Python cpp_extension.CUDA_HOME屬性代碼示例

本文整理匯總了Python中torch.utils.cpp_extension.CUDA_HOME屬性的典型用法代碼示例。如果您正苦於以下問題：Python cpp_extension.CUDA_HOME屬性的具體用法？Python cpp_extension.CUDA_HOME怎麽用？Python cpp_extension.CUDA_HOME使用的例子？那麽, 這裏精選的屬性代碼示例或許可以為您提供幫助。您也可以進一步了解該屬性所在類torch.utils.cpp_extension的用法示例。

在下文中一共展示了cpp_extension.CUDA_HOME屬性的11個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: _load_C_extensions

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def _load_C_extensions():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    this_dir = os.path.dirname(this_dir)
    this_dir = os.path.join(this_dir, "csrc")

    main_file = glob.glob(os.path.join(this_dir, "*.cpp"))
    source_cpu = glob.glob(os.path.join(this_dir, "cpu", "*.cpp"))
    source_cuda = glob.glob(os.path.join(this_dir, "cuda", "*.cu"))

    source = main_file + source_cpu

    extra_cflags = []
    if torch.cuda.is_available() and CUDA_HOME is not None:
        source.extend(source_cuda)
        extra_cflags = ["-DWITH_CUDA"]
    source = [os.path.join(this_dir, s) for s in source]
    extra_include_paths = [this_dir]
    return load_ext(
        "torchvision",
        source,
        extra_cflags=extra_cflags,
        extra_include_paths=extra_include_paths,
    )

開發者ID:Res2Net，項目名稱:Res2Net-maskrcnn，代碼行數:25，代碼來源:_utils.py

示例2: _load_C_extensions

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def _load_C_extensions():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    this_dir = os.path.join(this_dir, "csrc")

    main_file = glob.glob(os.path.join(this_dir, "*.cpp"))
    sources_cpu = glob.glob(os.path.join(this_dir, "cpu", "*.cpp"))
    sources_cuda = glob.glob(os.path.join(this_dir, "cuda", "*.cu"))

    sources = main_file + sources_cpu

    extra_cflags = []
    extra_cuda_cflags = []
    if torch.cuda.is_available() and CUDA_HOME is not None:
        sources.extend(sources_cuda)
        extra_cflags = ["-O3", "-DWITH_CUDA"]
        extra_cuda_cflags = ["--expt-extended-lambda"]
    sources = [os.path.join(this_dir, s) for s in sources]
    extra_include_paths = [this_dir]
    return load(
        name="ext_lib",
        sources=sources,
        extra_cflags=extra_cflags,
        extra_include_paths=extra_include_paths,
        extra_cuda_cflags=extra_cuda_cflags,
    )

開發者ID:tamakoji，項目名稱:pytorch-syncbn，代碼行數:27，代碼來源:_csrc.py

示例3: detect_compute_compatibility

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def detect_compute_compatibility(CUDA_HOME, so_file):
    try:
        cuobjdump = os.path.join(CUDA_HOME, "bin", "cuobjdump")
        if os.path.isfile(cuobjdump):
            output = subprocess.check_output(
                "'{}' --list-elf '{}'".format(cuobjdump, so_file), shell=True
            )
            output = output.decode("utf-8").strip().split("\n")
            sm = []
            for line in output:
                line = re.findall(r"\.sm_[0-9]*\.", line)[0]
                sm.append(line.strip("."))
            sm = sorted(set(sm))
            return ", ".join(sm)
        else:
            return so_file + "; cannot find cuobjdump"
    except Exception:
        # unhandled failure
        return so_file

