#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 { const char * (*GGML_CALL get_name) (ggml_backend_buffer_type_t buft); ggml_backend_buffer_t (*GGML_CALL alloc_buffer) (ggml_backend_buffer_type_t buft, size_t size); size_t (*GGML_CALL get_alignment) (ggml_backend_buffer_type_t buft); // tensor alignment size_t (*GGML_CALL get_max_size) (ggml_backend_buffer_type_t buft); // allocation max size size_t (*GGML_CALL get_alloc_size) (ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor); // data size needed to allocate the tensor, including padding bool (*GGML_CALL 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 (*GGML_CALL 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 { const char * (*GGML_CALL get_name) (ggml_backend_buffer_t buffer); void (*GGML_CALL free_buffer)(ggml_backend_buffer_t buffer); void * (*GGML_CALL get_base) (ggml_backend_buffer_t buffer); void (*GGML_CALL init_tensor)(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor); void (*GGML_CALL set_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size); void (*GGML_CALL get_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size); bool (*GGML_CALL cpy_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst); // dst is in the buffer, src may be in any buffer void (*GGML_CALL clear) (ggml_backend_buffer_t buffer, uint8_t value); void (*GGML_CALL reset) (ggml_backend_buffer_t buffer); // reset any internal state due to tensor initialization, such as tensor extras }; 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; enum ggml_backend_buffer_usage usage; }; GGML_CALL 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); // do not use directly, use ggml_backend_tensor_copy instead bool ggml_backend_buffer_copy_tensor(const struct ggml_tensor * src, struct ggml_tensor * dst); // buffer that contains a collection of buffers GGML_CALL ggml_backend_buffer_t ggml_backend_multi_buffer_alloc_buffer(ggml_backend_buffer_t * buffers, size_t n_buffers); GGML_CALL bool ggml_backend_buffer_is_multi_buffer(ggml_backend_buffer_t buffer); GGML_CALL void ggml_backend_multi_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage); // // Backend // typedef void * ggml_backend_context_t; struct ggml_backend_i { const char * (*GGML_CALL get_name)(ggml_backend_t backend); void (*GGML_CALL free)(ggml_backend_t backend); // buffer allocation ggml_backend_buffer_type_t (*GGML_CALL get_default_buffer_type)(ggml_backend_t backend); // (optional) asynchronous tensor data access void (*GGML_CALL set_tensor_async)(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size); void (*GGML_CALL get_tensor_async)(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size); bool (*GGML_CALL cpy_tensor_async)(ggml_backend_t backend_src, ggml_backend_t backend_dst, const struct ggml_tensor * src, struct ggml_tensor * dst); // (optional) complete all pending operations void (*GGML_CALL synchronize)(ggml_backend_t backend); // compute graph with a plan (not used currently) ggml_backend_graph_plan_t (*GGML_CALL graph_plan_create) (ggml_backend_t backend, const struct ggml_cgraph * cgraph); void (*GGML_CALL graph_plan_free) (ggml_backend_t backend, ggml_backend_graph_plan_t plan); // compute graph with a plan enum ggml_status (*GGML_CALL graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan); // compute graph without a plan (async) enum ggml_status (*GGML_CALL graph_compute) (ggml_backend_t backend, struct ggml_cgraph * cgraph); // check if the backend supports an operation bool (*GGML_CALL supports_op)(ggml_backend_t backend, const struct ggml_tensor * op); // check if the backend wants to run an operation, even if the weights are allocated in a CPU buffer // these should be expensive operations with large batch sizes that may benefit from running on this backend // even if the weight has to be copied from the CPU temporarily bool (*GGML_CALL offload_op)(ggml_backend_t backend, const struct ggml_tensor * op); // (optional) event synchronization ggml_backend_event_t (*GGML_CALL event_new) (ggml_backend_t backend); void (*GGML_CALL event_free) (ggml_backend_event_t event); void (*GGML_CALL event_record) (ggml_backend_event_t event); void (*GGML_CALL event_wait) (ggml_backend_t backend, ggml_backend_event_t event); void (*GGML_CALL event_synchronize) (ggml_backend_event_t event); }; struct ggml_backend { ggml_guid_t guid; struct ggml_backend_i iface; ggml_backend_context_t context; }; struct ggml_backend_event { ggml_backend_t backend; void * context; }; // // Backend registry // typedef ggml_backend_t (*GGML_CALL ggml_backend_init_fn)(const char * params, void * user_data); GGML_CALL 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