ggml-backend : add device and backend reg interfaces (#9707)
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
This commit is contained in:
Diego Devesa
GitHub
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c83ad6d01e
28 changed files with 1809 additions and 1303 deletions
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@ -9,145 +9,229 @@ extern "C" {
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#endif
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//
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// Backend buffer
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// Backend buffer type
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//
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// buffer type
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typedef void * ggml_backend_buffer_type_context_t;
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struct ggml_backend_buffer_type_i {
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const char * (*GGML_CALL get_name) (ggml_backend_buffer_type_t buft);
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const char * (*get_name) (ggml_backend_buffer_type_t buft);
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// allocate a buffer of this type
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ggml_backend_buffer_t (*GGML_CALL alloc_buffer) (ggml_backend_buffer_type_t buft, size_t size);
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ggml_backend_buffer_t (*alloc_buffer) (ggml_backend_buffer_type_t buft, size_t size);
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// tensor alignment
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size_t (*GGML_CALL get_alignment) (ggml_backend_buffer_type_t buft);
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// max buffer size that can be allocated
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size_t (*GGML_CALL get_max_size) (ggml_backend_buffer_type_t buft);
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// data size needed to allocate the tensor, including padding
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size_t (*GGML_CALL get_alloc_size) (ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor);
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// check if tensor data is in host memory
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bool (*GGML_CALL is_host) (ggml_backend_buffer_type_t buft);
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size_t (*get_alignment) (ggml_backend_buffer_type_t buft);
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// (optional) max buffer size that can be allocated (defaults to SIZE_MAX)
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size_t (*get_max_size) (ggml_backend_buffer_type_t buft);
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// (optional) data size needed to allocate the tensor, including padding (defaults to ggml_nbytes)
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size_t (*get_alloc_size)(ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor);
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// (optional) check if tensor data is in host memory (defaults to false)
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bool (*is_host) (ggml_backend_buffer_type_t buft);
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};
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struct ggml_backend_buffer_type {
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struct ggml_backend_buffer_type_i iface;
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ggml_backend_buffer_type_context_t context;
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ggml_backend_dev_t device;
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void * context;
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};
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// buffer
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typedef void * ggml_backend_buffer_context_t;
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//
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// Backend buffer
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//
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struct ggml_backend_buffer_i {
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const char * (*GGML_CALL get_name) (ggml_backend_buffer_t buffer);
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void (*GGML_CALL free_buffer) (ggml_backend_buffer_t buffer);
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void * (*GGML_CALL get_base) (ggml_backend_buffer_t buffer);
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void (*GGML_CALL init_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
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void (*GGML_CALL memset_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size);
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void (*GGML_CALL set_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
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void (*GGML_CALL get_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
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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
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void (*GGML_CALL clear) (ggml_backend_buffer_t buffer, uint8_t value);
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void (*GGML_CALL reset) (ggml_backend_buffer_t buffer); // reset any internal state due to tensor initialization, such as tensor extras
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const char * (*get_name) (ggml_backend_buffer_t buffer);
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// (optional) free the buffer
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void (*free_buffer) (ggml_backend_buffer_t buffer);
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// base address of the buffer
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void * (*get_base) (ggml_backend_buffer_t buffer);
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// (optional) initialize a tensor in the buffer (eg. add tensor extras)
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void (*init_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
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// tensor data access
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void (*memset_tensor)(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size);
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void (*set_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
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void (*get_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
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// (optional) tensor copy: dst is in the buffer, src may be in any buffer, including buffers from a different backend (return false if not supported)
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bool (*cpy_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst);
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// clear the entire buffer
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void (*clear) (ggml_backend_buffer_t buffer, uint8_t value);
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// (optional) reset any internal state due to tensor initialization, such as tensor extras
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void (*reset) (ggml_backend_buffer_t buffer);
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};
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struct ggml_backend_buffer {
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struct ggml_backend_buffer_i iface;
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ggml_backend_buffer_type_t buft;
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ggml_backend_buffer_context_t context;
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void * context;
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size_t size;
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enum ggml_backend_buffer_usage usage;
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};
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GGML_CALL ggml_backend_buffer_t ggml_backend_buffer_init(
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ggml_backend_buffer_type_t buft,
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struct ggml_backend_buffer_i iface,
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ggml_backend_buffer_context_t context,
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size_t size);
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ggml_backend_buffer_t ggml_backend_buffer_init(
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ggml_backend_buffer_type_t buft,
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struct ggml_backend_buffer_i iface,
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void * context,
