void softmax_nv_f32(torch::Tensor input, torch::Tensor output, int size, int dimsize, int stride); void attention_nv_f32(torch::Tensor Q, torch::Tensor K, torch::Tensor V, int N, int d, torch::Tensor output); P
(); } PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { // 第一个参数"softmax"表示注册到python模块中的函数名称,可以替换为其他名字,使用方法为:模块.softmax // 第二个参数softmaxLaunch是上面编写的kernel launch 函数,这里需要获得该函数的地址 // 第三个参数"Cuda Core softmax function"是描述性文字,...
创建setup.py文件:在<package_name>文件夹下创建一个名为setup.py的文件,用于描述和配置Python包的元数据和依赖关系。 在ext_modules中,使用Extension类指定C++模块的名称和源代码文件。 创建C++源代码文件:在<package_name>文件夹下创建一个名为<module_source>.cpp的C++源代码文件,用于实现swig/pybind11接口...
AI代码解释 #include<pybind11/pybind11.h>namespace py=pybind11;intadd(int i,int j){returni+j;}PYBIND11_MODULE(example,m){m.doc()="pybind11 示例";// 模块文档字符串m.def("add",&add,"一个简单的加法函数");} 第二步 把功能打包成 python 包 为了方便使用我们最好配置一下 setup.py 把...
A high-throughput and memory-efficient inference and serving engine for LLMs - [Kernel][Misc] Use TORCH_LIBRARY instead of PYBIND11_MODULE for custo… · vllm-project/vllm@5467ac3
I am working on a large library and trying to make it accessible from python. I want to be able to call functions in a derived class (and some setters in its parent class). The derived class is Class C. Class C inherits from Class B (an ...
namespacegbf{namespacemath{classVector3{public:doublex;doubley;doublez;Vector3():x(0.0),y(0.0),z(0.0){}Vector3(double_x,double_y,double_z):x(_x),y(_y),z(_z){}~Vector3(){}// Returns the length (magnitude) of the vector.doubleLength()const;/// Extract the primary (dominant)...
PYBIND11_MODULE()宏函数将会创建一个函数,在由Python发起import语句时该函数将会被调用。模块名字“example”,由宏的第一个参数指定(千万不能出现引号)。第二个参数"m",定义了一个py::module的变量。函数py::module::def()生成绑定代码,将add()函数暴露给Python。
运行 AI代码解释 // NOTE: _T = typing.TypeVar('_T') and Any/Type/Union/Mapping/Optional are defines by the Python typing module.staticPyMethodDef PyMethods[]={{PyGenUtil::PostInitFuncName,PyCFunctionCast(&FMethods::PostInit),METH_NOARGS,"_post_init(self) -> None -- called during Unre...
return self.module.train_step(*inputs[0], **kwargs[0]) File "d:\lw\mmdetection-2.7.0\mmdet\models\detectors\base.py", line 246, in train_step losses = self(**data) File "D:\Applications\WPy64-3850\python-3.8.5.amd64\lib\site-packages\torch\nn\modules\module.py", line 727, in...