PyTorch模型TorchScript导出与libtorch C++加载报错求助

问题概述 #

在GPU上用PyTorch训练模型后，保存为PT(H)文件，尝试通过libtorch在C++环境中加载时，触发Unrecognized data format错误，目前正测试基础的导出/导入功能。

错误信息 #

Error loading model
Unrecognized data format
Exception raised from load at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\jit\serialization\import.cpp:449 (most recent call first):
00007FFBB1FFDA2200007FFBB1FFD9C0 c10.dll!c10::Error::Error [<unknown file> @ <unknown line number>]
00007FFBB1FFD43E00007FFBB1FFD3F0 c10.dll!c10::detail::torchCheckFail [<unknown file> @ <unknown line number>]
00007FFB4B87B54700007FFB4B87B4E0 torch_cpu.dll!torch::jit::load [<unknown file> @ <unknown line number>]
00007FFB4B87B42A00007FFB4B87B380 torch_cpu.dll!torch::jit::load [<unknown file> @ <unknown line number>]
00007FF6089A737A00007FF6089A7210 pytroch_load_model.exe!main [c:\users\USER\projects\cmake dx cuda pytorch\cmake_integration_examples\pytorch\src\pytroch_load_model.cpp @ 19]
00007FF6089D8A9400007FF6089D8A60 pytroch_load_model.exe!invoke_main [d:\agent\_work\2\s\src\vctools\crt\vcstartup\src\startup\exe_common.inl @ 79]
00007FF6089D893E00007FF6089D8810 pytroch_load_model.exe!__scrt_common_main_seh [d:\agent\_work\2\s\src\vctools\crt\vcstartup\src\startup\exe_common.inl @ 288]
00007FF6089D87FE00007FF6089D87F0 pytroch_load_model.exe!__scrt_common_main [d:\agent\_work\2\s\src\vctools\crt\vcstartup\src\startup\exe_common.inl @ 331]
00007FF6089D8B2900007FF6089D8B20 pytroch_load_model.exe!mainCRTStartup [d:\agent\_work\2\s\src\vctools\crt\vcstartup\src\startup\exe_main.cpp @ 17]
00007FFBDF8C703400007FFBDF8C7020 KERNEL32.DLL!BaseThreadInitThunk [<unknown file> @ <unknown line number>]
00007FFBDFBA265100007FFBDFBA2630 ntdll.dll!RtlUserThreadStart [<unknown file> @ <unknown line number>]

相关代码 #

Python（PyTorch） #

import torch
import torch.nn as nn
import torch.nn.functional as F

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(3, 6, 5)
        self.pool = nn.MaxPool2d(2, 2)
        self.conv2 = nn.Conv2d(6, 16, 5)
        self.fc1 = nn.Linear(16 * 5 * 5, 120)
        self.fc2 = nn.Linear(120, 84)
        self.fc3 = nn.Linear(84, 10)

    def forward(self, x):
        x = self.pool(F.relu(self.conv1(x)))
        x = self.pool(F.relu(self.conv2(x)))
        x = x.view(-1, 16 * 5 * 5)
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return x

class TestModel(nn.Module):
    def __init__(self):
        super(TestModel, self).__init__()
        self.x = 2

    def forward(self):
        return self.x

test_net = torch.jit.script(Net())
test_module = torch.jit.script(TestModel())
torch.jit.save(test_net, 'test_net.pt')
torch.jit.save(test_module, 'test_module.pt')

C++（libtorch） #

#include <torch/script.h>
#include <iostream>
#include <memory>

int main(int argc, const char* argv[]) {
    if (argc != 2) {
        std::cerr << "usage: example-app <path-to-exported-script-module>\n";
        return -1;
    }

    torch::jit::script::Module module;
    try {
        std::cout << "Trying to load model..." << std::endl;
        // Deserialize the ScriptModule from a file using torch::jit::load().
        module = torch::jit::load(argv[1]);
    }
    catch (const c10::Error& e) {
        std::cerr << "Loading failed" << std::endl;
        std::cerr << e.what() << std::endl;
        return -1;
    }

    std::cout << "Loading successful" << std::endl;
}

CMakeLists.txt #

cmake_minimum_required (VERSION 3.12 FATAL_ERROR)

project(pytroch
  DESCRIPTION "CMake example for PyTorch (libtorch C++) integration"
  LANGUAGES CXX
)

set(CMAKE_CXX_STANDARD 14)

set(SRC_DIR "${CMAKE_CURRENT_SOURCE_DIR}/src")
set(CMAKE_PREFIX_PATH "${CMAKE_SOURCE_DIR}/deps/libtorch/1.12.1/release/cpu/share/cmake/Torch")
find_package(Torch REQUIRED)
if(TORCH_FOUND)
    message(STATUS "Found Torch")
else()
    message(CRITICAL_ERROR "Unable to find Torch")
endif(TORCH_FOUND)

add_executable(pytroch_load_model
    "${SRC_DIR}/pytroch_load_model.cpp"
)
target_include_directories(pytroch_load_model PUBLIC ${TORCH_INCLUDE_DIRS})
target_link_libraries(pytroch_load_model PRIVATE ${TORCH_LIBRARIES})
message("${TORCH_LIBRARIES}")
file(GLOB LIBTORCH_DLLS
  "${CMAKE_SOURCE_DIR}/deps/libtorch/1.12.1/release/cpu/lib/*.dll"
)
file(COPY
    ${LIBTORCH_DLLS}
    DESTINATION "${CMAKE_BINARY_DIR}/bin/"
)

环境信息 #

• libtorch 1.12.1共享发行版（Windows10，已尝试CPU和GPU非调试版本）
• TestModel直接取自Torch JIT文档

排查方向 #

• 版本匹配问题：确认Python端PyTorch版本与libtorch版本完全一致（包括CUDA版本），序列化格式会随版本变化，版本不兼容是这类错误的常见原因。
• 文件完整性与路径：检查PT文件是否保存完整（可在Python中先用torch.jit.load测试加载）；C++加载时使用绝对路径，避免Windows路径分隔符转义问题。
• 模型设备一致性：如果Python端模型在GPU上，保存前需调用.cpu()转到CPU；若使用GPU版libtorch，需保证CUDA环境与Python端一致。
• libtorch配置验证：确认CMake的CMAKE_PREFIX_PATH指向正确的libtorch cmake目录，所有依赖DLL已复制到exe运行目录（比如c10.dll、torch_cpu.dll等）。

内容的提问来源于stack exchange，提问作者rbaleksandar