependencies():
print("预加载DLL依赖...")

dlls_to_try = [
# Intel运行时DLL
"sycl.dll",
"OpenCL.dll",
"ze_loader.dll",
"ze_intel_gpu64_1.dll",

# 系统DLL
"vcruntime140.dll",
"vcruntime140_1.dll",
"msvcp140.dll",
"concrt140.dll",
]

# torch库目录
torch_lib = r"D:\Program Files\Python310\lib\site-packages\torch\lib"

for dll_name in dlls_to_try:
# 先尝试系统目录
try:
ctypes.WinDLL(dll_name)
print(f" ✅ 预加载系统

{dll_name}
")
except:
# 尝试torch目录
dll_path = os.path.join(torch_lib, dll_name)
if os.path.exists(dll_path):
try:
ctypes.WinDLL(dll_path)
print(f" ✅ 预加载

{dll_path}
")
except:
pass

# 添加torch目录到PATH
os.environ['PATH'] = torch_lib + ';' + os.environ.get('PATH', '')

# 执行预加载
preload_dependencies()

# 现在导入torch
print("\n导入torch...")
import torch
print(f"✅ torch导入成功:

{torch.__version__}
")

if hasattr(torch, 'xpu'):
print(f"XPU可用性:

{torch.xpu.is_available()}
")
else:
print("❌ torch.xpu不存在")

方案3：直接启动ComfyUI的包装脚本创建

Code:

launch_comfyui.bat

：

Code:

@echo off
chcp 65001
echo ========================================
echo ComfyUI with Intel XPU 启动器
echo ========================================

REM 设置环境变量
set "TORCH_LIB=D:\Program Files\Python310\lib\site-packages\torch\lib"
set "PATH=%TORCH_LIB%;%PATH%"

REM 添加可能的Intel路径
set "INTEL_PATHS=C:\Program Files (x86)\Intel\oneAPI\compiler\latest\windows\bin;C:\Program Files\Intel\oneAPI\compiler\latest\windows\bin"
set "PATH=%INTEL_PATHS%;%PATH%"

echo 环境PATH已更新
echo.

REM 切换到ComfyUI目录
cd /d "E:\AI\ComfyUI\ComfyUI"

REM 启动ComfyUI
echo 启动ComfyUI...
echo ========================================
python main.py

pause

方案4：终极方案-使用进程注入如果以上都不行，这个脚本使用更高级的技术：

Code:

import os
import sys
import ctypes
from ctypes import wintypes

# 使用Windows API手动加载DLL
kernel32 = ctypes.WinDLL('kernel32', use_last_error=True)

# 设置DLL搜索路径
def set_dll_directory(path):
kernel32.SetDllDirectoryW(path)
print(f"设置DLL搜索路径:

{path}
")

# 加载DLL并解析依赖
def load_dll_chain(dll_path):
"""递归加载DLL及其依赖"""
if not os.path.exists(dll_path):
print(f"文件不存在:

{dll_path}
")
return None

try:
# 尝试加载
dll = ctypes.WinDLL(dll_path)
print(f"✅ 成功加载:

{os.path.basename(dll_path)}
")
return dll
except OSError as e:
print(f"❌ 加载失败

{os.path.basename(dll_path)}
:

{e}
")

# 尝试加载依赖
if "找不到指定的模块" in str(e) or "126" in str(e):
# 这是一个依赖错误，尝试找到并加载依赖
base_dir = os.path.dirname(dll_path)
possible_deps = ["sycl.dll", "OpenCL.dll", "ze_loader.dll"]

for dep in possible_deps:
dep_path = os.path.join(base_dir, dep)
if os.path.exists(dep_path):
print(f" 尝试加载依赖:

{dep}
")
load_dll_chain(dep_path)

# 再次尝试
try:
dll = ctypes.WinDLL(dll_path)
print(f"✅ 重新加载成功:

{os.path.basename(dll_path)}
")
return dll
except:
pass

return None

# 主修复函数
def fix_dll_loading():
print("=" * 60)
print("DLL加载修复")
print("=" * 60)

# 关键DLL路径
target_dll = r"D:\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll"
torch_lib_dir = os.path.dirname(target_dll)

# 1. 设置DLL搜索路径
set_dll_directory(torch_lib_dir)

# 2. 添加路径到系统PATH（当前进程）
os.environ['PATH'] = torch_lib_dir + ';' + os.environ.get('PATH', '')

# 3. 预加载关键DLL
print("\n预加载依赖链...")

# 先加载可能的系统依赖
system_dlls = [
"vcruntime140.dll",
"msvcp140.dll",
"concrt140.dll",
]

for dll in system_dlls:
try:
ctypes.WinDLL(dll)
print(f" ✅ 系统DLL:

