diff --git a/ggml/include/ggml-backend.h b/ggml/include/ggml-backend.h index b096aaed6..864bcbded 100644 --- a/ggml/include/ggml-backend.h +++ b/ggml/include/ggml-backend.h @@ -164,7 +164,7 @@ extern "C" { GGML_API size_t ggml_backend_reg_dev_count(ggml_backend_reg_t reg); GGML_API ggml_backend_dev_t ggml_backend_reg_dev_get(ggml_backend_reg_t reg, size_t index); GGML_API void * ggml_backend_reg_get_proc_address(ggml_backend_reg_t reg, const char * name); - GGML_API void ggml_backend_reg_set_log_callback(ggml_backend_reg_t reg, ggml_log_callback log_callback, void * user_data); + // Functions that may be obtained using ggml_backend_reg_get_proc_address typedef ggml_backend_buffer_type_t (*ggml_backend_split_buffer_type_t)(const float *); @@ -184,9 +184,6 @@ extern "C" { GGML_API ggml_backend_dev_t ggml_backend_dev_by_name(const char * name); GGML_API ggml_backend_dev_t ggml_backend_dev_by_type(enum ggml_backend_dev_type type); - // Set the log callback for all registered backends - GGML_API void ggml_backend_set_log_callback(ggml_log_callback log_callback, void * user_data); - // Direct backend (stream) initialization // = ggml_backend_dev_init(ggml_backend_dev_by_name(name), params) GGML_API ggml_backend_t ggml_backend_init_by_name(const char * name, const char * params); diff --git a/ggml/include/ggml-cann.h b/ggml/include/ggml-cann.h index ba9ff2292..95bdaf10d 100644 --- a/ggml/include/ggml-cann.h +++ b/ggml/include/ggml-cann.h @@ -116,17 +116,6 @@ GGML_API void ggml_backend_cann_get_device_memory(int32_t device, size_t* free, size_t* total); -/** - * @brief Set the logging callback for GGML. - * - * This function sets the logging callback and user data for logging. - * - * @param log_callback The logging callback to set. - * @param user_data User data to pass to the logging callback. - */ -GGML_API void ggml_backend_cann_log_set_callback(ggml_log_callback log_callback, - void* user_data); - #ifdef __cplusplus } #endif diff --git a/ggml/include/ggml-cuda.h b/ggml/include/ggml-cuda.h index a8feddc94..f44d8f4e6 100644 --- a/ggml/include/ggml-cuda.h +++ b/ggml/include/ggml-cuda.h @@ -40,8 +40,6 @@ GGML_API void ggml_backend_cuda_get_device_memory(int device, size_t * free, siz GGML_API bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size); GGML_API void ggml_backend_cuda_unregister_host_buffer(void * buffer); -GGML_API void ggml_backend_cuda_log_set_callback(ggml_log_callback log_callback, void * user_data); - GGML_API ggml_backend_reg_t ggml_backend_cuda_reg(void); #ifdef __cplusplus diff --git a/ggml/include/ggml-metal.h b/ggml/include/ggml-metal.h index 55e6ecd84..c3ec572b2 100644 --- a/ggml/include/ggml-metal.h +++ b/ggml/include/ggml-metal.h @@ -39,8 +39,6 @@ extern "C" { // user-code should use only these functions // -GGML_API void ggml_backend_metal_log_set_callback(ggml_log_callback log_callback, void * user_data); - GGML_API ggml_backend_t ggml_backend_metal_init(void); GGML_API bool ggml_backend_is_metal(ggml_backend_t backend); diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h index 969be3e94..1b4006b62 100644 --- a/ggml/include/ggml.h +++ b/ggml/include/ggml.h @@ -2167,6 +2167,10 @@ extern "C" { typedef void (*ggml_opt_callback)(void * data, int accum_step, float * sched, bool * cancel); typedef void (*ggml_log_callback)(enum ggml_log_level level, const char * text, void * user_data); + // Set callback for all future logging events. + // If this is not called, or NULL is supplied, everything is output on stderr. + GGML_API void ggml_log_set(ggml_log_callback log_callback, void * user_data); + // optimization parameters // // see ggml.c (ggml_opt_default_params) for default values diff --git a/ggml/src/ggml-backend-impl.h b/ggml/src/ggml-backend-impl.h index 470c922fe..ba2e26999 100644 --- a/ggml/src/ggml-backend-impl.h +++ b/ggml/src/ggml-backend-impl.h @@ -215,9 +215,6 @@ extern "C" { // (optional) get a pointer to a function in the backend // backends can add custom functions that are not part of the standard ggml-backend interface void * (*get_proc_address)(ggml_backend_reg_t reg, const char * name); - - // (optional) set the log callback for the backend - void (*set_log_callback)(ggml_backend_reg_t reg, ggml_log_callback log_callback, void * user_data); }; struct ggml_backend_reg { diff --git a/ggml/src/ggml-backend.cpp b/ggml/src/ggml-backend.cpp index 73a2b24f8..3300ddb52 100644 --- a/ggml/src/ggml-backend.cpp +++ b/ggml/src/ggml-backend.cpp @@ -505,12 +505,6 @@ void * ggml_backend_reg_get_proc_address(ggml_backend_reg_t reg, const char * na return reg->iface.get_proc_address(reg, name); } -void ggml_backend_reg_set_log_callback(ggml_backend_reg_t reg, ggml_log_callback log_callback, void * user_data) { - if (reg->iface.set_log_callback) { - reg->iface.set_log_callback(reg, log_callback, user_data); - } -} - // Backend registry #ifdef GGML_USE_CUDA @@ -614,13 +608,6 @@ ggml_backend_dev_t ggml_backend_dev_by_type(enum ggml_backend_dev_type type) { return NULL; } -void ggml_backend_set_log_callback(ggml_log_callback log_callback, void * user_data) { - for (size_t i = 0; i < ggml_backend_reg_count(); i++) { - ggml_backend_reg_t reg = ggml_backend_reg_get(i); - ggml_backend_reg_set_log_callback(reg, log_callback, user_data); - } -} - // Convenience functions ggml_backend_t ggml_backend_init_by_name(const char * name, const char * params) { ggml_backend_dev_t dev = ggml_backend_dev_by_name(name); @@ -1161,7 +1148,6 @@ static const struct ggml_backend_reg_i ggml_backend_cpu_reg_i = { /* .get_device_count = */ ggml_backend_cpu_reg_get_device_count, /* .get_device = */ ggml_backend_cpu_reg_get_device, /* .get_proc_address = */ NULL, - /* .set_log_callback = */ NULL, }; ggml_backend_reg_t ggml_backend_cpu_reg(void) { diff --git a/ggml/src/ggml-cann.cpp b/ggml/src/ggml-cann.cpp index 63ad0b878..db5f8f186 100644 --- a/ggml/src/ggml-cann.cpp +++ b/ggml/src/ggml-cann.cpp @@ -39,69 +39,6 @@ #include "ggml-common.h" -/** - * @brief Default logging callback for GGML. - * - * This function is the default logging callback that logs messages to stderr. - * - * @param