開發者ID:facebookresearch，項目名稱:detectron2，代碼行數:21，代碼來源:collect_env.py

示例4: get_extensions

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def get_extensions():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    extensions_dir = os.path.join(this_dir, "src")

    main_file = glob.glob(os.path.join(extensions_dir, "*.cpp"))
    source_cpu = glob.glob(os.path.join(extensions_dir, "cpu", "*.cpp"))
    source_cuda = glob.glob(os.path.join(extensions_dir, "cuda", "*.cu"))

    sources = main_file + source_cpu
    extension = CppExtension

    extra_compile_args = {"cxx": []}
    define_macros = []

    if torch.cuda.is_available() and CUDA_HOME is not None:
        extension = CUDAExtension
        sources += source_cuda
        define_macros += [("WITH_CUDA", None)]
        extra_compile_args["nvcc"] = [
            "-DCUDA_HAS_FP16=1",
            "-D__CUDA_NO_HALF_OPERATORS__",
            "-D__CUDA_NO_HALF_CONVERSIONS__",
            "-D__CUDA_NO_HALF2_OPERATORS__",
        ]

    sources = [os.path.join(extensions_dir, s) for s in sources]

    include_dirs = [extensions_dir]

    ext_modules = [
        extension(
            "support._C",
            sources,
            include_dirs=include_dirs,
            define_macros=define_macros,
            extra_compile_args=extra_compile_args,
        )
    ]

    return ext_modules

開發者ID:potterhsu，項目名稱:easy-faster-rcnn.pytorch，代碼行數:42，代碼來源:setup.py

示例5: get_extensions

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def get_extensions():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    extensions_dir = os.path.join(this_dir, "maskrcnn_benchmark", "csrc")

    main_file = glob.glob(os.path.join(extensions_dir, "*.cpp"))
    source_cpu = glob.glob(os.path.join(extensions_dir, "cpu", "*.cpp"))
    source_cuda = glob.glob(os.path.join(extensions_dir, "cuda", "*.cu"))

    sources = main_file + source_cpu
    extension = CppExtension

    extra_compile_args = {"cxx": []}
    define_macros = []

    if torch.cuda.is_available() and CUDA_HOME is not None:
        extension = CUDAExtension
        sources += source_cuda
        define_macros += [("WITH_CUDA", None)]
        extra_compile_args["nvcc"] = [
            "-DCUDA_HAS_FP16=1",
            "-D__CUDA_NO_HALF_OPERATORS__",
            "-D__CUDA_NO_HALF_CONVERSIONS__",
            "-D__CUDA_NO_HALF2_OPERATORS__",
        ]

    sources = [os.path.join(extensions_dir, s) for s in sources]

    include_dirs = [extensions_dir]

    ext_modules = [
        extension(
            "maskrcnn_benchmark._C",
            sources,
            include_dirs=include_dirs,
            define_macros=define_macros,
            extra_compile_args=extra_compile_args,
        )
    ]

    return ext_modules

開發者ID:Res2Net，項目名稱:Res2Net-maskrcnn，代碼行數:42，代碼來源:setup.py

示例6: get_extensions

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def get_extensions():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    extensions_dir = os.path.join(this_dir, "csrc")

    main_file = glob.glob(os.path.join(extensions_dir, "*.cpp"))
    source_cpu = glob.glob(os.path.join(extensions_dir, "cpu", "*.cpp"))
    source_cuda = glob.glob(os.path.join(extensions_dir, "cuda", "*.cu"))

    sources = main_file + source_cpu
    extension = CppExtension

    extra_compile_args = {"cxx": []}
    define_macros = []

    if (torch.cuda.is_available() and CUDA_HOME is not None) or os.getenv("FORCE_CUDA", "0") == "1":
        extension = CUDAExtension
        sources += source_cuda
        define_macros += [("WITH_CUDA", None)]
        extra_compile_args["nvcc"] = [
            "-DCUDA_HAS_FP16=1",
            "-D__CUDA_NO_HALF_OPERATORS__",
            "-D__CUDA_NO_HALF_CONVERSIONS__",
            "-D__CUDA_NO_HALF2_OPERATORS__",
        ]

    sources = [os.path.join(extensions_dir, s) for s in sources]

