From: Georgi Gerganov Date: Thu, 3 Oct 2024 19:11:21 +0000 (+0300) Subject: ggml : remove old file (skip) (#0) X-Git-Tag: upstream/0.0.1642~309 X-Git-Url: https://git.djapps.eu/?a=commitdiff_plain;h=47e4bf0065d8c6b8b2ca7766cd5d3ad9e107bde5;p=pkg%2Fggml%2Fsources%2Fggml ggml : remove old file (skip) (#0) --- diff --git a/scripts/sync-llama-am.sh b/scripts/sync-llama-am.sh index 04268a1b..bea88da5 100755 --- a/scripts/sync-llama-am.sh +++ b/scripts/sync-llama-am.sh @@ -122,7 +122,7 @@ if [ -f $SRC_GGML/llama-src.patch ]; then # ggml/src/ggml-aarch64.h -> src/ggml-aarch64.h # ggml/src/ggml-alloc.c -> src/ggml-alloc.c # ggml/src/ggml-backend-impl.h -> src/ggml-backend-impl.h - # ggml/src/ggml-backend.c -> src/ggml-backend.c + # ggml/src/ggml-backend.cpp -> src/ggml-backend.cpp # ggml/src/ggml-blas.cpp -> src/ggml-blas.cpp # ggml/src/ggml-cann/* -> src/ggml-cann/* # ggml/src/ggml-cann.cpp -> src/ggml-cann.cpp @@ -170,7 +170,7 @@ if [ -f $SRC_GGML/llama-src.patch ]; then -e 's/\/ggml\/src\/ggml-aarch64\.h/\/src\/ggml-aarch64.h/g' \ -e 's/\/ggml\/src\/ggml-alloc\.c/\/src\/ggml-alloc.c/g' \ -e 's/\/ggml\/src\/ggml-backend-impl\.h/\/src\/ggml-backend-impl.h/g' \ - -e 's/\/ggml\/src\/ggml-backend\.c/\/src\/ggml-backend.c/g' \ + -e 's/\/ggml\/src\/ggml-backend\.cpp/\/src\/ggml-backend.cpp/g' \ -e 's/\/ggml\/src\/ggml-blas\.cpp/\/src\/ggml-blas.cpp/g' \ -e 's/\/ggml\/src\/ggml-cann\//\/src\/ggml-cann\//g' \ -e 's/\/ggml\/src\/ggml-cann\.cpp/\/src\/ggml-cann.cpp/g' \ diff --git a/src/ggml-backend.c b/src/ggml-backend.c deleted file mode 100644 index ba280e06..00000000 --- a/src/ggml-backend.c +++ /dev/null @@ -1,2294 +0,0 @@ -#include "ggml-backend-impl.h" -#include "ggml-alloc.h" -#include "ggml-impl.h" - -#include -#include -#include -#include -#include -#include - - -#define MAX(a, b) ((a) > (b) ? (a) : (b)) - -// backend buffer type - -const char * ggml_backend_buft_name(ggml_backend_buffer_type_t buft) { - return buft->iface.get_name(buft); -} - -GGML_CALL ggml_backend_buffer_t ggml_backend_buft_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { - return buft->iface.alloc_buffer(buft, size); -} - -size_t ggml_backend_buft_get_alignment(ggml_backend_buffer_type_t buft) { - return buft->iface.get_alignment(buft); -} - -size_t ggml_backend_buft_get_max_size(ggml_backend_buffer_type_t buft) { - // get_max_size is optional, defaults to SIZE_MAX - if (buft->iface.get_max_size) { - return buft->iface.get_max_size(buft); - } - return SIZE_MAX; -} - -GGML_CALL size_t ggml_backend_buft_get_alloc_size(ggml_backend_buffer_type_t buft, struct ggml_tensor * tensor) { - // get_alloc_size is optional, defaults to ggml_nbytes - if (buft->iface.get_alloc_size) { - size_t size = buft->iface.get_alloc_size(buft, tensor); - assert(size >= ggml_nbytes(tensor)); - return size; - } - return ggml_nbytes(tensor); -} - -bool ggml_backend_buft_is_host(ggml_backend_buffer_type_t buft) { - if (buft->iface.is_host) { - return buft->iface.is_host(buft); - } - return false; -} - -// backend buffer - -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) { - ggml_backend_buffer_t buffer = malloc(sizeof(struct ggml_backend_buffer)); - - (*buffer) = (struct ggml_backend_buffer) { - /* .interface = */ iface, - /* .buft = */ buft, - /* .context = */ context, - /* .size = */ size, - /* .usage = */ GGML_BACKEND_BUFFER_USAGE_ANY - }; - - return buffer; -} - -const char * ggml_backend_buffer_name(ggml_backend_buffer_t buffer) { - return buffer->iface.get_name(buffer); -} - -void ggml_backend_buffer_free(ggml_backend_buffer_t buffer) { - if (buffer == NULL) { - return; - } - - if (buffer->iface.free_buffer != NULL) { - buffer->iface.free_buffer(buffer); - } - free(buffer); -} - -size_t ggml_backend_buffer_get_size(ggml_backend_buffer_t buffer) { - return buffer->size; -} - -void * ggml_backend_buffer_get_base(ggml_backend_buffer_t buffer) { - void * base = buffer->iface.get_base(buffer); - - GGML_ASSERT(base != NULL && "backend buffer base cannot be NULL"); - - return base; -} - -GGML_CALL void ggml_backend_buffer_init_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor) { - // init_tensor is optional - if (buffer->iface.init_tensor) { - buffer->iface.init_tensor(buffer, tensor); - } -} - -size_t ggml_backend_buffer_get_alignment (ggml_backend_buffer_t buffer) { - return ggml_backend_buft_get_alignment(ggml_backend_buffer_get_type(buffer)); -} - -size_t ggml_backend_buffer_get_max_size(ggml_backend_buffer_t buffer) { - return ggml_backend_buft_get_max_size(ggml_backend_buffer_get_type(buffer)); -} - -size_t ggml_backend_buffer_get_alloc_size(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor) { - return ggml_backend_buft_get_alloc_size(ggml_backend_buffer_get_type(buffer), tensor); -} - -void ggml_backend_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) { - buffer->iface.clear(buffer, value); -} - -bool ggml_backend_buffer_is_host(ggml_backend_buffer_t buffer) { - return ggml_backend_buft_is_host(ggml_backend_buffer_get_type(buffer)); -} - -void ggml_backend_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage) { - buffer->usage = usage; - - // FIXME: add a generic callback to the buffer interface - if (ggml_backend_buffer_is_multi_buffer(buffer)) { - ggml_backend_multi_buffer_set_usage(buffer, usage); - } -} - -enum ggml_backend_buffer_usage ggml_backend_buffer_get_usage(ggml_backend_buffer_t buffer) { - return buffer->usage; -} - -ggml_backend_buffer_type_t ggml_backend_buffer_get_type(ggml_backend_buffer_t buffer) { - return buffer->buft; -} - -void ggml_backend_buffer_reset(ggml_backend_buffer_t buffer) { - if (buffer->iface.reset) { - buffer->iface.reset(buffer); - } -} - -bool ggml_backend_buffer_copy_tensor(const struct ggml_tensor * src, struct ggml_tensor * dst) { - ggml_backend_buffer_t dst_buf = dst->view_src ? dst->view_src->buffer : dst->buffer; - if (dst_buf->iface.cpy_tensor) { - return dst_buf->iface.cpy_tensor(dst_buf, src, dst); - } - return false; -} - -// backend - -ggml_guid_t ggml_backend_guid(ggml_backend_t backend) { - if (backend == NULL) { - return NULL; - } - return backend->guid; -} - -const char * ggml_backend_name(ggml_backend_t backend) { - if (backend == NULL) { - return "NULL"; - } - return backend->iface.get_name(backend); -} - -void ggml_backend_free(ggml_backend_t backend) { - if (backend == NULL) { - return; - } - - backend->iface.free(backend); -} - -ggml_backend_buffer_type_t ggml_backend_get_default_buffer_type(ggml_backend_t backend) { - return backend->iface.get_default_buffer_type(backend); -} - -ggml_backend_buffer_t ggml_backend_alloc_buffer(ggml_backend_t backend, size_t size) { - return ggml_backend_buft_alloc_buffer(ggml_backend_get_default_buffer_type(backend), size); -} - -size_t ggml_backend_get_alignment(ggml_backend_t backend) { - return ggml_backend_buft_get_alignment(ggml_backend_get_default_buffer_type(backend)); -} - -size_t ggml_backend_get_max_size(ggml_backend_t backend) { - return ggml_backend_buft_get_max_size(ggml_backend_get_default_buffer_type(backend)); -} - -void ggml_backend_tensor_set_async(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) { - GGML_ASSERT(tensor->data != NULL && "tensor not allocated"); - GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor write out of bounds"); - - if (backend->iface.set_tensor_async == NULL) { - ggml_backend_tensor_set(tensor, data, offset, size); - } else { - backend->iface.set_tensor_async(backend, tensor, data, offset, size); - } -} - -void ggml_backend_tensor_get_async(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { - GGML_ASSERT(tensor->data != NULL && "tensor not allocated"); - GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor read out of bounds"); - - if (backend->iface.get_tensor_async == NULL) { - ggml_backend_tensor_get(tensor, data, offset, size); - } else { - backend->iface.get_tensor_async(backend, tensor, data, offset, size); - } -} - -GGML_CALL void ggml_backend_tensor_set(struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) { - ggml_backend_buffer_t buf = tensor->view_src ? tensor->view_src->buffer : tensor->buffer; - - GGML_ASSERT(buf != NULL && "tensor buffer not set"); - GGML_ASSERT(tensor->data != NULL && "tensor not allocated"); - GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor write out of bounds"); - - if (!size) { - return; - } - - buf->iface.set_tensor(buf, tensor, data, offset, size); -} - -GGML_CALL void ggml_backend_tensor_get(const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { - ggml_backend_buffer_t buf = tensor->view_src ? tensor->view_src->buffer : tensor->buffer; - - GGML_ASSERT(buf != NULL && "tensor buffer not set"); - GGML_ASSERT(tensor->data != NULL && "tensor not allocated"); - GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor read out of bounds"); - - if (!size) { - return; - } - - buf->iface.get_tensor(buf, tensor, data, offset, size); -} - -GGML_API GGML_CALL void ggml_backend_tensor_memset(struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) { - ggml_backend_buffer_t buf = tensor->view_src ? tensor->view_src->buffer : tensor->buffer; - - GGML_ASSERT(buf != NULL && "tensor buffer not set"); - GGML_ASSERT(tensor->data != NULL && "tensor not allocated"); - GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor write out of bounds"); - - if (!size) { - return; - } - - GGML_ASSERT(buf->iface.memset_tensor != NULL && "memset not supported by backend buffer"); - - buf->iface.memset_tensor(buf, tensor, value, offset, size); -} - -void ggml_backend_synchronize(ggml_backend_t backend) { - if (backend->iface.synchronize == NULL) { - return; - } - - backend->iface.synchronize(backend); -} - -ggml_backend_graph_plan_t ggml_backend_graph_plan_create(ggml_backend_t backend, struct ggml_cgraph * cgraph) { - GGML_ASSERT(backend->iface.graph_plan_create != NULL); - - return backend->iface.graph_plan_create(backend, cgraph); -} - -void ggml_backend_graph_plan_free(ggml_backend_t backend, ggml_backend_graph_plan_t plan) { - GGML_ASSERT(backend->iface.graph_plan_free != NULL); - - backend->iface.graph_plan_free(backend, plan); -} - -enum ggml_status ggml_backend_graph_plan_compute(ggml_backend_t backend, ggml_backend_graph_plan_t plan) { - GGML_ASSERT(backend->iface.graph_plan_compute != NULL); - - return backend->iface.graph_plan_compute(backend, plan); -} - -enum ggml_status ggml_backend_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) { - enum ggml_status err = ggml_backend_graph_compute_async(backend, cgraph); - ggml_backend_synchronize(backend); - return err; -} - -enum ggml_status ggml_backend_graph_compute_async(ggml_backend_t backend, struct ggml_cgraph * cgraph) { - return backend->iface.graph_compute(backend, cgraph); -} - -bool ggml_backend_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) { - return backend->iface.supports_op(backend, op); -} - -bool ggml_backend_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) { - return backend->iface.supports_buft(backend, buft); -} - -bool ggml_backend_offload_op(ggml_backend_t backend, const struct ggml_tensor * op) { - if (backend->iface.offload_op != NULL) { - return backend->iface.offload_op(backend, op); - } - return false; -} - -// backend copy - -static bool ggml_are_same_layout(const struct ggml_tensor * a, const struct ggml_tensor * b) { - if (a->type != b->type) { - return false; - } - for (int i = 0; i < GGML_MAX_DIMS; i++) { - if (a->ne[i] != b->ne[i]) { - return false; - } - if (a->nb[i] != b->nb[i]) { - return false; - } - } - return true; -} - -void ggml_backend_tensor_copy(struct ggml_tensor * src, struct ggml_tensor * dst) { - GGML_ASSERT(ggml_are_same_layout(src, dst) && "cannot copy tensors with different layouts"); - - if (src == dst) { - return; - } - - if (ggml_backend_buffer_is_host(src->buffer)) { - ggml_backend_tensor_set(dst, src->data, 0, ggml_nbytes(src)); - } else if (ggml_backend_buffer_is_host(dst->buffer)) { - ggml_backend_tensor_get(src, dst->data, 0, ggml_nbytes(src)); - } else if (!ggml_backend_buffer_copy_tensor(src, dst)) { -#ifndef NDEBUG - fprintf(stderr, "%s: warning: slow copy from %s to %s\n", __func__, ggml_backend_buffer_name(src->buffer), ggml_backend_buffer_name(dst->buffer)); -#endif - size_t nbytes = ggml_nbytes(src); - void * data = malloc(nbytes); - ggml_backend_tensor_get(src, data, 0, nbytes); - ggml_backend_tensor_set(dst, data, 0, nbytes); - free(data); - } -} - -void ggml_backend_tensor_copy_async(ggml_backend_t backend_src, ggml_backend_t backend_dst, struct ggml_tensor * src, struct ggml_tensor * dst) { - GGML_ASSERT(ggml_are_same_layout(src, dst) && "cannot copy tensors with different layouts"); - - if (src == dst) { - return; - } - - if (backend_dst->iface.cpy_tensor_async != NULL) { - if (backend_dst->iface.cpy_tensor_async(backend_src, backend_dst, src, dst)) { - return; - } - } - - // an async copy would normally happen after all the queued operations on both backends are completed - // to simulate the same behavior, we need to synchronize both backends first, and do a blocking copy - ggml_backend_synchronize(backend_src); - ggml_backend_synchronize(backend_dst); - ggml_backend_tensor_copy(src, dst); -} - -// events - -ggml_backend_event_t ggml_backend_event_new(ggml_backend_t backend) { - if (backend->iface.event_new == NULL) { - return NULL; - } - return backend->iface.event_new(backend); -} - -void ggml_backend_event_free(ggml_backend_event_t event) { - if (event == NULL) { - return; - } - event->backend->iface.event_free(event); -} - -void ggml_backend_event_record(ggml_backend_event_t event) { - GGML_ASSERT(event->backend->iface.event_record != NULL); - - event->backend->iface.event_record(event); -} - -void ggml_backend_event_synchronize(ggml_backend_event_t event) { - GGML_ASSERT(event->backend->iface.event_synchronize != NULL); - - event->backend->iface.event_synchronize(event); -} - -void ggml_backend_event_wait(ggml_backend_t backend, ggml_backend_event_t event) { - GGML_ASSERT(backend->iface.event_wait != NULL); - - backend->iface.event_wait(backend, event); -} - -// backend registry - -#define GGML_REG_MAX_BACKENDS 64 - -struct ggml_backend_reg { - char name[128]; - ggml_backend_init_fn init_fn; - ggml_backend_buffer_type_t default_buffer_type; - void * user_data; -}; - -static struct ggml_backend_reg ggml_backend_registry[GGML_REG_MAX_BACKENDS]; -static size_t ggml_backend_registry_count = 0; - -GGML_CALL static ggml_backend_t ggml_backend_reg_cpu_init(const char * params, void * user_data); - -GGML_CALL static void ggml_backend_registry_init(void) { - static bool initialized = false; - - if (initialized) { - return; - } - - initialized = true; - - ggml_backend_register("CPU", ggml_backend_reg_cpu_init, ggml_backend_cpu_buffer_type(), NULL); - - // add forward decls here to avoid including the backend headers -#ifdef GGML_USE_CUDA - extern GGML_CALL void ggml_backend_cuda_reg_devices(void); - ggml_backend_cuda_reg_devices(); -#endif - -#ifdef GGML_USE_SYCL - extern void ggml_backend_sycl_reg_devices(void); - ggml_backend_sycl_reg_devices(); -#endif - -#ifdef GGML_USE_METAL - extern GGML_CALL ggml_backend_t ggml_backend_reg_metal_init(const char * params, void * user_data); - extern GGML_CALL ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void); - ggml_backend_register("Metal", ggml_backend_reg_metal_init, ggml_backend_metal_buffer_type(), NULL); -#endif - -#ifdef GGML_USE_VULKAN - extern GGML_CALL int ggml_backend_vk_reg_devices(void); - ggml_backend_vk_reg_devices(); -#endif - -#ifdef GGML_USE_KOMPUTE - extern GGML_CALL void ggml_backend_kompute_reg_devices(void); - ggml_backend_kompute_reg_devices(); -#endif - -#ifdef GGML_USE_CANN - extern GGML_CALL int ggml_backend_cann_reg_devices(void); - ggml_backend_cann_reg_devices(); -#endif -} - -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) { - GGML_ASSERT(ggml_backend_registry_count < GGML_REG_MAX_BACKENDS); - - size_t id = ggml_backend_registry_count; - - ggml_backend_registry[id] = (struct ggml_backend_reg) { - /* .name = */ {0}, - /* .fn = */ init_fn, - /* .default_buffer_type = */ default_buffer_type, - /* .user_data = */ user_data, - }; - - snprintf(ggml_backend_registry[id].name, sizeof(ggml_backend_registry[id].name), "%s", name); - -#ifndef NDEBUG - fprintf(stderr, "%s: registered backend %s\n", __func__, name); -#endif - - ggml_backend_registry_count++; -} - -size_t ggml_backend_reg_get_count(void) { - ggml_backend_registry_init(); - - return ggml_backend_registry_count; -} - -size_t ggml_backend_reg_find_by_name(const char * name) { - ggml_backend_registry_init(); - - for (size_t i = 0; i < ggml_backend_registry_count; i++) { - // TODO: case insensitive in a portable way - if (strcmp(ggml_backend_registry[i].name, name) == 0) { - return i; - } - } - - // not found - return SIZE_MAX; -} - -// init from backend:params string -ggml_backend_t ggml_backend_reg_init_backend_from_str(const char * backend_str) { - ggml_backend_registry_init(); - - const char * params = strchr(backend_str, ':'); - char backend_name[128]; - if (params == NULL) { - snprintf(backend_name, sizeof(backend_name), "%s", backend_str); - params = ""; - } else { - snprintf(backend_name, sizeof(backend_name), "%.*s", (int)(params - backend_str), backend_str); - params++; - } - - size_t backend_i = ggml_backend_reg_find_by_name(backend_name); - - if (backend_i == SIZE_MAX) { - fprintf(stderr, "%s: backend %s not found\n", __func__, backend_name); - return NULL; - } - - return ggml_backend_reg_init_backend(backend_i, params); -} - -const char * ggml_backend_reg_get_name(size_t i) { - ggml_backend_registry_init(); - - GGML_ASSERT(i < ggml_backend_registry_count); - return ggml_backend_registry[i].name; -} - -ggml_backend_t ggml_backend_reg_init_backend(size_t i, const char * params) { - ggml_backend_registry_init(); - - GGML_ASSERT(i < ggml_backend_registry_count); - return ggml_backend_registry[i].init_fn(params, ggml_backend_registry[i].user_data); -} - -ggml_backend_buffer_type_t ggml_backend_reg_get_default_buffer_type(size_t i) { - ggml_backend_registry_init(); - - GGML_ASSERT(i < ggml_backend_registry_count); - return ggml_backend_registry[i].default_buffer_type; -} - -ggml_backend_buffer_t ggml_backend_reg_alloc_buffer(size_t i, size_t size) { - ggml_backend_registry_init(); - - GGML_ASSERT(i < ggml_backend_registry_count); - return ggml_backend_buft_alloc_buffer(ggml_backend_registry[i].default_buffer_type, size); -} - -// backend CPU - -static const size_t TENSOR_ALIGNMENT = 32; // required for mmap as gguf only guarantees 32-byte alignment - -GGML_CALL static const char * ggml_backend_cpu_buffer_name(ggml_backend_buffer_t buffer) { - return "CPU"; - - GGML_UNUSED(buffer); -} - -GGML_CALL static void * ggml_backend_cpu_buffer_get_base(ggml_backend_buffer_t buffer) { - uintptr_t data = (uintptr_t)buffer->context; - - // align the buffer - if (data % TENSOR_ALIGNMENT != 0) { - data = GGML_PAD(data, TENSOR_ALIGNMENT); - } - - return (void *)data; -} - -GGML_CALL static void ggml_backend_cpu_buffer_free_buffer(ggml_backend_buffer_t buffer) { - free(buffer->context); -} - -GGML_CALL static void ggml_backend_cpu_buffer_memset_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) { - memset((char *)tensor->data + offset, value, size); - - GGML_UNUSED(buffer); -} - -GGML_CALL static void ggml_backend_cpu_buffer_set_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) { - memcpy((char *)tensor->data + offset, data, size); - - GGML_UNUSED(buffer); -} - -GGML_CALL static void ggml_backend_cpu_buffer_get_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { - memcpy(data, (const