使用Vscode调试Pytorch(c++)代码

$ tree -d -L 1
.
├── android
├── aten
├── benchmarks
├── binaries
├── build
├── c10
├── caffe2
├── cmake
├── docs
├── functorch
├── ios
├── modules
├── mypy_plugins
├── scripts
├── test
├── third_party
├── tools
├── torch
├── torch.egg-info
└── torchgen

    # the list of runtime dependencies required by this built package
    install_requires = [
        "filelock",
        "typing-extensions>=4.8.0",
        "sympy",
        "networkx",
        "jinja2",
        "fsspec",
        'mkl>=2021.1.1,<=2021.4.0; platform_system == "Windows"',
    ]

    # Parse the command line and check the arguments before we proceed with
    # building deps and setup. We need to set values so `--help` works.
    dist = Distribution()
    dist.script_name = os.path.basename(sys.argv[0])
    dist.script_args = sys.argv[1:]
    try:
        dist.parse_command_line()
    except setuptools.distutils.errors.DistutilsArgError as e:
        print(e)
        sys.exit(1)

    mirror_files_into_torchgen()
    if RUN_BUILD_DEPS:
        build_deps()

    (
        extensions,
        cmdclass,
        packages,
        entry_points,
        extra_install_requires,
    ) = configure_extension_build()

    install_requires += extra_install_requires

    extras_require = {
        "optree": ["optree>=0.9.1"],
        "opt-einsum": ["opt-einsum>=3.3"],
    }

    # Read in README.md for our long_description
    with open(os.path.join(cwd, "README.md"), encoding="utf-8") as f:
        long_description = f.read()

    version_range_max = max(sys.version_info[1], 12) + 1
    torch_package_data = [
        "py.typed",
        "bin/*",
        "test/*",
        "*.pyi",
        "_C/*.pyi",
        "cuda/*.pyi",
        
        # ..........
        
    ]

    if get_cmake_cache_vars()["BUILD_CAFFE2"]:
        torch_package_data.extend(
            [
                "include/caffe2/**/*.h",
                "include/caffe2/utils/*.h",
                "include/caffe2/utils/**/*.h",
            ]
        )
    if get_cmake_cache_vars()["USE_TENSORPIPE"]:
        torch_package_data.extend(
            [
                "include/tensorpipe/*.h",
                "include/tensorpipe/channel/*.h",
                "include/tensorpipe/channel/basic/*.h",
                "include/tensorpipe/channel/cma/*.h",
                "include/tensorpipe/channel/mpt/*.h",
                "include/tensorpipe/channel/xth/*.h",
                "include/tensorpipe/common/*.h",
                "include/tensorpipe/core/*.h",
                "include/tensorpipe/transport/*.h",
                "include/tensorpipe/transport/ibv/*.h",
                "include/tensorpipe/transport/shm/*.h",
                "include/tensorpipe/transport/uv/*.h",
            ]
        )
    torchgen_package_data = [
        # Recursive glob doesn't work in setup.py,
        # https://github.com/pypa/setuptools/issues/1806
        # To make this robust we should replace it with some code that
        # returns a list of everything under packaged/
        "packaged/ATen/*",
        "packaged/ATen/native/*",
        "packaged/ATen/templates/*",
        "packaged/autograd/*",
        "packaged/autograd/templates/*",
    ]
    setup(
        name=package_name,
        version=version,
        description=(
            "Tensors and Dynamic neural networks in "
            "Python with strong GPU acceleration"
        ),
        long_description=long_description,
        long_description_content_type="text/markdown",
        ext_modules=extensions,
        cmdclass=cmdclass,
        packages=packages,
        entry_points=entry_points,
        install_requires=install_requires,
        extras_require=extras_require,
        package_data={
            "torch": torch_package_data,
            "torchgen": torchgen_package_data,
            "caffe2": [
                "python/serialized_test/data/operator_test/*.zip",
            ],
        },
        url="https://pytorch.org/",
        download_url="https://github.com/pytorch/pytorch/tags",
        author="PyTorch Team",
        author_email="packages@pytorch.org",
        python_requires=f">={python_min_version_str}",
        # PyPI package information.
        classifiers=[
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Mathematics",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Software Development",
            "Topic :: Software Development :: Libraries",
            "Topic :: Software Development :: Libraries :: Python Modules",
            "Programming Language :: C++",
            "Programming Language :: Python :: 3",
        ]
        + [
            f"Programming Language :: Python :: 3.{i}"
            for i in range(python_min_version[1], version_range_max)
        ],
        license="BSD-3",
        keywords="pytorch, machine learning",
    ) 