    include_dirs = [extensions_dir]

    ext_modules = [
        extension(
            "_C",
            sources,
            include_dirs=include_dirs,
            define_macros=define_macros,
            extra_compile_args=extra_compile_args,
        )
    ]

    return ext_modules

開發者ID:soeaver，項目名稱:Parsing-R-CNN，代碼行數:42，代碼來源:setup_rcnn.py

示例7: get_extensions

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def get_extensions():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    extensions_dir = os.path.join(this_dir, "src")

    main_file = glob.glob(os.path.join(extensions_dir, "*.cpp"))
    source_cpu = glob.glob(os.path.join(extensions_dir, "cpu", "*.cpp"))
    source_cuda = glob.glob(os.path.join(extensions_dir, "cuda", "*.cu"))

    sources = main_file + source_cpu
    extension = CppExtension
    extra_compile_args = {"cxx": []}
    define_macros = []

    if torch.cuda.is_available() and CUDA_HOME is not None:
        extension = CUDAExtension
        sources += source_cuda
        define_macros += [("WITH_CUDA", None)]
        extra_compile_args["nvcc"] = [
            "-DCUDA_HAS_FP16=1",
            "-D__CUDA_NO_HALF_OPERATORS__",
            "-D__CUDA_NO_HALF_CONVERSIONS__",
            "-D__CUDA_NO_HALF2_OPERATORS__",
        ]
    else:
        raise NotImplementedError('Cuda is not availabel')

    sources = [os.path.join(extensions_dir, s) for s in sources]
    include_dirs = [extensions_dir]
    ext_modules = [
        extension(
            "DCN",
            sources,
            include_dirs=include_dirs,
            define_macros=define_macros,
            extra_compile_args=extra_compile_args,
        )
    ]
    return ext_modules

開發者ID:ruinmessi，項目名稱:ASFF，代碼行數:40，代碼來源:setup.py

示例8: get_extensions

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def get_extensions():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    extensions_dir = os.path.join(this_dir, "src")

    main_file = glob.glob(os.path.join(extensions_dir, "*.cpp"))
    source_cpu = glob.glob(os.path.join(extensions_dir, "cpu", "*.cpp"))
    source_cuda = glob.glob(os.path.join(extensions_dir, "cuda", "*.cu"))

    sources = main_file + source_cpu
    extension = CppExtension
    extra_compile_args = {"cxx": []}
    define_macros = []

    if torch.cuda.is_available() and CUDA_HOME is not None:
        extension = CUDAExtension
        sources += source_cuda
        define_macros += [("WITH_CUDA", None)]
        extra_compile_args["nvcc"] = [
            "-DCUDA_HAS_FP16=1",
            "-D__CUDA_NO_HALF_OPERATORS__",
            "-D__CUDA_NO_HALF_CONVERSIONS__",
            "-D__CUDA_NO_HALF2_OPERATORS__",
        ]
    else:
        raise NotImplementedError('Cuda is not availabel')

    sources = [os.path.join(extensions_dir, s) for s in sources]
    include_dirs = [extensions_dir]
    ext_modules = [
        extension(
            "_ext",
            sources,
            include_dirs=include_dirs,
            define_macros=define_macros,
            extra_compile_args=extra_compile_args,
        )
    ]
    return ext_modules

開發者ID:tensorboy，項目名稱:centerpose，代碼行數:40，代碼來源:setup.py

示例9: get_extensions

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def get_extensions():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    extensions_dir = os.path.join(this_dir, "src")

    main_file = glob.glob(os.path.join(extensions_dir, "*.cpp"))
    source_cpu = glob.glob(os.path.join(extensions_dir, "cpu", "*.cpp"))
    source_cuda = glob.glob(os.path.join(extensions_dir, "cuda", "*.cu"))

    sources = main_file + source_cpu
    extension = CppExtension
    extra_compile_args = {"cxx": []}
    define_macros = []