level The log level. - * @param msg The log message. - * @param user_data User data passed to the callback. - */ -static void ggml_cann_default_log_callback(enum ggml_log_level level, - const char* msg, void* user_data) { - GGML_UNUSED(level); - GGML_UNUSED(user_data); - fprintf(stderr, "%s", msg); -} - -ggml_log_callback ggml_cann_log_callback = ggml_cann_default_log_callback; -void* ggml_cann_log_user_data = NULL; - -GGML_API void ggml_backend_cann_log_set_callback(ggml_log_callback log_callback, - void* user_data) { - ggml_cann_log_callback = log_callback; - ggml_cann_log_user_data = user_data; -} - -#define GGML_CANN_LOG_INFO(...) ggml_cann_log(GGML_LOG_LEVEL_INFO, __VA_ARGS__) -#define GGML_CANN_LOG_WARN(...) ggml_cann_log(GGML_LOG_LEVEL_WARN, __VA_ARGS__) -#define GGML_CANN_LOG_ERROR(...) \ - ggml_cann_log(GGML_LOG_LEVEL_ERROR, __VA_ARGS__) - -GGML_ATTRIBUTE_FORMAT(2, 3) - -/** - * @brief Log a message using the current logging callback. - * - * This function formats a log message and passes it to the current logging - * callback. - * - * @param level The log level. - * @param format The format string for the log message. - * @param ... The arguments for the format string. - */ -static void ggml_cann_log(enum ggml_log_level level, const char* format, ...) { - if (ggml_cann_log_callback != NULL) { - va_list args; - va_start(args, format); - char buffer[128]; - int len = vsnprintf(buffer, 128, format, args); - if (len < 128) { - ggml_cann_log_callback(level, buffer, ggml_cann_log_user_data); - } else { - // vsnprintf adds a null terminator - std::vector buffer2(len + 1); - va_end(args); - va_start(args, format); - vsnprintf(&buffer2[0], buffer2.size(), format, args); - ggml_cann_log_callback(level, buffer2.data(), - ggml_cann_log_user_data); - } - va_end(args); - } -} - /** * @brief Handles CANN errors by printing an error message and aborting. * @@ -116,10 +53,10 @@ static void ggml_cann_log(enum ggml_log_level level, const char* format, ...) { int32_t id = -1; aclrtGetDevice(&id); - GGML_CANN_LOG_ERROR("CANN error: %s\n", msg); - GGML_CANN_LOG_ERROR(" current device: %d, in function %s at %s:%d\n", id, func, + GGML_LOG_ERROR("CANN error: %s\n", msg); + GGML_LOG_ERROR(" current device: %d, in function %s at %s:%d\n", id, func, file, line); - GGML_CANN_LOG_ERROR(" %s\n", stmt); + GGML_LOG_ERROR(" %s\n", stmt); // abort with GGML_ASSERT to get a stack trace GGML_ABORT("CANN error"); } @@ -165,7 +102,7 @@ static ggml_cann_device_info ggml_cann_init() { aclError err = aclrtGetDeviceCount((uint32_t*)&info.device_count); if (err != ACL_SUCCESS) { - GGML_CANN_LOG_ERROR("%s: failed to initialize CANN: %s\n", + GGML_LOG_ERROR("%s: failed to initialize CANN: %s\n", __func__, aclGetRecentErrMsg()); return info; } @@ -315,7 +252,7 @@ struct ggml_cann_pool_leg : public ggml_cann_pool { *actual_size = look_ahead_size; pool_size += look_ahead_size; #ifdef DEBUG_CANN_MALLOC - GGML_CANN_LOG_INFO( + GGML_LOG_INFO( "%s[%d]: %d buffers, max_size = %u MB, pool_size = %u MB, " "requested %u MB\n", __func__, device, nnz, (uint32_t)(max_size / 1024 / 1024), @@ -470,7 +407,7 @@ struct ggml_cann_pool_vmm : public ggml_cann_pool { // add to the pool pool_size += reserve_size; - // GGML_CANN_LOG_INFO("cann pool[%d]: size increased to %llu MB ( + // GGML_LOG_INFO("cann pool[%d]: size increased to %llu MB ( // reserved %llu MB)\n", // device, (unsigned long long) (pool_size/1024/1024), // (unsigned long long) (reserve_size/1024/1024)); @@ -483,7 +420,7 @@ struct ggml_cann_pool_vmm : public ggml_cann_pool { pool_used += size; #ifdef DEBUG_CANN_MALLOC - GGML_CANN_LOG_INFO("cann pool[%d]: allocated %llu bytes at %llx\n", device, + GGML_LOG_INFO("cann pool[%d]: allocated %llu bytes at %llx\n", device, (unsigned long long)size, (unsigned long long)ptr); #endif return ptr; @@ -497,7 +434,7 @@ struct ggml_cann_pool_vmm : public ggml_cann_pool { */ void free(void* ptr, size_t size) override { #ifdef DEBUG_CANN_MALLOC - GGML_CANN_LOG_INFO("cann pool[%d]: freed %llu bytes at %llx\n", device, + GGML_LOG_INFO("cann pool[%d]: freed %llu bytes at %llx\n", device, (unsigned long long)size, (unsigned long long)ptr); #endif @@ -1095,7 +1032,7 @@ ggml_backend_cann_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, void* dev_ptr; aclError err = aclrtMalloc(&dev_ptr, size, ACL_MEM_MALLOC_HUGE_FIRST); if (err != ACL_SUCCESS) { - GGML_CANN_LOG_ERROR( + GGML_LOG_ERROR( "%s: allocating %.2f MiB on device %d: aclrtMalloc failed: %s\n", __func__, size / 1024.0 / 1024.0, buft_ctx->device, aclGetRecentErrMsg()); @@ -1280,7 +1217,7 @@ static void * ggml_cann_host_malloc(size_t size) { aclError err = aclrtMallocHost((void **) &hostPtr, size); if (err != ACL_SUCCESS) { - GGML_CANN_LOG_WARN("%s: failed to allocate %.2f MiB of pinned memory: %s\n", __func__, + GGML_LOG_WARN("%s: failed to allocate %.2f MiB of pinned memory: %s\n", __func__, size / 1024.0 / 1024.0, aclGetRecentErrMsg()); return nullptr; } @@ -1733,7 +1670,7 @@ static enum ggml_status ggml_backend_cann_graph_compute( bool ok = ggml_cann_compute_forward(*cann_ctx, node); if (!ok) { - GGML_CANN_LOG_ERROR("%s: error: op not supported %s (%s)\n", __func__, + GGML_LOG_ERROR("%s: error: op not supported %s (%s)\n", __func__, node->name, ggml_op_name(node->op)); } GGML_ASSERT(ok); @@ -2043,13 +1980,13 @@ static ggml_guid_t ggml_backend_cann_guid() { ggml_backend_t ggml_backend_cann_init(int32_t device) { aclInit(nullptr); if (device < 0 || device >= ggml_backend_cann_get_device_count()) { - GGML_CANN_LOG_ERROR("%s: error: invalid device %d\n", __func__, device); + GGML_LOG_ERROR("%s: error: invalid device %d\n", __func__, device); return nullptr; } ggml_backend_cann_context* ctx = new ggml_backend_cann_context(device); if (ctx == nullptr) { - GGML_CANN_LOG_ERROR("%s: error: failed to allocate context\n", __func__); + GGML_LOG_ERROR("%s: error: failed to allocate context\n", __func__); return nullptr; } ggml_cann_set_device(ctx->device); diff --git a/ggml/src/ggml-cuda.cu b/ggml/src/ggml-cuda.cu index 43151e235..663e97cd7 100644 --- a/ggml/src/ggml-cuda.cu +++ b/ggml/src/ggml-cuda.cu @@ -56,52 +56,14 @@ static_assert(sizeof(half) == sizeof(ggml_fp16_t), "wrong fp16 size"); -static void ggml_cuda_default_log_callback(enum ggml_log_level level, const char * msg, void * user_data) { - GGML_UNUSED(level); - GGML_UNUSED(user_data); - fprintf(stderr, "%s", msg); -} - -ggml_log_callback ggml_cuda_log_callback = ggml_cuda_default_log_callback; -void * ggml_cuda_log_user_data = NULL; - -GGML_API void ggml_backend_cuda_log_set_callback(ggml_log_callback log_callback, void * user_data) { - ggml_cuda_log_callback = log_callback; - ggml_cuda_log_user_data = user_data; -} - -#define GGML_CUDA_LOG_INFO(...) ggml_cuda_log(GGML_LOG_LEVEL_INFO, __VA_ARGS__) -#define GGML_CUDA_LOG_WARN(...) ggml_cuda_log(GGML_LOG_LEVEL_WARN, __VA_ARGS__) -#define GGML_CUDA_LOG_ERROR(...) ggml_cuda_log(GGML_LOG_LEVEL_ERROR, __VA_ARGS__) - -GGML_ATTRIBUTE_FORMAT(2, 3) -static void ggml_cuda_log(enum ggml_log_level level, const char * format, ...) { - if (ggml_cuda_log_callback != NULL) { - va_list args; - va_start(args, format); - char buffer[128]; - int len = vsnprintf(buffer, 128, format, args); - if (len < 128) { - ggml_cuda_log_callback(level, buffer, ggml_cuda_log_user_data); - } else { - std::vector buffer2(len + 1); // vsnprintf adds a null terminator - va_end(args); - va_start(args, format); - vsnprintf(&buffer2[0], buffer2.size(), format, args); - ggml_cuda_log_callback(level, buffer2.data(), ggml_cuda_log_user_data); - } - va_end(args); - } -} - [[noreturn]] void ggml_cuda_error(const char * stmt, const char * func, const char * file, int line, const char * msg) { int id = -1; // in case cudaGetDevice fails cudaGetDevice(&id); - GGML_CUDA_LOG_ERROR(GGML_CUDA_NAME " error: %s\n", msg); - GGML_CUDA_LOG_ERROR(" current device: %d, in function %s at %s:%d\n", id, func, file, line); - GGML_CUDA_LOG_ERROR(" %s\n", stmt); + GGML_LOG_ERROR(GGML_CUDA_NAME " error: %s\n", msg); + GGML_LOG_ERROR(" current device: %d, in function %s at %s:%d\n", id, func, file, line); + GGML_LOG_ERROR(" %s\n", stmt); // abort with GGML_ABORT to get a stack trace GGML_ABORT(GGML_CUDA_NAME " error"); } @@ -166,7 +128,7 @@ static ggml_cuda_device_info ggml_cuda_init() { cudaError_t err = cudaGetDeviceCount(&info.device_count); if (err != cudaSuccess) { - GGML_CUDA_LOG_ERROR("%s: failed to initialize " GGML_CUDA_NAME ": %s\n", __func__, cudaGetErrorString(err)); + GGML_LOG_ERROR("%s: failed to initialize " GGML_CUDA_NAME ": %s\n", __func__, cudaGetErrorString(err)); return info; } @@ -174,16 +136,16 @@ static ggml_cuda_device_info ggml_cuda_init() { int64_t total_vram = 0; #ifdef GGML_CUDA_FORCE_MMQ - GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_MMQ: yes\n", __func__); + GGML_LOG_INFO("%s: GGML_CUDA_FORCE_MMQ: yes\n", __func__); #else - GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_MMQ: no\n", __func__); + GGML_LOG_INFO("%s: GGML_CUDA_FORCE_MMQ: no\n", __func__); #endif // GGML_CUDA_FORCE_MMQ #ifdef GGML_CUDA_FORCE_CUBLAS - GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_CUBLAS: yes\n", __func__); + GGML_LOG_INFO("%s: GGML_CUDA_FORCE_CUBLAS: yes\n", __func__); #else - GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_CUBLAS: no\n", __func__); + GGML_LOG_INFO("%s: GGML_CUDA_FORCE_CUBLAS: no\n", __func__); #endif // GGML_CUDA_FORCE_CUBLAS - GGML_CUDA_LOG_INFO("%s: found %d " GGML_CUDA_NAME " devices:\n", __func__, info.device_count); + GGML_LOG_INFO("%s: found %d " GGML_CUDA_NAME " devices:\n", __func__, info.device_count); for (int id = 0; id < info.device_count; ++id) { int device_vmm = 0; @@ -204,7 +166,7 @@ static ggml_cuda_device_info ggml_cuda_init() { cudaDeviceProp prop; CUDA_CHECK(cudaGetDeviceProperties(&prop, id)); - GGML_CUDA_LOG_INFO(" Device %d: %s, compute capability %d.%d, VMM: %s\n", id, prop.name, prop.major, prop.minor, device_vmm ? "yes" : "no"); + GGML_LOG_INFO(" Device %d: %s, compute capability %d.%d, VMM: %s\n", id, prop.name, prop.major, prop.minor, device_vmm ? "yes" : "no"); info.default_tensor_split[id] = total_vram; total_vram += prop.totalGlobalMem; @@ -312,7 +274,7 @@ struct ggml_cuda_pool_leg : public ggml_cuda_pool { *actual_size = look_ahead_size; pool_size += look_ahead_size; #ifdef DEBUG_CUDA_MALLOC - GGML_CUDA_LOG_INFO("%s[%d]: %d buffers, max_size = %u MB, pool_size = %u MB, requested %u MB\n", __func__, device, nnz, + GGML_LOG_INFO("%s[%d]: %d buffers, max_size = %u MB, pool_size = %u MB, requested %u MB\n", __func__, device, nnz, (uint32_t)(max_size / 1024 / 1024), (uint32_t)(pool_size / 1024 / 1024), (uint32_t)(size / 1024 / 1024)); #endif return ptr; @@ -327,7 +289,7 @@ struct ggml_cuda_pool_leg : public ggml_cuda_pool { return; } } - GGML_CUDA_LOG_WARN(GGML_CUDA_NAME " buffer pool full, increase MAX_CUDA_BUFFERS\n"); + GGML_LOG_WARN(GGML_CUDA_NAME " buffer pool full, increase MAX_CUDA_BUFFERS\n"); ggml_cuda_set_device(device); CUDA_CHECK(cudaFree(ptr)); pool_size -= size; @@ -591,7 +553,7 @@ static ggml_backend_buffer_t ggml_backend_cuda_buffer_type_alloc_buffer(ggml_bac if (err != cudaSuccess) { // clear the error cudaGetLastError(); - GGML_CUDA_LOG_ERROR("%s: allocating %.2f MiB on device %d: cudaMalloc failed: %s\n", __func__, size / 1024.0 / 1024.0, buft_ctx->device, cudaGetErrorString(err)); + GGML_LOG_ERROR("%s: allocating %.2f MiB on device %d: cudaMalloc failed: %s\n", __func__, size / 1024.0 / 1024.0, buft_ctx->device, cudaGetErrorString(err)); return nullptr; } @@ -1016,7 +978,7 @@ static void * ggml_cuda_host_malloc(size_t size) { if (err != cudaSuccess) { // clear the error cudaGetLastError(); - GGML_CUDA_LOG_WARN("%s: failed to allocate %.2f MiB of pinned memory: %s\n", __func__, + GGML_LOG_WARN("%s: failed to allocate %.2f MiB of pinned memory: %s\n", __func__, size / 1024.0 / 1024.0, cudaGetErrorString(err)); return nullptr; } @@ -2283,7 +2245,7 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg break; case GGML_OP_MUL_MAT: if (dst->src[0]->ne[3] != dst->src[1]->ne[3]) { - GGML_CUDA_LOG_ERROR("%s: cannot compute %s: src0->ne[3] = %" PRId64 ", src1->ne[3] = %" PRId64 " - fallback to