cmake -GNinja -DBUILD_PYTHON=True -DBUILD_TEST=True -DCMAKE_BUILD_TYPE=Debug -DCMAKE_INSTALL_PREFIX=/nas/lili/codes/pt/torchsrc/pytorch/torch -DCMAKE_PREFIX_PATH=/home/ubuntu/miniconda3/envs/torchbuild/lib/python3.9/site-packages -DNUMPY_INCLUDE_DIR=/home/ubuntu/miniconda3/envs/torchbuild/lib/python3.9/site-packages/numpy/core/include -DPYTHON_EXECUTABLE=/home/ubuntu/miniconda3/envs/torchbuild/bin/python -DPYTHON_INCLUDE_DIR=/home/ubuntu/miniconda3/envs/torchbuild/include/python3.9 -DPYTHON_LIBRARY=/home/ubuntu/miniconda3/envs/torchbuild/lib/libpython3.9.a -DTORCH_BUILD_VERSION=2.4.0a0+git8168338 -DUSE_NUMPY=True /nas/lili/codes/pt/torchsrc/pytorch

cmake --build . --target install --config Debug -- -j 96

class build_ext(setuptools.command.build_ext.build_ext):


    def run(self):
        # Report build options. This is run after the build completes so # `CMakeCache.txt` exists and we can get an
        # accurate report on what is used and what is not.
        cmake_cache_vars = defaultdict(lambda: False, cmake.get_cmake_cache_variables())
        if cmake_cache_vars["USE_NUMPY"]:
            report("-- Building with NumPy bindings")
        else:
            report("-- NumPy not found")
        if cmake_cache_vars["USE_CUDNN"]:
            report(
                "-- Detected cuDNN at "
                + cmake_cache_vars["CUDNN_LIBRARY"]
                + ", "
                + cmake_cache_vars["CUDNN_INCLUDE_DIR"]
            )
        else:
            report("-- Not using cuDNN")
        if cmake_cache_vars["USE_CUDA"]:
            report("-- Detected CUDA at " + cmake_cache_vars["CUDA_TOOLKIT_ROOT_DIR"])
        else:
            report("-- Not using CUDA")
        if cmake_cache_vars["USE_XPU"]:
            report("-- Detected XPU runtime at " + cmake_cache_vars["SYCL_LIBRARY_DIR"])
        else:
            report("-- Not using XPU")
        if cmake_cache_vars["USE_MKLDNN"]:
            report("-- Using MKLDNN")
            if cmake_cache_vars["USE_MKLDNN_ACL"]:
                report("-- Using Compute Library for the Arm architecture with MKLDNN")
            else:
                report(
                    "-- Not using Compute Library for the Arm architecture with MKLDNN"
                )
            if cmake_cache_vars["USE_MKLDNN_CBLAS"]:
                report("-- Using CBLAS in MKLDNN")
            else:
                report("-- Not using CBLAS in MKLDNN")
        else:
            report("-- Not using MKLDNN")
        if cmake_cache_vars["USE_NCCL"] and cmake_cache_vars["USE_SYSTEM_NCCL"]:
            report(
                "-- Using system provided NCCL library at {}, {}".format(
                    cmake_cache_vars["NCCL_LIBRARIES"],
                    cmake_cache_vars["NCCL_INCLUDE_DIRS"],
                )
            )
        elif cmake_cache_vars["USE_NCCL"]:
            report("-- Building NCCL library")
        else:
            report("-- Not using NCCL")
        if cmake_cache_vars["USE_DISTRIBUTED"]:
            if IS_WINDOWS:
                report("-- Building without distributed package")
            else:
                report("-- Building with distributed package: ")
                report(
                    "  -- USE_TENSORPIPE={}".format(cmake_cache_vars["USE_TENSORPIPE"])
                )
                report("  -- USE_GLOO={}".format(cmake_cache_vars["USE_GLOO"]))
                report("  -- USE_MPI={}".format(cmake_cache_vars["USE_OPENMPI"]))
        else:
            report("-- Building without distributed package")
        if cmake_cache_vars["STATIC_DISPATCH_BACKEND"]:
            report(
                "-- Using static dispatch with backend {}".format(
                    cmake_cache_vars["STATIC_DISPATCH_BACKEND"]
                )
            )
        if cmake_cache_vars["USE_LIGHTWEIGHT_DISPATCH"]:
            report("-- Using lightweight dispatch")
        if cmake_cache_vars["BUILD_EXECUTORCH"]:
            report("-- Building Executorch")

        if cmake_cache_vars["USE_ITT"]:
            report("-- Using ITT")
        else:
            report("-- Not using ITT")