char *)tensor->data + offset, size); - - GGML_UNUSED(buffer); -} - -GGML_CALL static bool ggml_backend_cpu_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst) { - if (ggml_backend_buffer_is_host(src->buffer)) { - memcpy(dst->data, src->data, ggml_nbytes(src)); - return true; - } - return false; - - GGML_UNUSED(buffer); -} - -GGML_CALL static void ggml_backend_cpu_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) { - memset(buffer->context, value, buffer->size); -} - -static struct ggml_backend_buffer_i cpu_backend_buffer_i = { - /* .get_name = */ ggml_backend_cpu_buffer_name, - /* .free_buffer = */ ggml_backend_cpu_buffer_free_buffer, - /* .get_base = */ ggml_backend_cpu_buffer_get_base, - /* .init_tensor = */ NULL, // no initialization required - /* .memset_tensor = */ ggml_backend_cpu_buffer_memset_tensor, - /* .set_tensor = */ ggml_backend_cpu_buffer_set_tensor, - /* .get_tensor = */ ggml_backend_cpu_buffer_get_tensor, - /* .cpy_tensor = */ ggml_backend_cpu_buffer_cpy_tensor, - /* .clear = */ ggml_backend_cpu_buffer_clear, - /* .reset = */ NULL, -}; - -// for buffers from ptr, free is not called -static struct ggml_backend_buffer_i cpu_backend_buffer_i_from_ptr = { - /* .get_name = */ ggml_backend_cpu_buffer_name, - /* .free_buffer = */ NULL, // ptr is not owned by the buffer, so it does not need to be freed - /* .get_base = */ ggml_backend_cpu_buffer_get_base, - /* .init_tensor = */ NULL, // no initialization required - /* .memset_tensor = */ ggml_backend_cpu_buffer_memset_tensor, - /* .set_tensor = */ ggml_backend_cpu_buffer_set_tensor, - /* .get_tensor = */ ggml_backend_cpu_buffer_get_tensor, - /* .cpy_tensor = */ ggml_backend_cpu_buffer_cpy_tensor, - /* .clear = */ ggml_backend_cpu_buffer_clear, - /* .reset = */ NULL, -}; - -GGML_CALL static const char * ggml_backend_cpu_buffer_type_get_name(ggml_backend_buffer_type_t buft) { - return "CPU"; - - GGML_UNUSED(buft); -} - -GGML_CALL static ggml_backend_buffer_t ggml_backend_cpu_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { - size += TENSOR_ALIGNMENT; // malloc may return an address that is not aligned - void * data = malloc(size); // TODO: use GGML_ALIGNED_MALLOC (move to ggml-impl.h) - if (data == NULL) { - fprintf(stderr, "%s: failed to allocate buffer of size %zu\n", __func__, size); - return NULL; - } - - return ggml_backend_buffer_init(buft, cpu_backend_buffer_i, data, size); -} - -GGML_CALL static size_t ggml_backend_cpu_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) { - return TENSOR_ALIGNMENT; - - GGML_UNUSED(buft); -} - -GGML_CALL static bool ggml_backend_cpu_buffer_type_is_host(ggml_backend_buffer_type_t buft) { - return true; - - GGML_UNUSED(buft); -} - -GGML_CALL ggml_backend_buffer_type_t ggml_backend_cpu_buffer_type(void) { - static struct ggml_backend_buffer_type ggml_backend_cpu_buffer_type = { - /* .iface = */ { - /* .get_name = */ ggml_backend_cpu_buffer_type_get_name, - /* .alloc_buffer = */ ggml_backend_cpu_buffer_type_alloc_buffer, - /* .get_alignment = */ ggml_backend_cpu_buffer_type_get_alignment, - /* .get_max_size = */ NULL, // defaults to SIZE_MAX - /* .get_alloc_size = */ NULL, // defaults to ggml_nbytes - /* .is_host = */ ggml_backend_cpu_buffer_type_is_host, - }, - /* .context = */ NULL, - }; - - return &ggml_backend_cpu_buffer_type; -} - -#ifdef GGML_USE_CPU_HBM - -// buffer type HBM - -#include - -GGML_CALL static const char * ggml_backend_cpu_hbm_buffer_type_get_name(ggml_backend_buffer_type_t buft) { - return "CPU_HBM"; - - GGML_UNUSED(buft); -} - -GGML_CALL static const char * ggml_backend_cpu_hbm_buffer_get_name(ggml_backend_buffer_t buf) { - return "CPU_HBM"; - - GGML_UNUSED(buf); -} - -GGML_CALL static void ggml_backend_cpu_hbm_buffer_free_buffer(ggml_backend_buffer_t buffer) { - hbw_free(buffer->context); -} - -GGML_CALL static ggml_backend_buffer_t ggml_backend_cpu_hbm_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { - //void * ptr = hbw_malloc(size); - void * ptr; - int result = hbw_posix_memalign(&ptr, ggml_backend_cpu_buffer_type_get_alignment(buft), size); - if (result != 0) { - fprintf(stderr, "failed to allocate HBM buffer of size %zu\n", size); - return NULL; - } - - ggml_backend_buffer_t buffer = ggml_backend_cpu_buffer_from_ptr(ptr, size); - buffer->buft = buft; - buffer->iface.get_name = ggml_backend_cpu_hbm_buffer_get_name; - buffer->iface.free_buffer = ggml_backend_cpu_hbm_buffer_free_buffer; - - return buffer; -} - -ggml_backend_buffer_type_t ggml_backend_cpu_hbm_buffer_type(void) { - static struct ggml_backend_buffer_type ggml_backend_cpu_buffer_type_hbm = { - /* .iface = */ { - /* .get_name = */ ggml_backend_cpu_hbm_buffer_type_get_name, - /* .alloc_buffer = */ ggml_backend_cpu_hbm_buffer_type_alloc_buffer, - /* .get_alignment = */ ggml_backend_cpu_buffer_type_get_alignment, - /* .get_max_size = */ NULL, // defaults to SIZE_MAX - /* .get_alloc_size = */ NULL, // defaults to ggml_nbytes - /* .is_host = */ ggml_backend_cpu_buffer_type_is_host, - }, - /* .context = */ NULL, - }; - - return &ggml_backend_cpu_buffer_type_hbm; -} -#endif - -struct ggml_backend_cpu_context { - int n_threads; - ggml_threadpool_t threadpool; - - void * work_data; - size_t work_size; - - ggml_abort_callback abort_callback; - void * abort_callback_data; -}; - -GGML_CALL static const char * ggml_backend_cpu_name(ggml_backend_t backend) { - return "CPU"; - - GGML_UNUSED(backend); -} - -GGML_CALL static void ggml_backend_cpu_free(ggml_backend_t backend) { - struct ggml_backend_cpu_context * cpu_ctx = (struct ggml_backend_cpu_context *)backend->context; - free(cpu_ctx->work_data); - free(cpu_ctx); - free(backend); -} - -GGML_CALL static ggml_backend_buffer_type_t ggml_backend_cpu_get_default_buffer_type(ggml_backend_t backend) { - return ggml_backend_cpu_buffer_type(); - - GGML_UNUSED(backend); -} - -struct ggml_backend_plan_cpu { - struct ggml_cplan cplan; - struct ggml_cgraph cgraph; -}; - -GGML_CALL static ggml_backend_graph_plan_t ggml_backend_cpu_graph_plan_create(ggml_backend_t backend, const struct ggml_cgraph * cgraph) { - struct ggml_backend_cpu_context * cpu_ctx = (struct ggml_backend_cpu_context *)backend->context; - - struct ggml_backend_plan_cpu * cpu_plan = malloc(sizeof(struct ggml_backend_plan_cpu)); - - cpu_plan->cplan = ggml_graph_plan(cgraph, cpu_ctx->n_threads, cpu_ctx->threadpool); - cpu_plan->cgraph = *cgraph; // FIXME: deep copy - - if (cpu_plan->cplan.work_size > 0) { - cpu_plan->cplan.work_data = malloc(cpu_plan->cplan.work_size); - if (cpu_plan->cplan.work_data == NULL) { - free(cpu_plan); - return NULL; - } - } - - cpu_plan->cplan.abort_callback = cpu_ctx->abort_callback; - cpu_plan->cplan.abort_callback_data = cpu_ctx->abort_callback_data; - - return cpu_plan; -} - -GGML_CALL static void ggml_backend_cpu_graph_plan_free(ggml_backend_t backend, ggml_backend_graph_plan_t plan) { - struct ggml_backend_plan_cpu * cpu_plan = (struct ggml_backend_plan_cpu *)plan; - - free(cpu_plan->cplan.work_data); - free(cpu_plan); - - GGML_UNUSED(backend); -} - -GGML_CALL static enum ggml_status ggml_backend_cpu_graph_plan_compute(ggml_backend_t backend, ggml_backend_graph_plan_t plan) { - struct ggml_backend_plan_cpu * cpu_plan = (struct ggml_backend_plan_cpu *)plan; - - return ggml_graph_compute(&cpu_plan->cgraph, &cpu_plan->cplan); - - GGML_UNUSED(backend); -} - -GGML_CALL static enum ggml_status ggml_backend_cpu_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) { - struct ggml_backend_cpu_context * cpu_ctx = (struct ggml_backend_cpu_context *)backend->context; - - struct ggml_cplan cplan = ggml_graph_plan(cgraph, cpu_ctx->n_threads, cpu_ctx->threadpool); - - if (cpu_ctx->work_size < cplan.work_size) { - free(cpu_ctx->work_data); - cpu_ctx->work_data = malloc(cplan.work_size); - if (cpu_ctx->work_data == NULL) { - cpu_ctx->work_size = 0; - return GGML_STATUS_ALLOC_FAILED; - } - cpu_ctx->work_size = cplan.work_size; - } - cplan.work_data = cpu_ctx->work_data; - - cplan.abort_callback = cpu_ctx->abort_callback; - cplan.abort_callback_data = cpu_ctx->abort_callback_data; - - return ggml_graph_compute(cgraph, &cplan); -} - -GGML_CALL static bool ggml_backend_cpu_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) { - switch (op->op) { - case GGML_OP_CPY: - return - op->type != GGML_TYPE_IQ2_XXS && - op->type != GGML_TYPE_IQ2_XS && - op->type != GGML_TYPE_IQ1_S && - op->type != GGML_TYPE_IQ1_M; // missing type_traits.from_float - case GGML_OP_MUL_MAT: - return op->src[1]->type == GGML_TYPE_F32 || op->src[1]->type == ggml_internal_get_type_traits(op->src[0]->type).vec_dot_type; - case GGML_OP_ROPE_BACK: - return op->src[2] == NULL && (op->op_params[2] & 4) == 0; - case GGML_OP_IM2COL_BACK: - return op->src[0]->type == GGML_TYPE_F32 && op->src[1]->type == GGML_TYPE_F32; - default: - return true; - } - - GGML_UNUSED(backend); -} - -GGML_CALL static bool ggml_backend_cpu_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) { - return ggml_backend_buft_is_host(buft); - - GGML_UNUSED(backend); -} - -static struct ggml_backend_i cpu_backend_i = { - /* .get_name = */ ggml_backend_cpu_name, - /* .free = */ ggml_backend_cpu_free, - /* .get_default_buffer_type = */ ggml_backend_cpu_get_default_buffer_type, - /* .set_tensor_async = */ NULL, - /* .get_tensor_async = */ NULL, - /* .cpy_tensor_async = */ NULL, - /* .synchronize = */ NULL, - /* .graph_plan_create = */ ggml_backend_cpu_graph_plan_create, - /* .graph_plan_free = */ ggml_backend_cpu_graph_plan_free, - /* .graph_plan_update = */ NULL, - /* .graph_plan_compute = */ ggml_backend_cpu_graph_plan_compute, - /* .graph_compute = */ ggml_backend_cpu_graph_compute, - /* .supports_op = */ ggml_backend_cpu_supports_op, - /* .supports_buft = */ ggml_backend_cpu_supports_buft, - /* .offload_op = */ NULL, - /* .event_new = */ NULL, - /* .event_free = */ NULL, - /* .event_record = */ NULL, - /* .event_wait = */ NULL, - /* .event_synchronize = */ NULL, -}; - -static ggml_guid_t ggml_backend_cpu_guid(void) { - static ggml_guid guid = { 0xaa, 0x67, 0xc7, 0x43, 0x96, 0xe6, 0xa3, 0x8a, 0xe3, 0xaf, 0xea, 0x92, 0x36, 0xbc, 0xfc, 0x89 }; - return &guid; -} - -ggml_backend_t ggml_backend_cpu_init(void) { - struct ggml_backend_cpu_context * ctx = malloc(sizeof(struct ggml_backend_cpu_context)); - if (ctx == NULL) { - return NULL; - } - - ctx->n_threads = GGML_DEFAULT_N_THREADS; - ctx->threadpool = NULL; - ctx->work_data = NULL; - ctx->work_size = 0; - ctx->abort_callback = NULL; - ctx->abort_callback_data = NULL; - - ggml_backend_t cpu_backend = malloc(sizeof(struct ggml_backend)); - if (cpu_backend == NULL) { - free(ctx); - return NULL; - } - - *cpu_backend = (struct ggml_backend) { - /* .guid = */ ggml_backend_cpu_guid(), - /* .interface = */ cpu_backend_i, - /* .context = */ ctx - }; - return cpu_backend; -} - -GGML_CALL bool ggml_backend_is_cpu(ggml_backend_t backend) { - return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_cpu_guid()); -} - -void ggml_backend_cpu_set_n_threads(ggml_backend_t backend_cpu, int n_threads) { - GGML_ASSERT(ggml_backend_is_cpu(backend_cpu)); - - struct ggml_backend_cpu_context * ctx = (struct ggml_backend_cpu_context *)backend_cpu->context; - ctx->n_threads = n_threads; -} - -void ggml_backend_cpu_set_threadpool(ggml_backend_t backend_cpu, ggml_threadpool_t threadpool) { - GGML_ASSERT(ggml_backend_is_cpu(backend_cpu)); - - struct ggml_backend_cpu_context * ctx = (struct ggml_backend_cpu_context *)backend_cpu->context; - - if (ctx->threadpool && ctx->threadpool != threadpool) { - // already had a different threadpool, pause/suspend it before switching - ggml_threadpool_pause(ctx->threadpool); - } - ctx->threadpool = threadpool; -} - -void ggml_backend_cpu_set_abort_callback(ggml_backend_t backend_cpu, ggml_abort_callback abort_callback, void * abort_callback_data) { - GGML_ASSERT(ggml_backend_is_cpu(backend_cpu)); - - struct ggml_backend_cpu_context * ctx = (struct ggml_backend_cpu_context *)backend_cpu->context; - ctx->abort_callback = abort_callback; - ctx->abort_callback_data = abort_callback_data; -} - -GGML_CALL ggml_backend_buffer_t ggml_backend_cpu_buffer_from_ptr(void * ptr, size_t size) { - GGML_ASSERT((uintptr_t)ptr % TENSOR_ALIGNMENT == 0 && "buffer pointer must be aligned"); - return ggml_backend_buffer_init(ggml_backend_cpu_buffer_type(), cpu_backend_buffer_i_from_ptr, ptr, size); -} - -GGML_CALL static ggml_backend_t ggml_backend_reg_cpu_init(const char * params, void * user_data) { - return ggml_backend_cpu_init(); - - GGML_UNUSED(params); - GGML_UNUSED(user_data); -} - -// multi-buffer buffer - -struct ggml_backend_multi_buffer_context { - ggml_backend_buffer_t * buffers; - size_t n_buffers; -}; - -typedef struct ggml_backend_multi_buffer_context * ggml_backend_multi_buffer_context_t; - -GGML_CALL static const char * ggml_backend_multi_buffer_get_name(ggml_backend_buffer_t buffer) { - ggml_backend_multi_buffer_context_t ctx = (ggml_backend_multi_buffer_context_t) buffer->context; - - return ctx->buffers[0]->iface.get_name(ctx->buffers[0]); -} - -GGML_CALL static void ggml_backend_multi_buffer_free_buffer(ggml_backend_buffer_t buffer) { - ggml_backend_multi_buffer_context_t ctx = (ggml_backend_multi_buffer_context_t) buffer->context; - for (size_t i = 0; i < ctx->n_buffers; i++) { - ggml_backend_buffer_free(ctx->buffers[i]); - } - - free(ctx->buffers); - free(ctx); -} - -GGML_CALL static void ggml_backend_multi_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) { - ggml_backend_multi_buffer_context_t ctx = (ggml_backend_multi_buffer_context_t) buffer->context; - for (size_t i = 0; i < ctx->n_buffers; i++) { - ggml_backend_buffer_clear(ctx->buffers[i], value); - } -} - -static struct ggml_backend_buffer_i ggml_backend_multi_buffer_context_interface(void) { - static struct ggml_backend_buffer_i multi_backend_buffer_i = { - /* .get_name = */ ggml_backend_multi_buffer_get_name, - /* .free_buffer = */ ggml_backend_multi_buffer_free_buffer, - /* .get_base = */ NULL, - /* .init_tensor = */ NULL, - /* .memset_tensor = */ NULL, - /* .set_tensor = */ NULL, - /* .get_tensor = */ NULL, - /* .cpy_tensor = */ NULL, - /* .clear = */ ggml_backend_multi_buffer_clear, - /* .reset = */ NULL, - }; - - return multi_backend_buffer_i; -} - -GGML_CALL ggml_backend_buffer_t ggml_backend_multi_buffer_alloc_buffer(ggml_backend_buffer_t * buffers, size_t n_buffers) { - ggml_backend_multi_buffer_context_t ctx = (ggml_backend_multi_buffer_context_t) malloc(sizeof(struct ggml_backend_multi_buffer_context)); - ctx->n_buffers = n_buffers; - ctx->buffers = (ggml_backend_buffer_t *) malloc(n_buffers * sizeof(ggml_backend_buffer_t)); - - GGML_ASSERT(ctx->buffers != NULL); - - size_t total_size = 0; - for (size_t i = 0; i < n_buffers; i++) { - ctx->buffers[i] = buffers[i]; - total_size += ggml_backend_buffer_get_size(buffers[i]); - } - - return ggml_backend_buffer_init(buffers[0]->buft, ggml_backend_multi_buffer_context_interface(), ctx, total_size); -} - -GGML_CALL bool ggml_backend_buffer_is_multi_buffer(ggml_backend_buffer_t buffer) { - return buffer->iface.get_name == ggml_backend_multi_buffer_get_name; -} - -GGML_CALL void ggml_backend_multi_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage) { - GGML_ASSERT(ggml_backend_buffer_is_multi_buffer(buffer)); - ggml_backend_multi_buffer_context_t ctx = (ggml_backend_multi_buffer_context_t) buffer->context; - for (size_t i = 0; i < ctx->n_buffers; i++) { - ggml_backend_buffer_set_usage(ctx->buffers[i], usage); - } -} - -// creates a copy of the tensor with the same memory layout -static struct ggml_tensor * ggml_dup_tensor_layout(struct ggml_context * ctx, const struct ggml_tensor * tensor) { - struct ggml_tensor * dup = ggml_dup_tensor(ctx, tensor); - for (int i = 0; i < GGML_MAX_DIMS; i++) { - dup->nb[i] = tensor->nb[i]; - } - return dup; -} - -static bool ggml_is_view_op(enum ggml_op op) { - return op == GGML_OP_VIEW || op == GGML_OP_RESHAPE || op == GGML_OP_PERMUTE || op == GGML_OP_TRANSPOSE; -} - -// scheduler - -#ifndef GGML_SCHED_MAX_BACKENDS -#define GGML_SCHED_MAX_BACKENDS 16 -#endif - -#ifndef GGML_SCHED_MAX_SPLIT_INPUTS -#define GGML_SCHED_MAX_SPLIT_INPUTS GGML_MAX_SRC -#endif - -#ifndef GGML_SCHED_MAX_COPIES -#define GGML_SCHED_MAX_COPIES 4 -#endif - -struct ggml_backend_sched_split { - int backend_id; - int i_start; - int i_end; - struct ggml_tensor * inputs[GGML_SCHED_MAX_SPLIT_INPUTS]; - int n_inputs; - // graph view of this split - struct ggml_cgraph graph; -}; - -struct ggml_backend_sched { - bool is_reset; // true if the scheduler has been reset since the last graph split - bool is_alloc; - - int n_backends; - - ggml_backend_t backends[GGML_SCHED_MAX_BACKENDS]; - ggml_backend_buffer_type_t bufts[GGML_SCHED_MAX_BACKENDS]; - ggml_gallocr_t galloc; - - // hash map of the nodes in the graph - struct ggml_hash_set hash_set; - int * hv_tensor_backend_ids; // [hash_set.size] - struct ggml_tensor ** hv_tensor_copies; // [hash_set.size][n_backends][n_copies] - - int * node_backend_ids; // [graph_size] - int * leaf_backend_ids; // [graph_size] - - int * prev_node_backend_ids; // [graph_size] - int * prev_leaf_backend_ids; // [graph_size] - - // copy of the graph with modified inputs - struct ggml_cgraph graph; - - // graph splits - struct ggml_backend_sched_split * splits; - int n_splits; - int splits_capacity; - - // pipeline parallelism support - int n_copies; - int cur_copy; - ggml_backend_event_t events[GGML_SCHED_MAX_BACKENDS][GGML_SCHED_MAX_COPIES]; - struct ggml_tensor * graph_inputs[GGML_SCHED_MAX_SPLIT_INPUTS]; - int n_graph_inputs; - - struct ggml_context * ctx; - - ggml_backend_sched_eval_callback callback_eval; - void * callback_eval_user_data; - - char * context_buffer; - size_t context_buffer_size; - - bool debug; -}; - -#define hash_id(tensor) ggml_hash_find_or_insert(&sched->hash_set, tensor) -#define tensor_backend_id(tensor) sched->hv_tensor_backend_ids[hash_id(tensor)] -#define tensor_id_copy(id, backend_id, copy_id) sched->hv_tensor_copies[(id) * sched->n_backends * sched->n_copies + (backend_id) * sched->n_copies + (copy_id)] -#define tensor_copy(tensor, backend_id, copy_id) tensor_id_copy(hash_id(tensor), backend_id, copy_id) - -// returns the priority of the backend, lower id is higher priority -static int ggml_backend_sched_backend_id(ggml_backend_sched_t sched, ggml_backend_t backend) { - for (int i = 0; i < sched->n_backends; i++) { - if (sched->backends[i] == backend) { - return i; - } - } - return -1; -} - -static int ggml_backend_sched_backend_from_buffer(ggml_backend_sched_t sched, const struct ggml_tensor * tensor, const struct ggml_tensor * op) { - ggml_backend_buffer_t buffer = tensor->buffer; - if (buffer == NULL) { - return -1; - } - - // find highest prio backend that supports the buffer type and the op - for (int i = 0; i < sched->n_backends; i++) { - if (ggml_backend_supports_buft(sched->backends[i], buffer->buft) && - ggml_backend_supports_op(sched->backends[i], op)) { - return i; - } - } - -#ifndef NDEBUG - fprintf(stderr, "%s: warning: no backend supports op %s with a weight with buffer type %s used in tensor %s, the weight will need to be copied\n", - __func__, ggml_op_desc(tensor), ggml_backend_buffer_name(buffer), tensor->name); -#endif - - return -1; -} - -#if 0 -#define GGML_SCHED_MAX_SPLITS_DEBUG 4096 -static char causes[GGML_DEFAULT_GRAPH_SIZE*16 + GGML_SCHED_MAX_SPLITS_DEBUG*GGML_SCHED_MAX_SPLIT_INPUTS][128]; // debug only -#define SET_CAUSE(node, ...) sprintf(causes[hash_id(node)], __VA_ARGS__) -#define GET_CAUSE(node) causes[hash_id(node)] -#else -#define SET_CAUSE(node, ...) -#define GET_CAUSE(node) "" -#endif - -// returns