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size_t size);
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// do not use directly, use ggml_backend_tensor_copy instead
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bool ggml_backend_buffer_copy_tensor(const struct ggml_tensor * src, struct ggml_tensor * dst);
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// multi-buffer
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// buffer that contains a collection of buffers
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GGML_CALL ggml_backend_buffer_t ggml_backend_multi_buffer_alloc_buffer(ggml_backend_buffer_t * buffers, size_t n_buffers);
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GGML_CALL bool ggml_backend_buffer_is_multi_buffer(ggml_backend_buffer_t buffer);
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GGML_CALL void ggml_backend_multi_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage);
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ggml_backend_buffer_t ggml_backend_multi_buffer_alloc_buffer(ggml_backend_buffer_t * buffers, size_t n_buffers);
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bool ggml_backend_buffer_is_multi_buffer(ggml_backend_buffer_t buffer);
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void ggml_backend_multi_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage);
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//
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// Backend
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// Backend (stream)
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//
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typedef void * ggml_backend_context_t;
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struct ggml_backend_i {
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const char * (*GGML_CALL get_name)(ggml_backend_t backend);
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const char * (*get_name)(ggml_backend_t backend);
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void (*GGML_CALL free)(ggml_backend_t backend);
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void (*free)(ggml_backend_t backend);
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// buffer allocation
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ggml_backend_buffer_type_t (*GGML_CALL get_default_buffer_type)(ggml_backend_t backend);
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ggml_backend_buffer_type_t (*get_default_buffer_type)(ggml_backend_t backend);
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// (optional) asynchronous tensor data access
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void (*GGML_CALL set_tensor_async)(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
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void (*GGML_CALL get_tensor_async)(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
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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);
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void (*set_tensor_async)(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
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void (*get_tensor_async)(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
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bool (*cpy_tensor_async)(ggml_backend_t backend_src, ggml_backend_t backend_dst, const struct ggml_tensor * src, struct ggml_tensor * dst);
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// (optional) complete all pending operations
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void (*GGML_CALL synchronize)(ggml_backend_t backend);
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void (*synchronize)(ggml_backend_t backend);
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// compute graph with a plan (not used currently)
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// create a new plan for a graph
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ggml_backend_graph_plan_t (*GGML_CALL graph_plan_create) (ggml_backend_t backend, const struct ggml_cgraph * cgraph);
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void (*GGML_CALL graph_plan_free) (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
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// (optional) compute graph with a plan (not used currently)
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ggml_backend_graph_plan_t (*graph_plan_create) (ggml_backend_t backend, const struct ggml_cgraph * cgraph);
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void (*graph_plan_free) (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
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// update the plan with a new graph - this should be faster than creating a new plan when the graph has the same topology
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void (*GGML_CALL graph_plan_update) (ggml_backend_t backend, ggml_backend_graph_plan_t plan, const struct ggml_cgraph * cgraph);
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void (*graph_plan_update) (ggml_backend_t backend, ggml_backend_graph_plan_t plan, const struct ggml_cgraph * cgraph);
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// compute the graph with the plan
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enum ggml_status (*GGML_CALL graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
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enum ggml_status (*graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
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// compute graph without a plan (async)
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enum ggml_status (*GGML_CALL graph_compute) (ggml_backend_t backend, struct ggml_cgraph * cgraph);
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// compute graph (always async if supported by the backend)
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enum ggml_status (*graph_compute) (ggml_backend_t backend, struct ggml_cgraph * cgraph);
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// IMPORTANT: these functions have been moved to the device interface and will be removed from the backend interface
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// new backends should implement the device interface instead
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// These functions are being moved to the device interface
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// check if the backend can compute an operation
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bool (*GGML_CALL supports_op)(ggml_backend_t backend, const struct ggml_tensor * op);
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bool (*supports_op) (ggml_backend_t backend, const struct ggml_tensor * op);
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// check if the backend can use tensors allocated in a buffer type
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bool (*GGML_CALL supports_buft)(ggml_backend_t backend, ggml_backend_buffer_type_t buft);
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bool (*supports_buft)(ggml_backend_t backend, ggml_backend_buffer_type_t buft);
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// check if the backend wants to run an operation, even if the weights are allocated in a CPU buffer
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// these should be expensive operations with large batch sizes that may benefit from running on this backend
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// even if the weight has to be copied from the CPU temporarily
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bool (*GGML_CALL offload_op)(ggml_backend_t backend, const struct ggml_tensor * op);
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bool (*offload_op) (ggml_backend_t backend, const struct ggml_tensor * op);
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// (optional) event synchronization
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// create a new event that can record events on this backend instance
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ggml_backend_event_t (*GGML_CALL event_new) (ggml_backend_t backend);
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void (*GGML_CALL event_free) (ggml_backend_event_t event);
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// record an event on the backend instance that created it
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void (*GGML_CALL event_record) (ggml_backend_event_t event);
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// wait for an event on on a different backend instance
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void (*GGML_CALL event_wait) (ggml_backend_t backend, ggml_backend_event_t event);
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// block until an event is recorded
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void (*GGML_CALL event_synchronize) (ggml_backend_event_t event);