        # Do not use clang to compile extensions if `-fstack-clash-protection` is defined
        # in system CFLAGS
        c_flags = str(os.getenv("CFLAGS", ""))
        if (
            IS_LINUX
            and "-fstack-clash-protection" in c_flags
            and "clang" in os.environ.get("CC", "")
        ):
            os.environ["CC"] = str(os.environ["CC"])

        # It's an old-style class in Python 2.7...
        setuptools.command.build_ext.build_ext.run(self)

        if IS_DARWIN and package_type != "conda":
            self._embed_libomp()

        # Copy the essential export library to compile C++ extensions.
        if IS_WINDOWS:
            build_temp = self.build_temp

            ext_filename = self.get_ext_filename("_C")
            lib_filename = ".".join(ext_filename.split(".")[:-1]) + ".lib"

            export_lib = os.path.join(
                build_temp, "torch", "csrc", lib_filename
            ).replace("\\", "/")

            build_lib = self.build_lib

            target_lib = os.path.join(build_lib, "torch", "lib", "_C.lib").replace(
                "\\", "/"
            )

            # Create "torch/lib" directory if not exists.
            # (It is not created yet in "develop" mode.)
            target_dir = os.path.dirname(target_lib)
            if not os.path.exists(target_dir):
                os.makedirs(target_dir)

            self.copy_file(export_lib, target_lib)

    def build_extensions(self):
        self.create_compile_commands()
        # The caffe2 extensions are created in
        # tmp_install/lib/pythonM.m/site-packages/caffe2/python/
        # and need to be copied to build/lib.linux.... , which will be a
        # platform dependent build folder created by the "build" command of
        # setuptools. Only the contents of this folder are installed in the
        # "install" command by default.
        # We only make this copy for Caffe2's pybind extensions
        caffe2_pybind_exts = [
            "caffe2.python.caffe2_pybind11_state",
            "caffe2.python.caffe2_pybind11_state_gpu",
            "caffe2.python.caffe2_pybind11_state_hip",
        ]
        i = 0
        while i < len(self.extensions):
            ext = self.extensions[i]
            if ext.name not in caffe2_pybind_exts:
                i += 1
                continue
            fullname = self.get_ext_fullname(ext.name)
            filename = self.get_ext_filename(fullname)
            report(f"\nCopying extension {ext.name}")

            relative_site_packages = (
                sysconfig.get_path("purelib")
                .replace(sysconfig.get_path("data"), "")
                .lstrip(os.path.sep)
            )
            src = os.path.join("torch", relative_site_packages, filename)
            if not os.path.exists(src):
                report(f"{src} does not exist")
                del self.extensions[i]
            else:
                dst = os.path.join(os.path.realpath(self.build_lib), filename)
                report(f"Copying {ext.name} from {src} to {dst}")
                dst_dir = os.path.dirname(dst)
                if not os.path.exists(dst_dir):
                    os.makedirs(dst_dir)
                self.copy_file(src, dst)
                i += 1

        # Copy functorch extension
        for i, ext in enumerate(self.extensions):
            if ext.name != "functorch._C":
                continue
            fullname = self.get_ext_fullname(ext.name)
            filename = self.get_ext_filename(fullname)
            fileext = os.path.splitext(filename)[1]
            src = os.path.join(os.path.dirname(filename), "functorch" + fileext)
            dst = os.path.join(os.path.realpath(self.build_lib), filename)
            if os.path.exists(src):
                report(f"Copying {ext.name} from {src} to {dst}")
                dst_dir = os.path.dirname(dst)
                if not os.path.exists(dst_dir):
                    os.makedirs(dst_dir)
                self.copy_file(src, dst)

        setuptools.command.build_ext.build_ext.build_extensions(self)