the backend that should be used for the node based on the current locations -static int ggml_backend_sched_backend_id_from_cur(ggml_backend_sched_t sched, struct ggml_tensor * tensor) { - // TODO: use supports_op to check if the backend supports the op - - // assign pre-allocated nodes to their backend - int cur_backend_id = ggml_backend_sched_backend_from_buffer(sched, tensor, tensor); - if (cur_backend_id != -1) { - SET_CAUSE(tensor, "1.dst"); - return cur_backend_id; - } - - // view_src - if (tensor->view_src != NULL) { - cur_backend_id = ggml_backend_sched_backend_from_buffer(sched, tensor->view_src, tensor); - if (cur_backend_id != -1) { - SET_CAUSE(tensor, "1.vsrc"); - return cur_backend_id; - } - } - - if (tensor->buffer || (tensor->view_src && tensor->view_src->buffer)) { - // since the tensor is pre-allocated, it cannot be moved to another backend - GGML_ABORT("pre-allocated tensor in a backend that cannot run the operation"); - } - - // graph input - if (tensor->flags & GGML_TENSOR_FLAG_INPUT) { - cur_backend_id = sched->n_backends - 1; // last backend (assumed CPU) - SET_CAUSE(tensor, "1.inp"); - return cur_backend_id; - } - - // operations with weights are preferably run on the same backend as the weights - for (int i = 0; i < GGML_MAX_SRC; i++) { - const struct ggml_tensor * src = tensor->src[i]; - if (src == NULL) { - continue; - } - if (src->buffer != NULL && src->buffer->usage == GGML_BACKEND_BUFFER_USAGE_WEIGHTS) { - int src_backend_id = ggml_backend_sched_backend_from_buffer(sched, src, tensor); - // check if a backend with higher prio wants to offload the op - if (src_backend_id == sched->n_backends - 1) { - for (int b = 0; b < src_backend_id; b++) { - if (ggml_backend_supports_op(sched->backends[b], tensor) && ggml_backend_offload_op(sched->backends[b], tensor)) { - SET_CAUSE(tensor, "1.off"); - return b; - } - } - } - SET_CAUSE(tensor, "1.wgt%d", i); - return src_backend_id; - } - } - - return -1; -} - -static char * fmt_size(size_t size) { - static char buffer[128]; - if (size >= 1024*1024) { - snprintf(buffer, sizeof(buffer), "%zuM", size/1024/1024); - } else { - snprintf(buffer, sizeof(buffer), "%zuK", size/1024); - } - return buffer; -} - -static void ggml_backend_sched_print_assignments(ggml_backend_sched_t sched, struct ggml_cgraph * graph) { - int cur_split = 0; - for (int i = 0; i < graph->n_nodes; i++) { - if (cur_split < sched->n_splits && i == sched->splits[cur_split].i_start) { - ggml_backend_t split_backend = sched->backends[sched->splits[cur_split].backend_id]; - fprintf(stderr, "\n## SPLIT #%d: %s # %d inputs: ", cur_split, ggml_backend_name(split_backend), - sched->splits[cur_split].n_inputs); - for (int j = 0; j < sched->splits[cur_split].n_inputs; j++) { - fprintf(stderr, "[%s (%5.5s)] ", sched->splits[cur_split].inputs[j]->name, - fmt_size(ggml_nbytes(sched->splits[cur_split].inputs[j]))); - } - fprintf(stderr, "\n"); - cur_split++; - } - struct ggml_tensor * node = graph->nodes[i]; - if (ggml_is_view_op(node->op)) { - continue; - } - ggml_backend_t tensor_backend = ggml_backend_sched_get_tensor_backend(sched, node); - fprintf(stderr, "node #%3d (%10.10s): %20.20s (%5.5s) [%5.5s %8.8s]:", i, ggml_op_name(node->op), node->name, - fmt_size(ggml_nbytes(node)), tensor_backend ? ggml_backend_name(tensor_backend) : "NULL", GET_CAUSE(node)); - for (int j = 0; j < GGML_MAX_SRC; j++) { - struct ggml_tensor * src = node->src[j]; - if (src == NULL) { - continue; - } - ggml_backend_t src_backend = ggml_backend_sched_get_tensor_backend(sched, src); - fprintf(stderr, " %20.20s (%5.5s) [%5.5s %8.8s]", src->name, - fmt_size(ggml_nbytes(src)), src_backend ? ggml_backend_name(src_backend) : "NULL", GET_CAUSE(src)); - } - fprintf(stderr, "\n"); - } -} - -static bool ggml_backend_sched_buffer_supported(ggml_backend_sched_t sched, struct ggml_tensor * t, int backend_id) { - ggml_backend_buffer_t buf = t->view_src ? t->view_src->buffer : t->buffer; - ggml_backend_buffer_type_t buft = NULL; - - if (buf) { - // the tensor is already allocated - buft = buf->buft; - } else { - // see if the tensor already has a backend assigned, and use the buffer type of that backend - int tensor_backend_id = tensor_backend_id(t); - if (tensor_backend_id == -1 && t->view_src) { - tensor_backend_id = tensor_backend_id(t->view_src); - } - if (tensor_backend_id != -1) { - buft = sched->bufts[tensor_backend_id]; - } - } - - return buft != NULL && ggml_backend_supports_buft(sched->backends[backend_id], buft); -} - -static void ggml_backend_sched_set_if_supported(ggml_backend_sched_t sched, struct ggml_tensor * node, int cur_backend_id, int * node_backend_id) { - if (ggml_backend_supports_op(sched->backends[cur_backend_id], node)) { - *node_backend_id = cur_backend_id; - SET_CAUSE(node, "2.sup"); - } -} - -// assigns backends to ops and splits the graph into subgraphs that can be computed on the same backend -static void ggml_backend_sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgraph * graph) { - // reset splits - sched->n_splits = 0; - sched->n_graph_inputs = 0; - sched->is_reset = false; - - struct ggml_init_params params = { - /* .mem_size = */ sched->context_buffer_size, - /* .mem_buffer = */ sched->context_buffer, - /* .no_alloc = */ true - }; - - ggml_free(sched->ctx); - - sched->ctx = ggml_init(params); - if (sched->ctx == NULL) { - GGML_ABORT("%s: failed to initialize context\n", __func__); - } - - // pass 1: assign backends to ops with pre-allocated inputs - for (int i = 0; i < graph->n_leafs; i++) { - struct ggml_tensor * leaf = graph->leafs[i]; - int * leaf_backend_id = &tensor_backend_id(leaf); - // do not overwrite user assignments - if (*leaf_backend_id == -1) { - *leaf_backend_id = ggml_backend_sched_backend_id_from_cur(sched, leaf); - } - } - - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - int * node_backend_id = &tensor_backend_id(node); - // do not overwrite user assignments - if (*node_backend_id == -1) { - *node_backend_id = ggml_backend_sched_backend_id_from_cur(sched, node); - -#if 0 - // src - if (node->op == GGML_OP_NONE) { - continue; - } - - for (int j = 0; j < GGML_MAX_SRC; j++) { - struct ggml_tensor * src = node->src[j]; - if (src == NULL) { - continue; - } - int * src_backend_id = &tensor_backend_id(src); - if (*src_backend_id == -1) { - *src_backend_id = ggml_backend_sched_backend_id_from_cur(sched, src); - } - } -#endif - } - } - - // pass 2: expand current backend assignments - // assign the same backend to adjacent nodes - // expand gpu backends (i.e. non last prio) up and down, ignoring cpu (the lowest priority backend) - // thus, cpu will never be used unless weights are on cpu, or there are no gpu ops between cpu ops - // ops unsupported by the backend being expanded will be left unassigned so that they can be assigned later when the locations of its inputs are known - // expand gpu down - { - int cur_backend_id = -1; - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - if (ggml_is_view_op(node->op)) { - continue; - } - int * node_backend_id = &tensor_backend_id(node); - if (*node_backend_id != -1) { - if (*node_backend_id == sched->n_backends - 1) { - // skip cpu (lowest prio backend) - cur_backend_id = -1; - } else { - cur_backend_id = *node_backend_id; - } - } else if (cur_backend_id != -1) { - ggml_backend_sched_set_if_supported(sched, node, cur_backend_id, node_backend_id); - } - } - } - // expand gpu up - { - int cur_backend_id = -1; - for (int i = graph->n_nodes - 1; i >= 0; i--) { - struct ggml_tensor * node = graph->nodes[i]; - if (ggml_is_view_op(node->op)) { - continue; - } - int * node_backend_id = &tensor_backend_id(node); - if (*node_backend_id != -1) { - if (*node_backend_id == sched->n_backends - 1) { - // skip cpu (lowest prio backend) - cur_backend_id = -1; - } else { - cur_backend_id = *node_backend_id; - } - } else if (cur_backend_id != -1) { - ggml_backend_sched_set_if_supported(sched, node, cur_backend_id, node_backend_id); - } - } - } - // expand rest down - { - int cur_backend_id = -1; - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - if (ggml_is_view_op(node->op)) { - continue; - } - int * node_backend_id = &tensor_backend_id(node); - if (*node_backend_id != -1) { - cur_backend_id = *node_backend_id; - } else if (cur_backend_id != -1) { - ggml_backend_sched_set_if_supported(sched, node, cur_backend_id, node_backend_id); - } - } - } - // expand rest up - { - int cur_backend_id = -1; - for (int i = graph->n_nodes - 1; i >= 0; i--) { - struct ggml_tensor * node = graph->nodes[i]; - if (ggml_is_view_op(node->op)) { - continue; - } - int * node_backend_id = &tensor_backend_id(node); - if (*node_backend_id != -1) { - cur_backend_id = *node_backend_id; - } else if (cur_backend_id != -1) { - ggml_backend_sched_set_if_supported(sched, node, cur_backend_id, node_backend_id); - } - } - } - - // pass 3: upgrade nodes to higher prio backends with compatible buffer types - // if the tensor is already in the same buffer type (*) as another higher priority backend, we should move it there - // however, we also need to verify that the sources are in compatible buffer types - // (*) the actual requirement is more relaxed, the buffer type of the backend should be supported by all the users of this tensor further down the graph - // however, this is slow to verify, so we have a more strict requirement that the buffer type is the same - // this is not uncommon since multiple backends can use host memory, with the same buffer type (eg. BLAS and CPU) - // additionally, set remaining unassigned nodes to the backend with the most supported inputs - // only nodes that could not be assigned during expansion due to the backend not supporting the op should be unassigned at this point - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - if (ggml_is_view_op(node->op)) { - continue; - } - int * node_backend_id = &tensor_backend_id(node); - if (*node_backend_id == -1) { - // unassigned node: find the backend with the most supported inputs - int n_supported_best = -1; - for (int b = 0; b < sched->n_backends; b++) { - if (ggml_backend_supports_op(sched->backends[b], node)) { - int n_supported = 0; - for (int j = 0; j < GGML_MAX_SRC; j++) { - struct ggml_tensor * src = node->src[j]; - if (src == NULL) { - continue; - } - if ((tensor_backend_id(src) != -1 || tensor_backend_id(src->view_src) != -1) && ggml_backend_sched_buffer_supported(sched, src, b)) { - n_supported++; - } - } - if (n_supported > n_supported_best) { - n_supported_best = n_supported; - *node_backend_id = b; - SET_CAUSE(node, "3.best"); - } - } - } - } else { - // assigned node: upgrade to higher prio backend if possible - for (int b = 0; b < *node_backend_id; b++) { - if (sched->bufts[b] == sched->bufts[*node_backend_id] && ggml_backend_supports_op(sched->backends[b], node)) { - bool supported = true; - for (int j = 0; j < GGML_MAX_SRC; j++) { - struct ggml_tensor * src = node->src[j]; - if (src == NULL) { - continue; - } - if (!ggml_backend_sched_buffer_supported(sched, src, b)) { - supported = false; - break; - } - } - if (supported) { - *node_backend_id = b; - SET_CAUSE(node, "3.upg"); - break; - } - } - } - } - } - - // pass 4: assign backends to remaining src from dst and view_src - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - int * cur_backend_id = &tensor_backend_id(node); - if (node->view_src != NULL && *cur_backend_id == -1) { - *cur_backend_id = tensor_backend_id(node->view_src); - SET_CAUSE(node, "4.vsrc"); - } - for (int j = 0; j < GGML_MAX_SRC; j++) { - struct ggml_tensor * src = node->src[j]; - if (src == NULL) { - continue; - } - int * src_backend_id = &tensor_backend_id(src); - if (*src_backend_id == -1) { - if (src->view_src != NULL) { - // views are always on the same backend as the source - *src_backend_id = tensor_backend_id(src->view_src); - SET_CAUSE(src, "4.vsrc"); - } else { - *src_backend_id = *cur_backend_id; - SET_CAUSE(src, "4.cur"); - } - } - } - } - - // pass 5: split graph, find tensors that need to be copied - { - int i_split = 0; - struct ggml_backend_sched_split * split = &sched->splits[0]; - // find the backend of the first split, skipping view ops - int i = 0; - for (; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - if (!ggml_is_view_op(node->op)) { - split->backend_id = tensor_backend_id(node); - break; - } - } - split->i_start = 0; - split->n_inputs = 0; - int cur_backend_id = split->backend_id; - for (; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - - if (ggml_is_view_op(node->op)) { - continue; - } - - const int node_backend_id = tensor_backend_id(node); - - assert(node_backend_id != -1); // all nodes should be assigned by now - - // check if we should start a new split based on the sources of the current node - bool need_new_split = false; - if (node_backend_id == cur_backend_id && split->n_inputs > 0) { - for (int j = 0; j < GGML_MAX_SRC; j++) { - struct ggml_tensor * src = node->src[j]; - if (src == NULL) { - continue; - } - // check if a weight is on a different backend - // by starting a new split, the memory of the previously offloaded weights can be reused - if (src->buffer != NULL && src->buffer->usage == GGML_BACKEND_BUFFER_USAGE_WEIGHTS) { - int src_backend_id = tensor_backend_id(src); - if (src_backend_id != cur_backend_id) { - need_new_split = true; - break; - } - } - // check if the split has too many inputs - // FIXME: count the number of inputs instead of only checking when full - if (split->n_inputs == GGML_SCHED_MAX_SPLIT_INPUTS) { - const size_t id = hash_id(src); - int src_backend_id = sched->hv_tensor_backend_ids[id]; - bool supported = ggml_backend_sched_buffer_supported(sched, src, cur_backend_id); - if (src_backend_id != cur_backend_id && tensor_id_copy(id, cur_backend_id, 0) == NULL && !supported) { - //printf("starting new split because of too many inputs: node %s, input %s\n", node->name, src->name); - need_new_split = true; - break; - } - } - } - } - - if (node_backend_id != cur_backend_id || need_new_split) { - split->i_end = i; - i_split++; - if (i_split >= sched->splits_capacity) { - sched->splits_capacity *= 2; - sched->splits = realloc(sched->splits, sched->splits_capacity * sizeof(struct ggml_backend_sched_split)); - GGML_ASSERT(sched->splits != NULL); - } - split = &sched->splits[i_split]; - split->backend_id = node_backend_id; - split->i_start = i; - split->n_inputs = 0; - cur_backend_id = node_backend_id; - } - - // find inputs that are not on the same backend - for (int j = 0; j < GGML_MAX_SRC; j++) { - struct ggml_tensor * src = node->src[j]; - if (src == NULL) { - continue; - } - - size_t src_id = hash_id(src); - const int src_backend_id = sched->hv_tensor_backend_ids[src_id]; - assert(src_backend_id != -1); // all inputs should be assigned by now - - if (src->flags & GGML_TENSOR_FLAG_INPUT && sched->n_copies > 1) { - if (tensor_id_copy(src_id, src_backend_id, 0) == NULL) { - ggml_backend_t backend = sched->backends[src_backend_id]; - for (int c = 0; c < sched->n_copies; c++) { - struct ggml_tensor * tensor_copy; - if (c == sched->cur_copy) { - tensor_copy = src; // use the original tensor as the current copy - } else { - tensor_copy = ggml_dup_tensor_layout(sched->ctx, src); - ggml_format_name(tensor_copy, "%s#%s#%d", ggml_backend_name(backend), src->name, c); - } - if (sched->n_copies > 1) { - ggml_set_input(tensor_copy); - ggml_set_output(tensor_copy); // prevent ggml-alloc from overwriting the tensor - } - tensor_id_copy(src_id, src_backend_id, c) = tensor_copy; - SET_CAUSE(tensor_copy, "4.cpy"); - } - int n_graph_inputs = sched->n_graph_inputs++; - GGML_ASSERT(n_graph_inputs < GGML_SCHED_MAX_SPLIT_INPUTS); - sched->graph_inputs[n_graph_inputs] = src; - } - } - - if (src_backend_id != cur_backend_id && !ggml_backend_sched_buffer_supported(sched, src, cur_backend_id)) { - // create a copy of the input in the split's backend - if (tensor_id_copy(src_id, cur_backend_id, 0) == NULL) { - ggml_backend_t backend = sched->backends[cur_backend_id]; - for (int c = 0; c < sched->n_copies; c++) { - struct ggml_tensor * tensor_copy = ggml_dup_tensor_layout(sched->ctx, src); - ggml_format_name(tensor_copy, "%s#%s#%d", ggml_backend_name(backend), src->name, c); - if (sched->n_copies > 1) { - ggml_set_input(tensor_copy); - ggml_set_output(tensor_copy); // prevent ggml-alloc from overwriting the tensor - } - tensor_id_copy(src_id, cur_backend_id, c) = tensor_copy; - SET_CAUSE(tensor_copy, "4.cpy"); - } - int n_inputs = split->n_inputs++; - GGML_ASSERT(n_inputs < GGML_SCHED_MAX_SPLIT_INPUTS); - split->inputs[n_inputs] = src; - } - node->src[j] = tensor_id_copy(src_id, cur_backend_id, sched->cur_copy); - } - } - } - split->i_end = graph->n_nodes; - sched->n_splits = i_split + 1; - } - - if (sched->debug) { - ggml_backend_sched_print_assignments(sched, graph); - } - - // swap node_backend_ids and leaf _backend_ids with prevs - { - int * tmp = sched->node_backend_ids; - sched->node_backend_ids = sched->prev_node_backend_ids; - sched->prev_node_backend_ids = tmp; - - tmp = sched->leaf_backend_ids; - sched->leaf_backend_ids = sched->prev_leaf_backend_ids; - sched->prev_leaf_backend_ids = tmp; - } - - int graph_size = MAX(graph->n_nodes, graph->n_leafs) + sched->n_splits*GGML_SCHED_MAX_SPLIT_INPUTS*2*sched->n_copies; - if (sched->graph.size < graph_size) { - sched->graph.size = graph_size; - sched->graph.nodes = realloc(sched->graph.nodes, graph_size * sizeof(struct ggml_tensor *)); - sched->graph.leafs = realloc(sched->graph.leafs, graph_size * sizeof(struct ggml_tensor *)); - GGML_ASSERT(sched->graph.nodes != NULL); - GGML_ASSERT(sched->graph.leafs != NULL); - } - sched->graph.n_nodes = 0; - sched->graph.n_leafs = 0; - - struct ggml_cgraph * graph_copy = &sched->graph; - - for (int i = 0; i < sched->n_splits; i++) { - struct ggml_backend_sched_split * split = &sched->splits[i]; - split->graph = ggml_graph_view(graph, split->i_start, split->i_end); - - // add inputs to the graph copy so that they are allocated by ggml-alloc at the start of the split - for (int j = 0; j < split->n_inputs; j++) { - assert(graph_copy->size > (graph_copy->n_nodes + 1)); - - struct ggml_tensor * input = split->inputs[j]; - const size_t input_id = hash_id(input); - struct ggml_tensor * input_cpy = tensor_id_copy(input_id, split->backend_id, sched->cur_copy); - - // add a dependency to the input source so that it is not freed before the copy is done - struct ggml_tensor * input_dep = ggml_view_tensor(sched->ctx, input); - input_dep->src[0] = input; - sched->node_backend_ids[graph_copy->n_nodes] = sched->hv_tensor_backend_ids[input_id]; - graph_copy->nodes[graph_copy->n_nodes++] = input_dep; - - // add a dependency to the input copy so that it is allocated at the start of the split - sched->node_backend_ids[graph_copy->n_nodes] = split->backend_id; - graph_copy->nodes[graph_copy->n_nodes++] = input_cpy; - } - - for (int j = split->i_start; j < split->i_end; j++) { - assert(graph_copy->size > graph_copy->n_nodes); - sched->node_backend_ids[graph_copy->n_nodes] = tensor_backend_id(graph->nodes[j]); - graph_copy->nodes[graph_copy->n_nodes++] = graph->nodes[j]; - } - } - - if (sched->n_copies > 1) { - // add input copies as leafs so that they are allocated first - for (int i = 0; i < sched->n_graph_inputs; i++) { - struct ggml_tensor * input = sched->graph_inputs[i]; - size_t id = hash_id(input); - int backend_id = tensor_backend_id(input); - for (int c = 0; c < sched->n_copies; c++) { - struct ggml_tensor * input_cpy = tensor_id_copy(id, backend_id, c); - sched->leaf_backend_ids[graph_copy->n_leafs] = backend_id; - assert(graph_copy->size > graph_copy->n_leafs); - graph_copy->leafs[graph_copy->n_leafs++] = input_cpy; - } - } - - for (int i = 0; i < sched->n_splits; i++) { - struct ggml_backend_sched_split * split = &sched->splits[i]; - int backend_id = split->backend_id; - for (int j = 0; j < split->n_inputs; j++) { - struct ggml_tensor * input = split->inputs[j]; - size_t id = hash_id(input); - for (int c = 0; c < sched->n_copies; c++) { - struct ggml_tensor * input_cpy = tensor_id_copy(id, backend_id, c); - sched->leaf_backend_ids[graph_copy->n_leafs] = backend_id; - assert(graph_copy->size > graph_copy->n_leafs); - graph_copy->leafs[graph_copy->n_leafs++] = input_cpy; - } - } - } - } - - // add leafs from the original graph - for (int i = 0; i < graph->n_leafs; i++) { - struct ggml_tensor * leaf = graph->leafs[i]; - sched->leaf_backend_ids[graph_copy->n_leafs] = tensor_backend_id(leaf); - assert(graph_copy->size > graph_copy->n_leafs); - graph_copy->leafs[graph_copy->n_leafs++] = leaf; - } -} - -static bool ggml_backend_sched_alloc_splits(ggml_backend_sched_t sched) { - bool backend_ids_changed = false; - for (int i = 0; i < sched->graph.n_nodes; i++) { - if (sched->node_backend_ids[i] != sched->prev_node_backend_ids[i] && - sched->bufts[sched->node_backend_ids[i]] != sched->bufts[sched->prev_node_backend_ids[i]]) { - backend_ids_changed = true; - break; - } - } - if (!backend_ids_changed) { - for (int i = 0; i < sched->graph.n_leafs; i++) { - if (sched->leaf_backend_ids[i] != sched->prev_leaf_backend_ids[i] && - sched->bufts[sched->leaf_backend_ids[i]] != sched->bufts[sched->prev_leaf_backend_ids[i]]) { - backend_ids_changed = true; - break; - } - } - } - - // allocate graph - if (backend_ids_changed || !ggml_gallocr_alloc_graph(sched->galloc, &sched->graph)) { - // the re-allocation may cause the split inputs to be moved to a different address - ggml_backend_sched_synchronize(sched); -#ifndef NDEBUG - fprintf(stderr, "%s: failed to allocate graph, reserving (backend_ids_changed = %d)\n", __func__, backend_ids_changed); -#endif - ggml_gallocr_reserve_n(sched->galloc, &sched->graph, sched->node_backend_ids, sched->leaf_backend_ids); - if (!ggml_gallocr_alloc_graph(sched->galloc, &sched->graph)) { - fprintf(stderr, "%s: failed to allocate graph\n", __func__); - return false; - } - } - - return true; -} - -static enum ggml_status ggml_backend_sched_compute_splits(ggml_backend_sched_t sched) { - struct ggml_backend_sched_split * splits = sched->splits; - - for (int i = 0; i < sched->n_splits; i++) { - struct ggml_backend_sched_split * split = &splits[i]; - int split_backend_id = split->backend_id; - ggml_backend_t split_backend = sched->backends[split_backend_id]; - - // copy the input tensors to the split backend - for (int j = 0; j < split->n_inputs; j++) { - ggml_backend_t input_backend = ggml_backend_sched_get_tensor_backend(sched, split->inputs[j]); - struct ggml_tensor * input = split->inputs[j]; - struct ggml_tensor * input_cpy = tensor_copy(input, split_backend_id, sched->cur_copy); - - if (input->flags & GGML_TENSOR_FLAG_INPUT) { - // inputs from the user must be copied immediately to prevent the user overwriting the data before the copy is done - if (sched->events[split_backend_id][sched->cur_copy] != NULL) { - ggml_backend_event_synchronize(sched->events[split_backend_id][sched->cur_copy]); - } else { - ggml_backend_synchronize(split_backend); - } - ggml_backend_tensor_copy(input, input_cpy); - } else { - // wait for the split backend to finish using the input before overwriting it - if (sched->events[split_backend_id][sched->cur_copy] != NULL) { - ggml_backend_event_wait(split_backend, sched->events[split_backend_id][sched->cur_copy]); - } else { - ggml_backend_synchronize(split_backend); - } - // try async copy, but if not possible, we can still use a sync copy without synchronizing the dst backend, since we handle the synchronization here with multiple copies and events - // TODO: add public function to facilitate this, since applications do not have direct access to the backend interface - if (!split_backend->iface.cpy_tensor_async || !split_backend->iface.cpy_tensor_async(input_backend, split_backend, input, input_cpy)) { - ggml_backend_synchronize(input_backend); - if (sched->events[split_backend_id][sched->cur_copy] != NULL) { - ggml_backend_event_synchronize(sched->events[split_backend_id][sched->cur_copy]); - } else { - ggml_backend_synchronize(split_backend); - } - ggml_backend_tensor_copy(input, input_cpy); - } - } - } - - if (!sched->callback_eval) { - enum ggml_status ec = ggml_backend_graph_compute_async(split_backend, &split->graph); - if (ec != GGML_STATUS_SUCCESS) { - return ec; - } - } else { - // similar to ggml_backend_compare_graph_backend - for (int j0 = 0; j0 < split->graph.n_nodes; j0++) { - struct ggml_tensor * t = split->graph.nodes[j0]; - - // check if the user needs data from this node - bool need = sched->callback_eval(t, true, sched->callback_eval_user_data); - - int j1 = j0; - - // determine the range [j0, j1] of nodes that can be computed together - while (!need && j1 < split->graph.n_nodes - 1) { - t = split->graph.nodes[++j1]; - need = sched->callback_eval(t, true, sched->callback_eval_user_data); - } - - struct ggml_cgraph gv = ggml_graph_view(&split->graph, j0, j1 + 1); - - enum ggml_status ec = ggml_backend_graph_compute_async(split_backend, &gv); - if (ec != GGML_STATUS_SUCCESS) { - return ec; - } - - // TODO: pass backend to the callback, then the user can decide if they want to synchronize - ggml_backend_synchronize(split_backend); - - if (need && !sched->callback_eval(t, false, sched->callback_eval_user_data)) { - break; - } - - j0 = j1; - } - } - - // record the event of this copy - if (split->n_inputs > 0) { - if (sched->events[split_backend_id][sched->cur_copy] != NULL) { - ggml_backend_event_record(sched->events[split_backend_id][sched->cur_copy]); - } - } - } - - sched->cur_copy = (sched->cur_copy + 1) % sched->n_copies; - - return GGML_STATUS_SUCCESS; -} - -ggml_backend_sched_t ggml_backend_sched_new( - ggml_backend_t * backends, - ggml_backend_buffer_type_t * bufts, - int n_backends, - size_t graph_size, - bool parallel) { - GGML_ASSERT(n_backends > 0); - GGML_ASSERT(n_backends <= GGML_SCHED_MAX_BACKENDS); - GGML_ASSERT(ggml_backend_is_cpu(backends[n_backends - 1])); // last backend must be CPU - - struct ggml_backend_sched * sched = calloc(1, sizeof(struct ggml_backend_sched)); - - sched->debug = getenv("GGML_SCHED_DEBUG") != NULL; - sched->n_backends = n_backends; - sched->n_copies = parallel ? GGML_SCHED_MAX_COPIES : 1; - - // initialize hash table - // FIXME: needs to be size*2 to account for leafs (do it in graph_split instead) - sched->hash_set = ggml_hash_set_new(graph_size); - sched->hv_tensor_backend_ids = malloc(sched->hash_set.size * sizeof(sched->hv_tensor_backend_ids[0])); - sched->hv_tensor_copies = malloc(sched->hash_set.size * sched->n_backends * sched->n_copies * sizeof(struct ggml_tensor *)); - - const size_t ggml_sched_max_splits = graph_size; // at most there is one split for each node in the graph - const size_t nodes_size = graph_size + ggml_sched_max_splits*GGML_SCHED_MAX_SPLIT_INPUTS*2; - sched->node_backend_ids = calloc(nodes_size, sizeof(sched->node_backend_ids[0])); - sched->leaf_backend_ids = calloc(nodes_size, sizeof(sched->leaf_backend_ids[0])); - sched->prev_node_backend_ids = calloc(nodes_size, sizeof(sched->prev_node_backend_ids[0])); - sched->prev_leaf_backend_ids = calloc(nodes_size, sizeof(sched->prev_leaf_backend_ids[0])); - - sched->context_buffer_size = ggml_sched_max_splits*GGML_SCHED_MAX_SPLIT_INPUTS*2*sizeof(struct ggml_tensor) + ggml_graph_overhead_custom(graph_size, false); - sched->context_buffer = malloc(sched->context_buffer_size); - - const int initial_splits_capacity = 16; - sched->splits = calloc(initial_splits_capacity, sizeof(sched->splits[0])); - sched->splits_capacity = initial_splits_capacity; - - for (int b = 0; b < n_backends; b++) { - sched->backends[b] = backends[b]; - sched->bufts[b] = bufts ? bufts[b] : ggml_backend_get_default_buffer_type(backends[b]); - GGML_ASSERT(ggml_backend_supports_buft(backends[b], sched->bufts[b])); - if (sched->n_copies > 1) { - for (int c = 0; c < sched->n_copies; c++) { - sched->events[b][c] = ggml_backend_event_new(backends[b]); - } - } - } - - sched->galloc = ggml_gallocr_new_n(sched->bufts, n_backends); - - ggml_backend_sched_reset(sched); - - return sched; -} - -void ggml_backend_sched_free(ggml_backend_sched_t sched) { - if (sched == NULL) { - return; - } - for (int b = 0; b < sched->n_backends; b++) { - for (int c = 0; c < sched->n_copies; c++) { - ggml_backend_event_free(sched->events[b][c]); - } - } - ggml_gallocr_free(sched->galloc); - ggml_free(sched->ctx); - ggml_hash_set_free(&sched->hash_set); - free(sched->splits); - free(sched->hv_tensor_backend_ids); - free(sched->hv_tensor_copies); - free(sched->node_backend_ids); - free(sched->leaf_backend_ids); - free(sched->prev_node_backend_ids); - free(sched->prev_leaf_backend_ids); - free(sched->context_buffer); - free(sched->graph.nodes); - free(sched->graph.leafs); - free(sched); -} - -void ggml_backend_sched_reset(ggml_backend_sched_t sched) { - // reset state for the next run - if (!sched->is_reset) { - ggml_hash_set_reset(&sched->hash_set); - memset(sched->hv_tensor_backend_ids, -1, sched->hash_set.size * sizeof(sched->hv_tensor_backend_ids[0])); - memset(sched->hv_tensor_copies, 0, sched->hash_set.size * sched->n_backends * sched->n_copies * sizeof(struct ggml_tensor *)); - sched->is_reset = true; - } - sched->is_alloc = false; -} - -bool ggml_backend_sched_reserve(ggml_backend_sched_t sched, struct ggml_cgraph * measure_graph) { - GGML_ASSERT((int)sched->hash_set.size >= measure_graph->n_nodes + measure_graph->n_leafs); - - ggml_backend_sched_split_graph(sched, measure_graph); - - if (!ggml_gallocr_reserve_n(sched->galloc, &sched->graph, sched->node_backend_ids, sched->leaf_backend_ids)) { - return false; - } - - ggml_backend_sched_reset(sched); - ggml_backend_sched_synchronize(sched); - - return true; -} - -bool ggml_backend_sched_alloc_graph(ggml_backend_sched_t sched, struct ggml_cgraph * graph) { - GGML_ASSERT((int)sched->hash_set.size >= graph->n_nodes + graph->n_leafs); - - ggml_backend_sched_split_graph(sched, graph); - - - if (!ggml_backend_sched_alloc_splits(sched)) { - return false; - } - - sched->is_alloc = true; - - return true; -} - -enum ggml_status ggml_backend_sched_graph_compute(ggml_backend_sched_t sched, struct ggml_cgraph * graph) { - enum ggml_status err = ggml_backend_sched_graph_compute_async(sched, graph); - ggml_backend_sched_synchronize(sched); - return err; -} - -enum ggml_status ggml_backend_sched_graph_compute_async(ggml_backend_sched_t sched, struct ggml_cgraph * graph) { - if (!sched->is_reset && !sched->is_alloc) { - ggml_backend_sched_reset(sched); - } - - if (!sched->is_alloc) { - if (!ggml_backend_sched_alloc_graph(sched, graph)) { - return GGML_STATUS_ALLOC_FAILED; - } - } - - return ggml_backend_sched_compute_splits(sched); -} - -void ggml_backend_sched_synchronize(ggml_backend_sched_t sched) { - for (int i = 0; i < sched->n_backends; i++) { - ggml_backend_synchronize(sched->backends[i]); - } -} - -void ggml_backend_sched_set_eval_callback(ggml_backend_sched_t sched, ggml_backend_sched_eval_callback callback, void * user_data) { - sched->callback_eval = callback; - sched->callback_eval_user_data = user_data; -} - -int ggml_backend_sched_get_n_splits(ggml_backend_sched_t sched) { - return sched->n_splits; -} - -int ggml_backend_sched_get_n_copies(ggml_backend_sched_t sched) { - return sched->n_copies; -} - -int ggml_backend_sched_get_n_backends(ggml_backend_sched_t sched) { - return sched->n_backends; -} - -ggml_backend_t ggml_backend_sched_get_backend(ggml_backend_sched_t sched, int i) { - GGML_ASSERT(i >= 0 && i < sched->n_backends); - return sched->backends[i]; -} - -size_t ggml_backend_sched_get_buffer_size(ggml_backend_sched_t sched, ggml_backend_t backend) { - int backend_index = ggml_backend_sched_backend_id(sched, backend); - GGML_ASSERT(backend_index >= 0 && backend_index < sched->n_backends); - - return ggml_gallocr_get_buffer_size(sched->galloc, backend_index); -} - -void ggml_backend_sched_set_tensor_backend(ggml_backend_sched_t sched, struct ggml_tensor * node, ggml_backend_t backend) { - int backend_index = ggml_backend_sched_backend_id(sched, backend); - GGML_ASSERT(backend_index >= 0 && backend_index < sched->n_backends); - tensor_backend_id(node) = backend_index; - SET_CAUSE(node, "usr"); - sched->is_reset = false; -} - -ggml_backend_t ggml_backend_sched_get_tensor_backend(ggml_backend_sched_t sched, struct ggml_tensor * node) { - int backend_index = tensor_backend_id(node); - if (backend_index == -1) { - return NULL; - } - return sched->backends[backend_index]; -} - -// utils - -void ggml_backend_view_init(struct ggml_tensor * tensor) { - GGML_ASSERT(tensor->buffer == NULL); - GGML_ASSERT(tensor->view_src != NULL); - GGML_ASSERT(tensor->view_src->buffer != NULL); - GGML_ASSERT(tensor->view_src->data != NULL); - - tensor->buffer = tensor->view_src->buffer; - tensor->data = (char *)tensor->view_src->data + tensor->view_offs; - ggml_backend_buffer_init_tensor(tensor->buffer, tensor); -} - -void ggml_backend_tensor_alloc(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, void * addr) { - GGML_ASSERT(tensor->buffer == NULL); - GGML_ASSERT(tensor->data == NULL); - GGML_ASSERT(tensor->view_src == NULL); - GGML_ASSERT(addr >= ggml_backend_buffer_get_base(buffer)); - GGML_ASSERT((char *)addr + ggml_backend_buffer_get_alloc_size(buffer, tensor) <= - (char *)ggml_backend_buffer_get_base(buffer) + ggml_backend_buffer_get_size(buffer)); - - tensor->buffer = buffer; - tensor->data = addr; - ggml_backend_buffer_init_tensor(buffer, tensor); -} - -static struct ggml_tensor * graph_copy_dup_tensor(struct ggml_hash_set hash_set, struct ggml_tensor ** node_copies, - struct ggml_context * ctx_allocated, struct ggml_context * ctx_unallocated, struct ggml_tensor * src) { - - GGML_ASSERT(src != NULL); - GGML_ASSERT(src->data && "graph must be allocated"); - - size_t id = ggml_hash_insert(&hash_set, src); - if (id == GGML_HASHSET_ALREADY_EXISTS) { - return node_copies[ggml_hash_find(&hash_set, src)]; - } - - struct ggml_tensor * dst = ggml_dup_tensor_layout(src->data && !src->view_src ? ctx_allocated : ctx_unallocated, src); - if (src->view_src != NULL) { - dst->view_src = graph_copy_dup_tensor(hash_set, node_copies, ctx_allocated, ctx_unallocated, src->view_src); - dst->view_offs = src->view_offs; - } - dst->op = src->op; - memcpy(dst->op_params, src->op_params, sizeof(dst->op_params)); - ggml_set_name(dst, src->name); - - // copy src - for (int i = 0; i < GGML_MAX_SRC; i++) { - struct ggml_tensor * s = src->src[i]; - if (s == NULL) { - continue; - } - dst->src[i] = graph_copy_dup_tensor(hash_set, node_copies, ctx_allocated, ctx_unallocated, s); - } - - node_copies[id] = dst; - return dst; -} - -static void graph_copy_init_tensor(struct ggml_hash_set * hash_set, struct ggml_tensor ** node_copies, bool * node_init, struct ggml_tensor * src) { - size_t id = ggml_hash_find(hash_set, src); - if (node_init[id]) { - return; - } - node_init[id] = true; - - struct ggml_tensor * dst = node_copies[id]; - if (dst->view_src != NULL) { - graph_copy_init_tensor(hash_set, node_copies, node_init, src->view_src); - ggml_backend_view_init(dst); - } - else { - ggml_backend_tensor_copy(src, dst); - } - - // init src - for (int i = 0; i < GGML_MAX_SRC; i++) { - struct ggml_tensor * s = src->src[i]; - if (s == NULL) { - continue; - } - graph_copy_init_tensor(hash_set, node_copies, node_init, s); - } -} - -struct ggml_backend_graph_copy ggml_backend_graph_copy(ggml_backend_t backend, struct ggml_cgraph * graph) { - struct ggml_hash_set hash_set = ggml_hash_set_new(graph->visited_hash_set.size); - struct ggml_tensor ** node_copies = calloc(hash_set.size, sizeof(node_copies[0])); // NOLINT - bool * node_init = calloc(hash_set.size, sizeof(node_init[0])); - - struct ggml_init_params params = { - /* .mem_size = */ ggml_tensor_overhead()*hash_set.size + ggml_graph_overhead_custom(graph->size, false), - /* .mem_buffer = */ NULL, - /* .no_alloc = */ true - }; - - struct ggml_context * ctx_allocated = ggml_init(params); - struct ggml_context * ctx_unallocated = ggml_init(params); - - if (ctx_allocated == NULL || ctx_unallocated == NULL) { - fprintf(stderr, "failed to allocate context for graph copy\n"); - ggml_hash_set_free(&hash_set); - free(node_copies); - free(node_init); - ggml_free(ctx_allocated); - ggml_free(ctx_unallocated); - return (struct ggml_backend_graph_copy) { - /* .buffer = */ NULL, - /* .ctx_allocated = */ NULL, - /* .ctx_unallocated = */ NULL, - /* .graph = */ NULL, - }; - } - - // dup nodes - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - graph_copy_dup_tensor(hash_set, node_copies, ctx_allocated, ctx_unallocated, node); - } - - // allocate nodes - ggml_backend_buffer_t buffer = ggml_backend_alloc_ctx_tensors(ctx_allocated, backend); - if (buffer == NULL) { - fprintf(stderr, "failed to allocate buffer for graph copy\n"); - ggml_hash_set_free(&hash_set); - free(node_copies); - free(node_init); - ggml_free(ctx_allocated); - ggml_free(ctx_unallocated); - return (struct ggml_backend_graph_copy) { - /* .buffer = */ NULL, - /* .ctx_allocated = */ NULL, - /* .ctx_unallocated = */ NULL, - /* .graph = */ NULL, - }; - } - - //printf("copy buffer size: %zu MB\n", ggml_backend_buffer_get_size(buffer) / 1024 / 1024); - - // copy data and init views - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - graph_copy_init_tensor(&hash_set, node_copies, node_init, node); - } - - // build graph copy - struct ggml_cgraph * graph_copy = ggml_new_graph_custom(ctx_allocated, graph->size, false); - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - struct ggml_tensor * node_copy = node_copies[ggml_hash_find(&hash_set, node)]; - graph_copy->nodes[i] = node_copy; - } - graph_copy->n_nodes = graph->n_nodes; - - ggml_hash_set_free(&hash_set); - free(node_copies); - free(node_init); - - return (struct ggml_backend_graph_copy) { - /* .buffer = */ buffer, - /* .ctx_allocated = */ ctx_allocated, - /* .ctx_unallocated = */ ctx_unallocated, - /* .graph = */ graph_copy, - }; -} - -void ggml_backend_graph_copy_free(struct ggml_backend_graph_copy copy) { - ggml_backend_buffer_free(copy.buffer); - ggml_free(copy.ctx_allocated); - ggml_free(copy.ctx_unallocated); -} - -bool ggml_backend_compare_graph_backend(ggml_backend_t backend1, ggml_backend_t backend2, struct ggml_cgraph * graph, ggml_backend_eval_callback callback, void * user_data) { - struct ggml_backend_graph_copy copy = ggml_backend_graph_copy(backend2, graph); - if (copy.buffer == NULL) { - return false; - } - - struct ggml_cgraph * g1 = graph; - struct ggml_cgraph * g2 = copy.graph; - - assert(g1->n_nodes == g2->n_nodes); - - for (int i = 0; i < g1->n_nodes; i++) { - //printf("eval %d/%d\n", i, g1->n_nodes); - struct ggml_tensor * t1 = g1->nodes[i]; - struct ggml_tensor * t2 = g2->nodes[i]; - - assert(t1->op == t2->op && ggml_are_same_layout(t1, t2)); - - struct ggml_cgraph g1v = ggml_graph_view(g1, i, i + 1); - struct ggml_cgraph g2v = ggml_graph_view(g2, i, i + 1); - - ggml_backend_graph_compute(backend1, &g1v); - ggml_backend_graph_compute(backend2, &g2v); - - if (ggml_is_view_op(t1->op)) { - continue; - } - - // compare results, calculate rms etc - if (!callback(i, t1, t2, user_data)) { - break; - } - } - - ggml_backend_graph_copy_free(copy); - - return true; -}