CPU\n", __func__, dst->name, dst->src[0]->ne[3], dst->src[1]->ne[3]); + GGML_LOG_ERROR("%s: cannot compute %s: src0->ne[3] = %" PRId64 ", src1->ne[3] = %" PRId64 " - fallback to CPU\n", __func__, dst->name, dst->src[0]->ne[3], dst->src[1]->ne[3]); return false; } else { ggml_cuda_mul_mat(ctx, dst->src[0], dst->src[1], dst); @@ -2367,7 +2329,7 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg cudaError_t err = cudaGetLastError(); if (err != cudaSuccess) { - GGML_CUDA_LOG_ERROR("%s: %s failed\n", __func__, ggml_op_desc(dst)); + GGML_LOG_ERROR("%s: %s failed\n", __func__, ggml_op_desc(dst)); CUDA_CHECK(err); } @@ -2436,7 +2398,7 @@ static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend_src, ggml_ if (cuda_ctx_src->device != buf_ctx_src->device || cuda_ctx_dst->device != buf_ctx_dst->device) { #ifndef NDEBUG - GGML_CUDA_LOG_WARN("%s: backend and buffer devices do not match\n", __func__); + GGML_LOG_WARN("%s: backend and buffer devices do not match\n", __func__); #endif return false; } @@ -2552,7 +2514,7 @@ static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, if (ggml_cuda_info().devices[cuda_ctx->device].cc < CC_AMPERE) { cuda_ctx->cuda_graph->disable_due_to_gpu_arch = true; #ifndef NDEBUG - GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to GPU architecture\n", __func__); + GGML_LOG_WARN("%s: disabling CUDA graphs due to GPU architecture\n", __func__); #endif } } @@ -2603,14 +2565,14 @@ static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, if (node->src[0] && node->src[0]->buffer && ggml_backend_buffer_is_cuda_split(node->src[0]->buffer)) { use_cuda_graph = false; // Split buffers are not supported by CUDA graph capture #ifndef NDEBUG - GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to split buffer\n", __func__); + GGML_LOG_WARN("%s: disabling CUDA graphs due to split buffer\n", __func__); #endif } if (node->op == GGML_OP_MUL_MAT_ID) { use_cuda_graph = false; // This node type is not supported by CUDA graph capture #ifndef NDEBUG - GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to mul_mat_id\n", __func__); + GGML_LOG_WARN("%s: disabling CUDA graphs due to mul_mat_id\n", __func__); #endif } @@ -2619,7 +2581,7 @@ static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, // Changes in batch size or context size can cause changes to the grid size of some kernels. use_cuda_graph = false; #ifndef NDEBUG - GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to batch size > 1 [%s] [%ld %ld %ld %ld]\n", __func__, node->name, node->ne[0], node->ne[1], node->ne[2], node->ne[3]); + GGML_LOG_WARN("%s: disabling CUDA graphs due to batch size > 1 [%s] [%ld %ld %ld %ld]\n", __func__, node->name, node->ne[0], node->ne[1], node->ne[2], node->ne[3]); #endif } @@ -2631,7 +2593,7 @@ static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, if (!ptr) { use_cuda_graph = false; #ifndef NDEBUG - GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to unsupported copy op\n", __func__); + GGML_LOG_WARN("%s: disabling CUDA graphs due to unsupported copy op\n", __func__); #endif } else { if (std::find(ggml_cuda_cpy_fn_ptrs.begin(), ggml_cuda_cpy_fn_ptrs.end(), ptr) == ggml_cuda_cpy_fn_ptrs.end()) { @@ -2655,7 +2617,7 @@ static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, if (cuda_ctx->cuda_graph->number_consecutive_updates >= 4) { cuda_ctx->cuda_graph->disable_due_to_too_many_updates = true; #ifndef NDEBUG - GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to too many consecutive updates\n", __func__); + GGML_LOG_WARN("%s: disabling CUDA graphs due to too many consecutive updates\n", __func__); #endif } } @@ -2694,7 +2656,7 @@ static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, bool ok = ggml_cuda_compute_forward(*cuda_ctx, node); if (!ok) { - GGML_CUDA_LOG_ERROR("%s: op not supported %s (%s)\n", __func__, node->name, ggml_op_name(node->op)); + GGML_LOG_ERROR("%s: op not supported %s (%s)\n", __func__, node->name, ggml_op_name(node->op)); } GGML_ASSERT(ok); } @@ -2713,7 +2675,7 @@ static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, use_cuda_graph = false; cuda_ctx->cuda_graph->disable_due_to_failed_graph_capture = true; #ifndef NDEBUG - GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to failed graph capture\n", __func__); + GGML_LOG_WARN("%s: disabling CUDA graphs due to failed graph capture\n", __func__); #endif } else { graph_evaluated_or_captured = true; // CUDA graph has been captured @@ -2780,7 +2742,7 @@ static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, cudaError_t stat = cudaGraphExecUpdate(cuda_ctx->cuda_graph->instance, cuda_ctx->cuda_graph->graph, &result_info); if (stat == cudaErrorGraphExecUpdateFailure) { #ifndef NDEBUG - GGML_CUDA_LOG_ERROR("%s: CUDA graph update failed\n", __func__); + GGML_LOG_ERROR("%s: CUDA graph update failed\n", __func__); #endif // The pre-existing graph exec cannot be updated due to violated constraints // so instead clear error and re-instantiate @@ -2882,7 +2844,7 @@ bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size) { // clear the error cudaGetLastError(); - GGML_CUDA_LOG_WARN("%s: failed to register %.2f MiB of pinned memory: %s\n", __func__, + GGML_LOG_WARN("%s: failed to register %.2f MiB of pinned memory: %s\n", __func__, size / 1024.0 / 1024.0, cudaGetErrorString(err)); return false; } @@ -3305,17 +3267,11 @@ static void * ggml_backend_cuda_reg_get_proc_address(ggml_backend_reg_t reg, con return nullptr; } -static void ggml_backend_cuda_reg_set_log_callback(ggml_backend_reg_t reg, ggml_log_callback log_callback, void * user_data) { - GGML_UNUSED(reg); - ggml_backend_cuda_log_set_callback(log_callback, user_data); -} - static const ggml_backend_reg_i ggml_backend_cuda_reg_interface = { /* .get_name = */ ggml_backend_cuda_reg_get_name, /* .get_device_count = */ ggml_backend_cuda_reg_get_device_count, /* .get_device_get = */ ggml_backend_cuda_reg_get_device, /* .get_proc_address = */ ggml_backend_cuda_reg_get_proc_address, - /* .set_log_callback = */ ggml_backend_cuda_reg_set_log_callback, }; // backend registry @@ -3361,13 +3317,13 @@ ggml_backend_reg_t ggml_backend_cuda_reg() { ggml_backend_t