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// record an event on this stream
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void (*event_record)(ggml_backend_t backend, ggml_backend_event_t event);
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// wait for an event on on a different stream
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void (*event_wait) (ggml_backend_t backend, ggml_backend_event_t event);
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};
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struct ggml_backend {
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ggml_guid_t guid;
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struct ggml_backend_i iface;
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ggml_backend_context_t context;
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ggml_backend_dev_t device;
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void * context;
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};
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struct ggml_backend_event {
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ggml_backend_t backend;
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struct ggml_backend_device * device;
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void * context;
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};
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//
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// Backend registry
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// Backend device
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//
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typedef ggml_backend_t (*GGML_CALL ggml_backend_init_fn)(const char * params, void * user_data);
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// Note: if additional properties are needed, we should add a struct with all of them
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// the current functions to obtain the properties can remain, since they are more convenient for often used properties
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struct ggml_backend_device_i {
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// device name: short identifier for this device, such as "CPU" or "CUDA0"
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const char * (*get_name)(ggml_backend_dev_t dev);
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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);
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// device description: short informative description of the device, could be the model name
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const char * (*get_description)(ggml_backend_dev_t dev);
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// device memory in bytes
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void (*get_memory)(ggml_backend_dev_t dev, size_t * free, size_t * total);
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// device type
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enum ggml_backend_dev_type (*get_type)(ggml_backend_dev_t dev);
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// device properties
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void (*get_props)(ggml_backend_dev_t dev, struct ggml_backend_dev_props * props);
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// backend (stream) initialization
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ggml_backend_t (*init_backend)(ggml_backend_dev_t dev, const char * params);
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// preferred buffer type
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ggml_backend_buffer_type_t (*get_buffer_type)(ggml_backend_dev_t dev);
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// (optional) host buffer type (in system memory, typically this is a pinned memory buffer for faster transfers between host and device)
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ggml_backend_buffer_type_t (*get_host_buffer_type)(ggml_backend_dev_t dev);
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// (optional) buffer from pointer: create a buffer from a host pointer (useful for memory mapped models and importing data from other libraries)
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ggml_backend_buffer_t (*buffer_from_host_ptr)(ggml_backend_dev_t dev, void * ptr, size_t size, size_t max_tensor_size);
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// check if the backend can compute an operation
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bool (*supports_op)(ggml_backend_dev_t dev, const struct ggml_tensor * op);
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// check if the backend can use tensors allocated in a buffer type
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bool (*supports_buft)(ggml_backend_dev_t dev, ggml_backend_buffer_type_t buft);
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// check if the backend wants to run an operation, even if the weights are allocated in a CPU buffer
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// these should be expensive operations with large batch sizes that may benefit from running on this backend
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// even if the weight has to be copied from the CPU temporarily
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bool (*offload_op)(ggml_backend_dev_t dev, const struct ggml_tensor * op);
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// (optional) event synchronization
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ggml_backend_event_t (*event_new) (ggml_backend_dev_t dev);
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void (*event_free) (ggml_backend_dev_t dev, ggml_backend_event_t event);
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void (*event_synchronize) (ggml_backend_dev_t dev, ggml_backend_event_t event);
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};
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struct ggml_backend_device {
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struct ggml_backend_device_i iface;
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ggml_backend_reg_t reg;
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void * context;
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};
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//
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// Backend (reg)
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//
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struct ggml_backend_reg_i {
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const char * (*get_name)(ggml_backend_reg_t reg);
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// enumerate available devices
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size_t (*get_device_count)(ggml_backend_reg_t reg);
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ggml_backend_dev_t (*get_device)(ggml_backend_reg_t reg, size_t index);
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// (optional) get a pointer to a function in the backend
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// backends can add custom functions that are not part of the standard ggml-backend interface
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void * (*get_proc_address)(ggml_backend_reg_t reg, const char * name);
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// (optional) set the log callback for the backend
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void (*set_log_callback)(ggml_backend_reg_t reg, ggml_log_callback log_callback, void * user_data);
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};
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struct ggml_backend_reg {
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// int api_version; // TODO: for dynamic loading
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struct ggml_backend_reg_i iface;
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void * context;
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};
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// Internal backend registry API
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void ggml_backend_register(ggml_backend_reg_t reg);
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void ggml_backend_device_register(ggml_backend_dev_t device);
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// TODO: backends can be loaded as a dynamic library, in which case it needs to export this function
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// typedef ggml_backend_register_t * (*ggml_backend_init)(void);
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#ifdef __cplusplus
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}
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