{dll}
")
except:
pass

# 加载Intel运行时DLL
intel_dlls = [
"sycl.dll",
"OpenCL.dll",
"ze_loader.dll",
]

for dll in intel_dlls:
dll_path = os.path.join(torch_lib_dir, dll)
if os.path.exists(dll_path):
load_dll_chain(dll_path)

# 4. 最后尝试加载目标DLL
print(f"\n加载目标DLL: aoti_custom_ops.dll")
result = load_dll_chain(target_dll)

return result is not None

# 执行修复
if fix_dll_loading():
print("\n" + "=" * 60)
print("✅ DLL加载修复完成！")
print("现在应该可以导入torch了")
print("=" * 60)

# 测试导入
try:
import torch
print(f"\ntorch导入成功! 版本:

{torch.__version__}
")

if hasattr(torch, 'xpu'):
print(f"torch.xpu可用性:

{torch.xpu.is_available()}
")
except Exception as e:
print(f"\n❌ 导入失败:

{e}
")
else:
print("\n❌ 修复失败，需要其他方法")

📋 建议执行顺序

先运行方案1的

Code:

test_xpu_fix.py

-最简单的PATH修复
如果不行，运行方案4的DLL加载修复脚本
再不行，使用方案3的批处理文件启动
最后考虑重启系统（有时需要重启使PATH生效）

🔍 快速测试运行这个最简单的测试：

Code:

import os
os.environ['PATH'] = r"D:\Program Files\Python310\lib\site-packages\torch\lib;" + os.environ.get('PATH', '')
import torch
print(f"导入成功! XPU可用:

{torch.xpu.is_available()}
")

请先尝试方案1，它最有可能立即解决问题！10、E:\AI>python te...问题详情： E:\AI>python test_xpu_fix.pyIntel XPU 环境修复与测试✅ 已将torch库添加到PATH:

\Program Files\Python310\lib\site-packages\torch\lib搜索dpcpp运行时库... 检查:

\Program Files\Python310\Lib\site-packages 检查: C:\Program Files(x86)\Intel\oneAPI尝试导入torch... ❌ torch导入失败:[WinError 126] 找不到指定的模块。Error loading "

\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll" or one of its dependencies.============================================================❌ 需要进一步修复回答（Answer）： 看来问题更深入一些。

Code:

aoti_custom_ops.dll

本身或它的直接依赖项缺失了关键的系统级DLL。让我们用更专业的方法来解决。🔍 深入诊断问题出在：即使添加了PATH，Windows仍然找不到

Code:

aoti_custom_ops.dll

的某个依赖DLL。我们需要找出具体是哪个DLL缺失。🛠️ 专业级解决方案方案1：使用Process Monitor实时追踪这是最有效的诊断方法：

下载 Process Monitor
运行Process Monitor
设置过滤器：
- Code:
  
  Process Name``is``python.exe
- Code:
  
  Path``ends with``.dll
- Code:
  
  Result``is``NAME NOT FOUND
运行Python导入torch
查看哪些DLL找不到

方案2：手动查找并修复依赖链运行这个增强版诊断脚本：

Code:

import os
import ctypes
import sys

def diagnose_dll_issues():
print("=" * 70)
print("DLL依赖链深度诊断")
print("=" * 70)

target_dll = r"D:\Program Files\Python310\lib\site-packages\torch\lib\aoti_custom_ops.dll"
torch_lib = os.path.dirname(target_dll)

print(f"目标DLL:

{target_dll}
")
print(f"文件存在:

{os.path.exists(target_dll)}
")
print(f"文件大小:

{os.path.getsize(target_dll) / 1024:.1f}
KB")

# 1. 首先检查Windows系统DLL
print("\n1. 检查关键系统DLL:")
system_dlls = [
("vcruntime140.dll", "VC++ 2015-2022 Redistributable"),
("vcruntime140_1.dll", "VC++ 2015-2022 Redistributable"),
("msvcp140.dll", "VC++ 2015-2022 Redistributable"),
("concrt140.dll", "VC++ 2015-2022 Redistributable"),
("ucrtbase.dll", "Windows Universal CRT"),
("api-ms-win-crt-runtime-l1-1-0.dll", "Windows CRT"),
]

for dll_name, description in system_dlls:
try:
ctypes.WinDLL(dll_name)
print(f" ✅

{dll_name:30}
(

{description}
)")
except OSError:
print(f" ❌

{dll_name:30}
(

{description}
) - 缺失!")