    if torch.cuda.is_available() and CUDA_HOME is not None:
        extension = CUDAExtension
        sources += source_cuda
        define_macros += [("WITH_CUDA", None)]
        extra_compile_args["nvcc"] = [
            "-DCUDA_HAS_FP16=1",
            "-D__CUDA_NO_HALF_OPERATORS__",
            "-D__CUDA_NO_HALF_CONVERSIONS__",
            "-D__CUDA_NO_HALF2_OPERATORS__",
        ]
    else:
        raise NotImplementedError('Cuda is not available')

    sources = [os.path.join(extensions_dir, s) for s in sources]
    include_dirs = [extensions_dir]
    ext_modules = [
        extension(
            "_ext",
            sources,
            include_dirs=include_dirs,
            define_macros=define_macros,
            extra_compile_args=extra_compile_args,
        )
    ]
    return ext_modules

開發者ID:dbolya，項目名稱:yolact，代碼行數:40，代碼來源:setup.py

示例10: get_extension

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def get_extension():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    extensions_dir = os.path.join(this_dir, "csrc")

    main_file = glob.glob(os.path.join(extensions_dir, "*.cpp"))
    source_cpu = glob.glob(os.path.join(extensions_dir, "cpu", "*.cpp"))
    source_cuda = glob.glob(os.path.join(extensions_dir, "cuda", "*.cu"))

    sources = main_file + source_cpu
    extension = CppExtension

    define_macros = []

    if (torch.cuda.is_available() and CUDA_HOME is not None) or os.getenv("FORCE_CUDA", "0") == "1":
        extension = CUDAExtension
        sources += source_cuda
        define_macros += [("WITH_CUDA", None)]

    sources = [os.path.join(extensions_dir, s) for s in sources]

    include_dirs = [extensions_dir]

    ext_modules = [
        extension(
            "._C",
            sources,
            include_dirs=include_dirs,
            define_macros=define_macros,
        )
    ]

    return ext_modules

開發者ID:Tramac，項目名稱:awesome-semantic-segmentation-pytorch，代碼行數:34，代碼來源:setup.py

示例11: get_extensions

# 需要導入模塊: from torch.utils import cpp_extension [as 別名]
# 或者: from torch.utils.cpp_extension import CUDA_HOME [as 別名]
def get_extensions():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    extensions_dir = os.path.join(this_dir, "maskrcnn_benchmark", "csrc")

    main_file = glob.glob(os.path.join(extensions_dir, "*.cpp"))
    source_cpu = glob.glob(os.path.join(extensions_dir, "cpu", "*.cpp"))
    source_cuda = glob.glob(os.path.join(extensions_dir, "cuda", "*.cu"))

    sources = main_file + source_cpu
    extension = CppExtension

    extra_compile_args = {"cxx": []}
    define_macros = []

    if (torch.cuda.is_available() and CUDA_HOME is not None) or os.getenv("FORCE_CUDA", "0") == "1":
        extension = CUDAExtension
        sources += source_cuda
        define_macros += [("WITH_CUDA", None)]
        extra_compile_args["nvcc"] = [
            "-DCUDA_HAS_FP16=1",
            "-D__CUDA_NO_HALF_OPERATORS__",
            "-D__CUDA_NO_HALF_CONVERSIONS__",
            "-D__CUDA_NO_HALF2_OPERATORS__",
        ]

    sources = [os.path.join(extensions_dir, s) for s in sources]

    include_dirs = [extensions_dir]

    ext_modules = [
        extension(
            "maskrcnn_benchmark._C",
            sources,
            include_dirs=include_dirs,
            define_macros=define_macros,
            extra_compile_args=extra_compile_args,
        )
    ]

    return ext_modules

開發者ID:megvii-model，項目名稱:DetNAS，代碼行數:42，代碼來源:setup.py

注：本文中的torch.utils.cpp_extension.CUDA_HOME屬性示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。