__func__); backend = ggml_backend_cuda_init(); // init device 0if (!backend) {fprintf(stderr, "%s: ggml_backend_cuda_init() failed\n", __func__); }#endif// if there aren't GPU Backends fallback to CPU backendif (!backend) { backend = ggml_backend_cpu_init(); ...
#ifdef GGML_USE_CUDA fprintf(stderr, "%s: using CUDA backend\n", __func__); backend = ggml_backend_cuda_init(0); // init device 0 if (!backend) { fprintf(stderr, "%s: ggml_backend_cuda_init() failed\n", __func__); } #endif // if there aren't GPU Backends fallback ...
ggml_cuda_init: failed to initialize MUSA: system has unsupported display driver / musa driver combination warning: no usable GPU found, --gpu-layers option will be ignored warning: one possible reason is that llama.cpp was compiled without GPU support ...
// 1. Initialize backend ggml_backend_t backend = NULL; #ifdef GGML_USE_CUDA fprintf(stderr, "%s: using CUDA backend\n", __func__); backend = ggml_backend_cuda_init(0); // init device 0 if (!backend) { fprintf(stderr, "%s: ggml_backend_cuda_init() failed\n", __func__...
Initialize backend ggml_backend_t backend = NULL; #ifdef GGML_USE_CUDA fprintf(stderr, "%s: using CUDA backend\n", __func__); backend = ggml_backend_cuda_init(0); // init device 0 if (!backend) { fprintf(stderr, "%s: ggml_backend_cuda_init() failed\n", __func__); } ...
Initialize backend ggml_backend_t backend = NULL; #ifdef GGML_USE_CUDA fprintf(stderr, "%s: using CUDA backend\n", __func__); backend = ggml_backend_cuda_init(0); // init device 0 if (!backend) { fprintf(stderr, "%s: ggml_backend_cuda_init() failed\n", __func__); } ...
// 1. Initialize backend ggml_backend_tbackend =NULL; #ifdefGGML_USE_CUDA fprintf(stderr,"%s: using CUDA backend\n", __func__); backend =ggml_backend_cuda_init(0);// init device 0 if(!backend) { fprintf(stderr,"%s: ggml_backend_cuda_init() failed\n", __func__); ...
在ggml 中,“后端”指的是一个可以处理张量操作的接口,比如 CPU、CUDA、Vulkan 等。 后端可以抽象化计算图的执行。当定义后,一个计算图就可以在相关硬件上用对应的后端实现去进行计算。注意,在这个过程中,ggml 会自动为需要的中间结果预留内存,并基于其生命周期优化内存使用。
// 1. Initialize backend ggml_backend_t backend = NULL; #ifdef GGML_USE_CUDA fprintf(stderr, "%s: using CUDA backend\n", __func__); backend = ggml_backend_cuda_init(0); // init device 0 if (!backend) { fprintf(stderr, "%s: ggml_backend_cuda_init() failed\n", __func...
extern void ggml_backend_cuda_reg_devices(void); ggml_backend_cuda_reg_devices(); #endif #ifdef GGML_USE_METAL extern ggml_backend_t ggml_backend_reg_metal_init(const char * params, void * user_data); extern ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void); ...