# 2. 检查Intel运行时DLL
print("\n2. 检查Intel运行时DLL:")

# 在多个位置查找
search_paths = [
torch_lib,
r"C:\Windows\System32",
r"C:\Windows\SysWOW64",
r"C:\Program Files (x86)\Intel\oneAPI\compiler\latest\windows\bin",
r"C:\Program Files\Intel\oneAPI\compiler\latest\windows\bin",
]

intel_dlls = ["sycl.dll", "OpenCL.dll", "ze_loader.dll", "ze_intel_gpu64_1.dll"]

for dll_name in intel_dlls:
found = False
for path in search_paths:
dll_path = os.path.join(path, dll_name)
if os.path.exists(dll_path):
print(f" ✅

{dll_name:25}
在

{path}
")
found = True
break

if not found:
print(f" ❌

{dll_name:25}
- 在所有位置都未找到!")

# 3. 使用LoadLibraryEx进行更详细的错误检查
print("\n3. 使用Windows API加载测试:")

# 定义Windows API函数
kernel32 = ctypes.WinDLL('kernel32', use_last_error=True)
LoadLibraryExW = kernel32.LoadLibraryExW
LoadLibraryExW.argtypes = [wintypes.LPCWSTR, wintypes.HANDLE, wintypes.DWORD]
LoadLibraryExW.restype = wintypes.HMODULE

GetLastError = kernel32.GetLastError
FormatMessageW = kernel32.FormatMessageW
FormatMessageW.argtypes = [wintypes.DWORD, wintypes.LPCVOID, wintypes.DWORD,
wintypes.DWORD, wintypes.LPWSTR, wintypes.DWORD,
wintypes.LPVOID]
FormatMessageW.restype = wintypes.DWORD

# 尝试加载DLL并获取详细错误
hmodule = LoadLibraryExW(target_dll, None, 0x00000008) # LOAD_WITH_ALTERED_SEARCH_PATH
if hmodule:
print(f" ✅ 成功加载 aoti_custom_ops.dll (句柄:

{hmodule}
)")
kernel32.FreeLibrary(hmodule)
else:
error_code = GetLastError()

# 获取错误信息
buf = ctypes.create_unicode_buffer(256)
FormatMessageW(0x00001000, None, error_code, 0, buf, len(buf), None)

print(f" ❌ 加载失败! 错误代码:

{error_code}
")
print(f" 错误信息:

{buf.value}
")

# 根据错误代码给出建议
if error_code == 126: # ERROR_MOD_NOT_FOUND
print(f" 建议: 某个依赖DLL缺失，需要安装Intel oneAPI或VC++ Redistributable")
elif error_code == 193: # ERROR_BAD_EXE_FORMAT
print(f" 建议: DLL架构不匹配 (可能是32位/64位问题)")
elif error_code == 14001: # ERROR_SXS_CANT_GEN_ACTCTX
print(f" 建议: 需要安装Microsoft Visual C++ Redistributable")

return hmodule is not None

if __name__ == "__main__":
import ctypes.wintypes as wintypes
success = diagnose_dll_issues()

if not success:
print("\n" + "=" * 70)
print("💡 修复建议:")
print("1. 安装 Microsoft Visual C++ Redistributable 2015-2022")
print(" 下载: https://aka.ms/vs/17/release/vc_redist.x64.exe")
print("\n2. 安装 Intel oneAPI Base Toolkit")
print(" 下载: https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html")
print("\n3. 确保使用最新Intel GPU驱动")
print(" 下载: https://www.intel.com/content/www/us/en/download/726609/")
print("=" * 70)

方案3：强制使用延迟加载（高级技巧）创建一个特殊的导入器

Code:

torch_loader.py

：

Code:

"""
强制加载Intel PyTorch XPU的专用加载器
"""
import os
import sys
import ctypes

class TorchXpuLoader:
def __init__(self):
self._fix_environment()
self._preload_libraries()

def _fix_environment(self):
"""修复环境变量"""
# 添加torch库路径
torch_lib = r"D:\Program Files\Python310\lib\site-packages\torch\lib"
os.environ['PATH'] = torch_lib + ';' + os.environ.get('PATH', '')

# 设置Python的DLL搜索路径
if hasattr(os, 'add_dll_directory'):
os.add_dll_directory(torch_lib)

print(f"[环境] 已添加

{torch_lib}
到搜索路径")

def _preload_libraries(self):
"""预加载所有可能需要的DLL"""
dll_load_order = [
# 1. Windows系统DLL
"vcruntime140.dll",
"vcruntime140_1.dll",
"msvcp140.dll",
"concrt140.dll",

