llama.cpp/ggml-backend-impl.h

#pragma once

// ggml-backend internal header

#include "ggml-backend.h"

#ifdef  __cplusplus
extern "C" {
#endif

    //
    // Backend buffer
    //

    // buffer type
    typedef void * ggml_backend_buffer_type_context_t;

    struct ggml_backend_buffer_type_i {
        ggml_backend_buffer_t (*alloc_buffer)    (ggml_backend_buffer_type_t buft, size_t size);
        size_t                (*get_alignment)   (ggml_backend_buffer_type_t buft); // tensor alignment
        size_t                (*get_alloc_size)  (ggml_backend_buffer_type_t buft, struct ggml_tensor * tensor); // data size needed to allocate the tensor, including padding
        bool                  (*supports_backend)(ggml_backend_buffer_type_t buft, ggml_backend_t backend); // check if the buffer type is usable by the backend
        // check if tensor data is in host memory
        // should be equivalent to supports_backend(buft, ggml_backend_cpu_init())
        bool                  (*is_host)         (ggml_backend_buffer_type_t buft);
    };

    struct ggml_backend_buffer_type {
        struct ggml_backend_buffer_type_i  iface;
        ggml_backend_buffer_type_context_t context;
    };

    // buffer
    typedef void * ggml_backend_buffer_context_t;

    struct ggml_backend_buffer_i {
        void   (*free_buffer)    (ggml_backend_buffer_t buffer);
        //void     (*reset)      (ggml_backend_buffer_t buffer); // reset any internal state due to tensor initialization, such as tensor extras
        void * (*get_base)       (ggml_backend_buffer_t buffer);
        void   (*init_tensor)    (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
        void   (*set_tensor)     (ggml_backend_buffer_t buffer,       struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
        void   (*get_tensor)     (ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor,       void * data, size_t offset, size_t size);
        // (optional) copy tensor between different buffer-type, allow for single-copy tranfers
        void   (*cpy_tensor_from)(ggml_backend_buffer_t buffer, struct ggml_tensor * src, struct ggml_tensor * dst);
        void   (*cpy_tensor_to)  (ggml_backend_buffer_t buffer, struct ggml_tensor * src, struct ggml_tensor * dst);
        void   (*clear)          (ggml_backend_buffer_t buffer, uint8_t value);
    };

    struct ggml_backend_buffer {
        struct ggml_backend_buffer_i  iface;
        ggml_backend_buffer_type_t    buft;
        ggml_backend_buffer_context_t context;
        size_t size;
    };

    ggml_backend_buffer_t ggml_backend_buffer_init(
                   ggml_backend_buffer_type_t      buft,
            struct ggml_backend_buffer_i           iface,
                   ggml_backend_buffer_context_t   context,
                   size_t                          size);


    //
    // Backend
    //

    typedef void * ggml_backend_context_t;

    struct ggml_backend_i {
        const char * (*get_name)(ggml_backend_t backend);

        void (*free)(ggml_backend_t backend);

        // buffer allocation
        ggml_backend_buffer_type_t (*get_default_buffer_type)(ggml_backend_t backend);

        // (optional) asynchroneous tensor data access
        void (*set_tensor_async)(ggml_backend_t backend,       struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
        void (*get_tensor_async)(ggml_backend_t backend, const struct ggml_tensor * tensor,       void * data, size_t offset, size_t size);

        // (optional) asynchroneous tensor copy
        void (*cpy_tensor_from_async)(ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst);
        void (*cpy_tensor_to_async)  (ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst);

        void (*synchronize)(ggml_backend_t backend);

        // compute graph with a plan
        ggml_backend_graph_plan_t (*graph_plan_create) (ggml_backend_t backend, struct ggml_cgraph * cgraph);
        void                      (*graph_plan_free)   (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
        void                      (*graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);

        // compute graph without a plan
        bool (*graph_compute)(ggml_backend_t backend, struct ggml_cgraph * cgraph);

        // check if the backend supports an operation
        bool (*supports_op)(ggml_backend_t backend, const struct ggml_tensor * op);
    };

    struct ggml_backend {
        struct ggml_backend_i iface;

        ggml_backend_context_t context;
    };


    //
    // Backend registry
    //

    typedef ggml_backend_t (*ggml_backend_init_fn)(const char * params, void * user_data);

    void ggml_backend_register(const char * name, ggml_backend_init_fn init_fn, ggml_backend_buffer_type_t default_buffer_type, void * user_data);

#ifdef  __cplusplus
}
#endif