ggml_backend_cuda_init(int device) { if (device < 0 || device >= ggml_backend_cuda_get_device_count()) { - GGML_CUDA_LOG_ERROR("%s: invalid device %d\n", __func__, device); + GGML_LOG_ERROR("%s: invalid device %d\n", __func__, device); return nullptr; } ggml_backend_cuda_context * ctx = new ggml_backend_cuda_context(device); if (ctx == nullptr) { - GGML_CUDA_LOG_ERROR("%s: failed to allocate context\n", __func__); + GGML_LOG_ERROR("%s: failed to allocate context\n", __func__); return nullptr; } diff --git a/ggml/src/ggml-impl.h b/ggml/src/ggml-impl.h index 833984190..d3f4bad8c 100644 --- a/ggml/src/ggml-impl.h +++ b/ggml/src/ggml-impl.h @@ -33,6 +33,21 @@ extern "C" { #endif #endif +// +// logging +// + +GGML_ATTRIBUTE_FORMAT(2, 3) +void ggml_log_internal (enum ggml_log_level level, const char * format, ...); +void ggml_log_callback_default(enum ggml_log_level level, const char * text, void * user_data); + +#define GGML_LOG(...) ggml_log_internal(GGML_LOG_LEVEL_NONE , __VA_ARGS__) +#define GGML_LOG_INFO(...) ggml_log_internal(GGML_LOG_LEVEL_INFO , __VA_ARGS__) +#define GGML_LOG_WARN(...) ggml_log_internal(GGML_LOG_LEVEL_WARN , __VA_ARGS__) +#define GGML_LOG_ERROR(...) ggml_log_internal(GGML_LOG_LEVEL_ERROR, __VA_ARGS__) +#define GGML_LOG_DEBUG(...) ggml_log_internal(GGML_LOG_LEVEL_DEBUG, __VA_ARGS__) +#define GGML_LOG_CONT(...) ggml_log_internal(GGML_LOG_LEVEL_CONT , __VA_ARGS__) + // bitset typedef uint32_t ggml_bitset_t; diff --git a/ggml/src/ggml-metal.m b/ggml/src/ggml-metal.m index 8ff16983e..7ffaaf8d8 100644 --- a/ggml/src/ggml-metal.m +++ b/ggml/src/ggml-metal.m @@ -18,19 +18,6 @@ // max number of MTLCommandBuffer used to submit a graph for processing #define GGML_METAL_MAX_COMMAND_BUFFERS 8 -#ifdef GGML_METAL_NDEBUG -#define GGML_METAL_LOG(...) -#define GGML_METAL_LOG_INFO(...) -#define GGML_METAL_LOG_WARN(...) -#define GGML_METAL_LOG_ERROR(...) -#else -#define GGML_METAL_LOG(...) ggml_metal_log(GGML_LOG_LEVEL_NONE, __VA_ARGS__) -#define GGML_METAL_LOG_INFO(...) ggml_metal_log(GGML_LOG_LEVEL_INFO, __VA_ARGS__) -#define GGML_METAL_LOG_WARN(...) ggml_metal_log(GGML_LOG_LEVEL_WARN, __VA_ARGS__) -#define GGML_METAL_LOG_ERROR(...) ggml_metal_log(GGML_LOG_LEVEL_ERROR, __VA_ARGS__) -#define GGML_METAL_LOG_DEBUG(...) ggml_metal_log(GGML_LOG_LEVEL_DEBUG, __VA_ARGS__) -#endif - #define UNUSED(x) (void)(x) struct ggml_metal_kernel { @@ -277,51 +264,19 @@ struct ggml_backend_metal_context { @implementation GGMLMetalClass @end -static void ggml_metal_default_log_callback(enum ggml_log_level level, const char * msg, void * user_data) { - fprintf(stderr, "%s", msg); - - UNUSED(level); - UNUSED(user_data); -} - -ggml_log_callback ggml_metal_log_callback = ggml_metal_default_log_callback; -void * ggml_metal_log_user_data = NULL; - -GGML_ATTRIBUTE_FORMAT(2, 3) -static void ggml_metal_log(enum ggml_log_level level, const char * format, ...){ - if (ggml_metal_log_callback != NULL) { - va_list args; - va_start(args, format); - char buffer[128]; - int len = vsnprintf(buffer, 128, format, args); - if (len < 128) { - ggml_metal_log_callback(level, buffer, ggml_metal_log_user_data); - } else { - char* buffer2 = malloc(len+1); - va_end(args); - va_start(args, format); - vsnprintf(buffer2, len+1, format, args); - buffer2[len] = 0; - ggml_metal_log_callback(level, buffer2, ggml_metal_log_user_data); - free(buffer2); - } - va_end(args); - } -} - static void * ggml_metal_host_malloc(size_t n) { void * data = NULL; #if TARGET_OS_OSX kern_return_t err = vm_allocate((vm_map_t) mach_task_self(), (void *) &data, n, VM_FLAGS_ANYWHERE); if (err != KERN_SUCCESS) { - GGML_METAL_LOG_ERROR("%s: error: vm_allocate failed\n", __func__); + GGML_LOG_ERROR("%s: error: vm_allocate failed\n", __func__); return NULL; } #else const int result = posix_memalign((void **) &data, sysconf(_SC_PAGESIZE), n); if (result != 0) { - GGML_METAL_LOG_ERROR("%s: error: posix_memalign failed\n", __func__); + GGML_LOG_ERROR("%s: error: posix_memalign failed\n", __func__); return NULL; } #endif @@ -330,20 +285,20 @@ static void * ggml_metal_host_malloc(size_t n) { } static struct ggml_backend_metal_context * ggml_metal_init(void) { - GGML_METAL_LOG_INFO("%s: allocating\n", __func__); + GGML_LOG_INFO("%s: allocating\n", __func__); #if TARGET_OS_OSX && !GGML_METAL_NDEBUG // Show all the Metal device instances in the system NSArray * devices = MTLCopyAllDevices(); for (id device in devices) { - GGML_METAL_LOG_INFO("%s: found device: %s\n", __func__, [[device name] UTF8String]); + GGML_LOG_INFO("%s: found device: %s\n", __func__, [[device name] UTF8String]); } [devices release]; // since it was created by a *Copy* C method #endif // Pick and show default Metal device id device = MTLCreateSystemDefaultDevice(); - GGML_METAL_LOG_INFO("%s: picking default device: %s\n", __func__, [[device name] UTF8String]); + GGML_LOG_INFO("%s: picking default device: %s\n", __func__, [[device name] UTF8String]); // Configure context struct ggml_backend_metal_context * ctx = calloc(1, sizeof(struct ggml_backend_metal_context)); @@ -381,28 +336,28 @@ static struct ggml_backend_metal_context * ggml_metal_init(void) { if (try_metallib && path_lib != nil) { // pre-compiled library found NSURL * libURL = [NSURL fileURLWithPath:path_lib]; - GGML_METAL_LOG_INFO("%s: loading '%s'\n", __func__, [path_lib UTF8String]); + GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_lib UTF8String]); metal_library = [ctx->device newLibraryWithURL:libURL error:&error]; if (error) { - GGML_METAL_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); + GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); return NULL; } } else { #if GGML_METAL_EMBED_LIBRARY - GGML_METAL_LOG_INFO("%s: using embedded metal library\n", __func__); + GGML_LOG_INFO("%s: using embedded metal library\n", __func__); extern const char ggml_metallib_start[]; extern const char ggml_metallib_end[]; NSString * src = [[NSString alloc] initWithBytes:ggml_metallib_start length:(ggml_metallib_end-ggml_metallib_start) encoding:NSUTF8StringEncoding]; #else - GGML_METAL_LOG_INFO("%s: default.metallib