# 2. Intel运行时DLL (按依赖顺序)
"ze_loader.dll",
"OpenCL.dll",
"sycl.dll",

# 3. Torch基础DLL
"c10.dll",
"c10_xpu.dll",
"torch_cpu.dll",
"torch_xpu.dll",

# 4. 最后是目标DLL
"aoti_custom_ops.dll",
]

print("[预加载] 开始加载依赖链...")

for dll_name in dll_load_order:
try:
# 先尝试系统加载
ctypes.WinDLL(dll_name)
print(f" ✅ 系统:

{dll_name}
")
except OSError:
# 尝试从torch目录加载
dll_path = os.path.join(
r"D:\Program Files\Python310\lib\site-packages\torch\lib",
dll_name
)
if os.path.exists(dll_path):
try:
ctypes.WinDLL(dll_path)
print(f" ✅ 本地:

{dll_name}
")
except OSError as e:
print(f" ❌ 失败:

{dll_name}
-

{e}
")
else:
print(f" ⚠️ 缺失:

{dll_name}
")

def load_torch(self):
"""加载torch模块"""
print("[导入] 正在导入torch...")
try:
import torch
print(f"✅ torch导入成功! 版本:

{torch.__version__}
")

# 验证XPU
if hasattr(torch, 'xpu'):
available = torch.xpu.is_available()
print(f"📊 XPU可用性:

{available}
")
if available:
print(f"🎯 XPU设备:

{torch.xpu.get_device_name(0)}
")
return True
else:
print("⚠️ torch.xpu属性不存在")
return False

except Exception as e:
print(f"❌ torch导入失败:

{e}
")
return False

# 使用示例
if __name__ == "__main__":
loader = TorchXpuLoader()
if loader.load_torch():
print("\n" + "=" * 50)
print("✅ 加载成功! 可以启动ComfyUI")
print("=" * 50)

# 启动ComfyUI
comfy_path = r"E:\AI\ComfyUI\ComfyUI"
if os.path.exists(os.path.join(comfy_path, "main.py")):
import subprocess
print(f"\n启动ComfyUI...")
os.chdir(comfy_path)
subprocess.run([sys.executable, "main.py"])
else:
print("\n❌ 加载失败，需要进一步修复")

方案4：使用注册表修复DLL搜索路径创建注册表修复脚本

Code:

fix_dll_registry.reg

：

Code:

Windows Registry Editor Version 5.00

[HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\Session Manager\KnownDLLs]
"aoti_custom_ops.dll"=-

[HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\Session Manager]
"ExcludeFromKnownDlls"=hex(7):61,00,6f,00,74,00,69,00,5f,00,63,00,75,00,73,\
00,74,00,6f,00,6d,00,5f,00,6f,00,70,00,73,00,2e,00,64,00,6c,00,6c,00,00,\
00,00,00

; 添加DLL搜索路径
[HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\Session Manager\Environment]
"PATH"=hex(2):44,00,3a,00,5c,00,50,00,72,00,6f,00,67,00,72,00,61,00,6d,00,\
20,00,46,00,69,00,6c,00,65,00,73,00,5c,00,50,00,79,00,74,00,68,00,6f,00,\
6e,00,33,00,31,00,30,00,5c,00,6c,00,69,00,62,00,5c,00,73,00,69,00,74,00,\
65,00,2d,00,70,00,61,00,63,00,6b,00,61,00,67,00,65,00,73,00,5c,00,74,00,\
6f,00,72,00,63,00,68,00,5c,00,6c,00,69,00,62,00,3b,00,25,00,50,00,41,00,\
54,00,48,00,25,00,00,00

警告： 修改注册表有风险，请先备份！方案5：最简单的临时方案如果以上都太复杂，先用CPU版本启动ComfyUI，以后再解决XPU问题：

Code:

# 暂时使用CPU版本
pip uninstall torch torchvision torchaudio intel-extension-for-pytorch -y
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu

# 启动ComfyUI
cd E:\AI\ComfyUI\ComfyUI
python main.py

📋 建议操作顺序

先运行方案2的诊断脚本 -查看具体缺失哪些DLL
根据诊断结果安装缺失的运行时（VC++ Redistributable或Intel oneAPI）
尝试方案3的专用加载器
如果着急使用，先用方案5的CPU版本

🔍 结论：依赖太凌乱，只能重新从头安装

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