running build_ext
-- Building with NumPy bindings
-- Detected cuDNN at , 
-- Detected CUDA at /usr/local/cuda-12.1
-- Not using XPU
-- Using MKLDNN
-- Not using Compute Library for the Arm architecture with MKLDNN
-- Not using CBLAS in MKLDNN
-- Building NCCL library
-- Building with distributed package: 
  -- USE_TENSORPIPE=True
  -- USE_GLOO=True
  -- USE_MPI=False
-- Building Executorch
-- Using ITT
Copying functorch._C from functorch/functorch.so to /nas/lili/codes/pt/torchsrc/pytorch/build/lib.linux-x86_64-cpython-39/functorch/_C.cpython-39-x86_64-linux-gnu.so
Creating /home/ubuntu/miniconda3/envs/torchbuild/lib/python3.9/site-packages/torch.egg-link (link to .)
torch 2.4.0a0+git8168338 is already the active version in easy-install.pth
Installing convert-caffe2-to-onnx script to /home/ubuntu/miniconda3/envs/torchbuild/bin
Installing convert-onnx-to-caffe2 script to /home/ubuntu/miniconda3/envs/torchbuild/bin
Installing torchrun script to /home/ubuntu/miniconda3/envs/torchbuild/bin

Installed /nas/lili/codes/pt/torchsrc/pytorch
Processing dependencies for torch==2.4.0a0+git8168338
Searching for fsspec==2024.3.1
Best match: fsspec 2024.3.1
Adding fsspec 2024.3.1 to easy-install.pth file

Using /home/ubuntu/miniconda3/envs/torchbuild/lib/python3.9/site-packages
Searching for Jinja2==3.1.3
Best match: Jinja2 3.1.3
Adding Jinja2 3.1.3 to easy-install.pth file

Using /home/ubuntu/miniconda3/envs/torchbuild/lib/python3.9/site-packages
Searching for networkx==3.2.1
Best match: networkx 3.2.1
Adding networkx 3.2.1 to easy-install.pth file

Using /home/ubuntu/miniconda3/envs/torchbuild/lib/python3.9/site-packages
Searching for sympy==1.12
Best match: sympy 1.12
Adding sympy 1.12 to easy-install.pth file
Installing isympy script to /home/ubuntu/miniconda3/envs/torchbuild/bin

Using /home/ubuntu/miniconda3/envs/torchbuild/lib/python3.9/site-packages
Searching for typing-extensions==4.9.0
Best match: typing-extensions 4.9.0
Adding typing-extensions 4.9.0 to easy-install.pth file

Using /home/ubuntu/.local/lib/python3.9/site-packages
Searching for filelock==3.13.1
Best match: filelock 3.13.1
Adding filelock 3.13.1 to easy-install.pth file

Using /home/ubuntu/miniconda3/envs/torchbuild/lib/python3.9/site-packages
Searching for MarkupSafe==2.1.5
Best match: MarkupSafe 2.1.5
Adding MarkupSafe 2.1.5 to easy-install.pth file

Using /home/ubuntu/miniconda3/envs/torchbuild/lib/python3.9/site-packages
Searching for mpmath==1.3.0
Best match: mpmath 1.3.0
Adding mpmath 1.3.0 to easy-install.pth file

Using /home/ubuntu/miniconda3/envs/torchbuild/lib/python3.9/site-packages
Finished processing dependencies for torch==2.4.0a0+git8168338

{
    "version": "0.2.0",
    "configurations": [
        {
            "name": "Python Debugger: Remote Attach",
            "type": "debugpy",
            "request": "attach",
            "connect": {
                "host": "remote server ip address",
                "port": 5678
            },
            "justMyCode": false
        }
    ]

{
    "version": "0.2.0",
    "configurations": [
        {
            "name": "Python Debugger: Remote Attach",
            "type": "debugpy",
            "request": "attach",
            "connect": {
                "host": "server ip",
                "port": 5678
            },
            "justMyCode": false
        },
        {
            "name": "Torch Debugger",
            "type": "cppdbg",
            "request": "attach",
            "program": "/home/ubuntu/miniconda3/envs/torchbuild/bin/python",
            "processId": "${command:pickProcess}",
            "MIMode": "gdb",
            "setupCommands": [
                {
                    "description": "Enable pretty-printing for gdb",
                    "text": "-enable-pretty-printing",
                    "ignoreFailures": true
                }
            ]
        
        }
    ]
}