not found, loading from source\n", __func__); + GGML_LOG_INFO("%s: default.metallib not found, loading from source\n", __func__); NSString * path_source; NSString * path_resource = [[NSProcessInfo processInfo].environment objectForKey:@"GGML_METAL_PATH_RESOURCES"]; - GGML_METAL_LOG_INFO("%s: GGML_METAL_PATH_RESOURCES = %s\n", __func__, path_resource ? [path_resource UTF8String] : "nil"); + GGML_LOG_INFO("%s: GGML_METAL_PATH_RESOURCES = %s\n", __func__, path_resource ? [path_resource UTF8String] : "nil"); if (path_resource) { path_source = [path_resource stringByAppendingPathComponent:@"ggml-metal.metal"]; @@ -411,15 +366,15 @@ static struct ggml_backend_metal_context * ggml_metal_init(void) { } if (path_source == nil) { - GGML_METAL_LOG_WARN("%s: error: could not use bundle path to find ggml-metal.metal, falling back to trying cwd\n", __func__); + GGML_LOG_WARN("%s: error: could not use bundle path to find ggml-metal.metal, falling back to trying cwd\n", __func__); path_source = @"ggml-metal.metal"; } - GGML_METAL_LOG_INFO("%s: loading '%s'\n", __func__, [path_source UTF8String]); + GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_source UTF8String]); NSString * src = [NSString stringWithContentsOfFile:path_source encoding:NSUTF8StringEncoding error:&error]; if (error) { - GGML_METAL_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); + GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); return NULL; } #endif // GGML_METAL_EMBED_LIBRARY @@ -435,7 +390,7 @@ static struct ggml_backend_metal_context * ggml_metal_init(void) { metal_library = [ctx->device newLibraryWithSource:src options:options error:&error]; if (error) { - GGML_METAL_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); + GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]); return NULL; } } @@ -443,7 +398,7 @@ static struct ggml_backend_metal_context * ggml_metal_init(void) { } // print MTL GPU family: - GGML_METAL_LOG_INFO("%s: GPU name: %s\n", __func__, [[ctx->device name] UTF8String]); + GGML_LOG_INFO("%s: GPU name: %s\n", __func__, [[ctx->device name] UTF8String]); const NSInteger MTLGPUFamilyMetal3 = 5001; @@ -453,21 +408,21 @@ static struct ggml_backend_metal_context * ggml_metal_init(void) { { for (int i = MTLGPUFamilyApple1 + 20; i >= MTLGPUFamilyApple1; --i) { if ([ctx->device supportsFamily:i]) { - GGML_METAL_LOG_INFO("%s: GPU family: MTLGPUFamilyApple%d (%d)\n", __func__, i - (int) MTLGPUFamilyApple1 + 1, i); + GGML_LOG_INFO("%s: GPU family: MTLGPUFamilyApple%d (%d)\n", __func__, i - (int) MTLGPUFamilyApple1 + 1, i); break; } } for (int i = MTLGPUFamilyCommon1 + 5; i >= MTLGPUFamilyCommon1; --i) { if ([ctx->device supportsFamily:i]) { - GGML_METAL_LOG_INFO("%s: GPU family: MTLGPUFamilyCommon%d (%d)\n", __func__, i - (int) MTLGPUFamilyCommon1 + 1, i); + GGML_LOG_INFO("%s: GPU family: MTLGPUFamilyCommon%d (%d)\n", __func__, i - (int) MTLGPUFamilyCommon1 + 1, i); break; } } for (int i = MTLGPUFamilyMetal3 + 5; i >= MTLGPUFamilyMetal3; --i) { if ([ctx->device supportsFamily:i]) { - GGML_METAL_LOG_INFO("%s: GPU family: MTLGPUFamilyMetal%d (%d)\n", __func__, i - (int) MTLGPUFamilyMetal3 + 3, i); + GGML_LOG_INFO("%s: GPU family: MTLGPUFamilyMetal%d (%d)\n", __func__, i - (int) MTLGPUFamilyMetal3 + 3, i); break; } } @@ -478,9 +433,9 @@ static struct ggml_backend_metal_context * ggml_metal_init(void) { ctx->support_simdgroup_mm = [ctx->device supportsFamily:MTLGPUFamilyApple7]; - GGML_METAL_LOG_INFO("%s: simdgroup reduction support = %s\n", __func__, ctx->support_simdgroup_reduction ? "true" : "false"); - GGML_METAL_LOG_INFO("%s: simdgroup matrix mul. support = %s\n", __func__, ctx->support_simdgroup_mm ? "true" : "false"); - GGML_METAL_LOG_INFO("%s: hasUnifiedMemory = %s\n", __func__, ctx->device.hasUnifiedMemory ? "true" : "false"); + GGML_LOG_INFO("%s: simdgroup reduction support = %s\n", __func__, ctx->support_simdgroup_reduction ? "true" : "false"); + GGML_LOG_INFO("%s: simdgroup matrix mul. support = %s\n", __func__, ctx->support_simdgroup_mm ? "true" : "false"); + GGML_LOG_INFO("%s: hasUnifiedMemory = %s\n", __func__, ctx->device.hasUnifiedMemory ? "true" : "false"); ctx->capture_next_compute = false; ctx->capture_started = false; @@ -494,13 +449,13 @@ static struct ggml_backend_metal_context * ggml_metal_init(void) { #if TARGET_OS_OSX || (TARGET_OS_IOS && __clang_major__ >= 15) if (@available(macOS 10.12, iOS 16.0, *)) { - GGML_METAL_LOG_INFO("%s: recommendedMaxWorkingSetSize = %8.2f MB\n", __func__, ctx->device.recommendedMaxWorkingSetSize / 1e6); + GGML_LOG_INFO("%s: recommendedMaxWorkingSetSize = %8.2f MB\n", __func__, ctx->device.recommendedMaxWorkingSetSize / 1e6); } #elif TARGET_OS_OSX if (ctx->device.maxTransferRate != 0) { - GGML_METAL_LOG_INFO("%s: maxTransferRate = %8.2f MB/s\n", __func__, ctx->device.maxTransferRate / 1e6); + GGML_LOG_INFO("%s: maxTransferRate = %8.2f MB/s\n", __func__, ctx->device.maxTransferRate / 1e6); } else { - GGML_METAL_LOG_INFO("%s: maxTransferRate = built-in GPU\n", __func__); + GGML_LOG_INFO("%s: maxTransferRate = built-in GPU\n", __func__); } #endif @@ -513,7 +468,7 @@ static struct ggml_backend_metal_context * ggml_metal_init(void) { } /* - GGML_METAL_LOG_INFO("%s: loaded %-40s %16p | th_max = %4d | th_width = %4d\n", __func__, "kernel_"#name, (void *) kernel->pipeline, \ + GGML_LOG_INFO("%s: loaded %-40s %16p | th_max = %4d | th_width = %4d\n", __func__, "kernel_"#name, (void *) kernel->pipeline, \ (int) kernel->pipeline.maxTotalThreadsPerThreadgroup, \ (int) kernel->pipeline.threadExecutionWidth); \ */ @@ -524,12 +479,12 @@ static struct ggml_backend_metal_context * ggml_metal_init(void) { kernel->pipeline = [ctx->device newComputePipelineStateWithFunction:metal_function error:&error]; \ [metal_function release]; \ if (error) { \ - GGML_METAL_LOG_ERROR("%s: error: load pipeline error: %s\n", __func__, [[error description] UTF8String]); \ + GGML_LOG_ERROR("%s: error: load pipeline error: %s\n", __func__, [[error description] UTF8String]); \ [metal_library release]; \ return NULL; \ } \ } else { \ - GGML_METAL_LOG_WARN("%s: skipping %-40s (not supported)\n", __func__, "kernel_"#name); \ + GGML_LOG_WARN("%s: skipping %-40s (not supported)\n", __func__, "kernel_"#name); \ } // simd_sum and simd_max requires MTLGPUFamilyApple7 @@ -726,7 +681,7 @@ static struct ggml_backend_metal_context * ggml_metal_init(void) { } static void ggml_metal_free(struct ggml_backend_metal_context * ctx) { - GGML_METAL_LOG_INFO("%s: deallocating\n", __func__); + GGML_LOG_INFO("%s: deallocating\n", __func__); for (int i = 0; i < GGML_METAL_KERNEL_TYPE_COUNT; ++i) { [ctx->kernels[i].pipeline release]; @@ -764,7 +719,7 @@ struct ggml_backend_metal_buffer_context { // Metal buffer based on the host memory pointer // static id ggml_metal_get_buffer(struct ggml_tensor * t, size_t * offs) { - //GGML_METAL_LOG_INFO("%s: data tensor '%16s', offs_data = %8ld, offs_eval = %8ld, offs_cach = %8ld\n", __func__, t->name, offs_data, offs_eval, offs_cach); + //GGML_LOG_INFO("%s: data tensor '%16s', offs_data = %8ld, offs_eval = %8ld, offs_cach = %8ld\n", __func__, t->name, offs_data, offs_eval, offs_cach); const int64_t tsize = ggml_nbytes(t); @@ -776,17 +731,17 @@ static id ggml_metal_get_buffer(struct ggml_tensor * t, size_t * offs for (int i = 0; i < buf_ctx->n_buffers; ++i) { const int64_t ioffs = (int64_t) t->data - (int64_t) buf_ctx->buffers[i].data; - //GGML_METAL_LOG_INFO("ioffs = %10ld, tsize = %10ld, sum = %10ld, buf_ctx->buffers[%d].size = %10ld\n", ioffs, tsize, ioffs + tsize, i, buf_ctx->buffers[i].size); + //GGML_LOG_INFO("ioffs = %10ld, tsize = %10ld, sum = %10ld, buf_ctx->buffers[%d].size = %10ld\n", ioffs, tsize, ioffs + tsize, i, buf_ctx->buffers[i].size); if (ioffs >= 0 && ioffs + tsize <= (int64_t) buf_ctx->buffers[i].size) { *offs = (size_t) ioffs; - //GGML_METAL_LOG_INFO("%s: tensor '%16s', offs = %8ld\n", __func__, t->name, *offs); + //GGML_LOG_INFO("%s: tensor '%16s', offs = %8ld\n", __func__, t->name, *offs); return buf_ctx->buffers[i].metal; } } - GGML_METAL_LOG_ERROR("%s: error: tensor '%s' buffer is nil\n", __func__, t->name); + GGML_LOG_ERROR("%s: error: tensor '%s' buffer is nil\n", __func__, t->name); return nil; } @@ -918,7 +873,7 @@ static void ggml_metal_encode_node( struct ggml_tensor * node = ggml_graph_node(gf, idx); - //GGML_METAL_LOG_INFO("%s: encoding node %3d, op = %8s\n", __func__, idx, ggml_op_name(node->op)); + //GGML_LOG_INFO("%s: encoding node %3d, op = %8s\n", __func__, idx, ggml_op_name(node->op)); struct ggml_tensor * src0 = node->src[0]; struct ggml_tensor * src1 = node->src[1]; @@ -944,7 +899,7 @@ static void ggml_metal_encode_node( } if (!ggml_metal_supports_op(ctx, dst)) { - GGML_METAL_LOG_ERROR("%s: error: unsupported op '%s'\n", __func__, ggml_op_desc(dst)); + GGML_LOG_ERROR("%s: error: unsupported op '%s'\n", __func__, ggml_op_desc(dst)); GGML_ABORT("unsupported op"); } @@ -1002,17 +957,17 @@ static void ggml_metal_encode_node( id id_src2 = src2 ? ggml_metal_get_buffer(src2, &offs_src2) : nil; id id_dst = dst ? ggml_metal_get_buffer(dst, &offs_dst) : nil; - //GGML_METAL_LOG_INFO("%s: op - %s\n", __func__, ggml_op_name(dst->op)); + //GGML_LOG_INFO("%s: op - %s\n", __func__, ggml_op_name(dst->op)); //if (src0) { - // GGML_METAL_LOG_INFO("%s: src0 - %4s [%5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(src0t), ne00, ne01, ne02, + // GGML_LOG_INFO("%s: src0 - %4s [%5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(src0t), ne00, ne01, ne02, // ggml_is_contiguous(src0), src0->name); //} //if (src1) { - // GGML_METAL_LOG_INFO("%s: src1 - %4s [%5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(src1t), ne10, ne11, ne12, + // GGML_LOG_INFO("%s: src1 - %4s [%5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(src1t), ne10, ne11, ne12, // ggml_is_contiguous(src1), src1->name); //} //if (dst) { - // GGML_METAL_LOG_INFO("%s: dst - %4s [%5lld, %5lld, %5lld], 1, %s\n", __func__, ggml_type_name(dstt), ne0, ne1, ne2, + // GGML_LOG_INFO("%s: dst - %4s [%5lld, %5lld, %5lld], 1, %s\n", __func__, ggml_type_name(dstt), ne0, ne1, ne2, // dst->name); //} @@ -1404,7 +1359,7 @@ static void ggml_metal_encode_node( } break; default: { - GGML_METAL_LOG_WARN("%s: node %3d, op = %8s not implemented\n", __func__, idx, ggml_op_name(dst->op)); + GGML_LOG_WARN("%s: node %3d, op = %8s not implemented\n", __func__, idx, ggml_op_name(dst->op)); GGML_ABORT("fatal error"); } } break; @@ -1956,7 +1911,7 @@ static void ggml_metal_encode_node( } break; default: { - GGML_METAL_LOG_ERROR("Asserting on type %d\n", (int)src0t); + GGML_LOG_ERROR("Asserting on type %d\n", (int)src0t); GGML_ABORT("not implemented"); } }; @@ -2252,7 +2207,7 @@ static void ggml_metal_encode_node( } break; default: { - GGML_METAL_LOG_ERROR("Asserting on type %d\n", (int)src2t); + GGML_LOG_ERROR("Asserting on type %d\n", (int)src2t); GGML_ABORT("not implemented"); } }; @@ -2821,8 +2776,8 @@ static void ggml_metal_encode_node( //case 256: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_F16_H256].pipeline; break; default: { - GGML_METAL_LOG_ERROR("unsupported size: %lld\n", ne00); - GGML_METAL_LOG_ERROR("add template specialization for this size\n"); + GGML_LOG_ERROR("unsupported size: %lld\n", ne00); + GGML_LOG_ERROR("add template specialization for this size\n"); GGML_ABORT("add template specialization for this size"); } } @@ -2834,8 +2789,8 @@ static void ggml_metal_encode_node( //case 256: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_FLASH_ATTN_EXT_VEC_F16_H256].pipeline; break; default: { - GGML_METAL_LOG_ERROR("unsupported size: %lld\n", ne00); - GGML_METAL_LOG_ERROR("add template specialization for this size\n"); + GGML_LOG_ERROR("unsupported size: %lld\n", ne00); + GGML_LOG_ERROR("add template specialization for this size\n"); GGML_ABORT("add template specialization for this size"); } } @@ -2996,7 +2951,7 @@ static void ggml_metal_encode_node( } break; default: { - GGML_METAL_LOG_ERROR("%s: error: node %3d, op = %8s not implemented\n", __func__, idx, ggml_op_name(dst->op)); + GGML_LOG_ERROR("%s: error: node %3d, op = %8s not implemented\n", __func__, idx, ggml_op_name(dst->op)); GGML_ABORT("fatal error"); } } @@ -3041,7 +2996,7 @@ static enum ggml_status ggml_metal_graph_compute( NSError * error = nil; if (![[MTLCaptureManager sharedCaptureManager] startCaptureWithDescriptor:descriptor error:&error]) { - GGML_METAL_LOG_ERROR("%s: error: unable to start capture '%s'\n", __func__, [[error localizedDescription] UTF8String]); + GGML_LOG_ERROR("%s: error: unable to start capture '%s'\n", __func__, [[error localizedDescription] UTF8String]); GGML_ABORT("capture failed"); } else { [ctx->capture_scope beginScope]; @@ -3123,9 +3078,9 @@ static enum ggml_status ggml_metal_graph_compute( MTLCommandBufferStatus status = [command_buffer status]; if (status != MTLCommandBufferStatusCompleted) { - GGML_METAL_LOG_INFO("%s: command buffer %d failed with status %lu\n", __func__, n_cb, status); + GGML_LOG_INFO("%s: command buffer %d failed with status %lu\n", __func__, n_cb, status); if (status == MTLCommandBufferStatusError) { - GGML_METAL_LOG_INFO("error: %s\n", [[command_buffer error].localizedDescription UTF8String]); + GGML_LOG_INFO("error: %s\n", [[command_buffer error].localizedDescription UTF8String]); } return GGML_STATUS_FAILED; @@ -3138,9 +3093,9 @@ static enum ggml_status ggml_metal_graph_compute( MTLCommandBufferStatus status = [command_buffer status]; if (status != MTLCommandBufferStatusCompleted) { - GGML_METAL_LOG_INFO("%s: command buffer %d failed with status %lu\n", __func__, i, status); + GGML_LOG_INFO("%s: command buffer %d failed with status %lu\n", __func__, i, status); if (status == MTLCommandBufferStatusError) { - GGML_METAL_LOG_INFO("error: %s\n", [[command_buffer error].localizedDescription UTF8String]); + GGML_LOG_INFO("error: %s\n", [[command_buffer error].localizedDescription UTF8String]); } return GGML_STATUS_FAILED; @@ -3157,7 +3112,7 @@ static enum ggml_status ggml_metal_graph_compute( } if (ctx->abort_callback && ctx->abort_callback(ctx->abort_callback_data)) { - GGML_METAL_LOG_INFO("%s: command buffer %d aborted", __func__, i); + GGML_LOG_INFO("%s: command buffer %d aborted", __func__, i); return GGML_STATUS_ABORTED; } @@ -3286,17 +3241,17 @@ static void ggml_backend_metal_log_allocated_size(id device, size_t s #ifndef GGML_METAL_NDEBUG #if TARGET_OS_OSX || (TARGET_OS_IOS && __clang_major__ >= 15) if (@available(macOS 10.12, iOS 16.0, *)) { - GGML_METAL_LOG_DEBUG("%s: allocated buffer, size = %8.2f MiB, (%8.2f / %8.2f)\n", + GGML_LOG_DEBUG("%s: allocated buffer, size = %8.2f MiB, (%8.2f / %8.2f)\n", __func__, size_aligned / 1024.0 / 1024.0, device.currentAllocatedSize / 1024.0 / 1024.0, device.recommendedMaxWorkingSetSize / 1024.0 / 1024.0); if (device.currentAllocatedSize > device.recommendedMaxWorkingSetSize) { - GGML_METAL_LOG_WARN("%s: warning: current allocated size is greater than the recommended max working set size\n", __func__); + GGML_LOG_WARN("%s: warning: current allocated size is greater than the recommended max working set size\n", __func__); } } else { - GGML_METAL_LOG_INFO("%s: allocated buffer, size = %8.2f MiB, (%8.2f)\n", + GGML_LOG_INFO("%s: allocated buffer, size = %8.2f MiB, (%8.2f)\n", __func__, size_aligned / 1024.0 / 1024.0, device.currentAllocatedSize / 1024.0 / 1024.0); @@ -3338,7 +3293,7 @@ static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buffer(ggml_ba } if (size_aligned > 0 && (ctx->all_data == NULL || ctx->buffers[0].metal == nil)) { - GGML_METAL_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_aligned / 1024.0 / 1024.0); + GGML_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_aligned / 1024.0 / 1024.0); free(ctx); ggml_backend_metal_free_device(); return NULL; @@ -3423,7 +3378,7 @@ ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t siz ctx->buffers[ctx->n_buffers].metal = [device newBufferWithBytesNoCopy:data length:size_aligned options:MTLResourceStorageModeShared deallocator:nil]; if (ctx->buffers[ctx->n_buffers].metal == nil) { - GGML_METAL_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_aligned / 1024.0 / 1024.0); + GGML_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_aligned / 1024.0 / 1024.0); return false; } } @@ -3449,7 +3404,7 @@ ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t siz ctx->buffers[ctx->n_buffers].metal = [device newBufferWithBytesNoCopy:(void *) ((uint8_t *) data + i) length:size_step_aligned options:MTLResourceStorageModeShared deallocator:nil]; if (ctx->buffers[ctx->n_buffers].metal == nil) { - GGML_METAL_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_step_aligned / 1024.0 / 1024.0); + GGML_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_step_aligned / 1024.0 / 1024.0); return false; } } @@ -3457,7 +3412,7 @@ ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t siz ggml_backend_metal_log_allocated_size(device, size_step_aligned); if (i + size_step < size) { - GGML_METAL_LOG_INFO("\n"); + GGML_LOG_INFO("\n"); } ++ctx->n_buffers; @@ -3514,7 +3469,7 @@ static void ggml_backend_metal_set_n_cb(ggml_backend_t backend, int n_cb) { ctx->n_cb = MIN(n_cb, GGML_METAL_MAX_COMMAND_BUFFERS); if (ctx->n_cb > 2) { - GGML_METAL_LOG_WARN("%s: n_cb = %d, using n_cb > 2 is not recommended and can degrade the performance in some cases\n", __func__, n_cb); + GGML_LOG_WARN("%s: n_cb = %d, using n_cb > 2 is not recommended and can degrade the performance in some cases\n", __func__, n_cb); } } @@ -3544,11 +3499,6 @@ static struct ggml_backend_i ggml_backend_metal_i = { /* .event_wait = */ NULL, }; -void ggml_backend_metal_log_set_callback(ggml_log_callback log_callback, void * user_data) { - ggml_metal_log_callback = log_callback; - ggml_metal_log_user_data = user_data; -} - static ggml_guid_t ggml_backend_metal_guid(void) { static ggml_guid guid = { 0x81, 0xa1, 0x8b, 0x1e, 0x71, 0xec, 0x79, 0xed, 0x2b, 0x85, 0xdc, 0x8a, 0x61, 0x98, 0x30, 0xe6 }; return &guid; @@ -3557,7 +3507,7 @@ static ggml_guid_t ggml_backend_metal_guid(void) { ggml_backend_t ggml_backend_metal_init(void) { struct ggml_backend_metal_context * ctx = ggml_metal_init(); if (ctx == NULL) { - GGML_METAL_LOG_ERROR("%s: error: failed to allocate context\n", __func__); + GGML_LOG_ERROR("%s: error: failed to allocate context\n", __func__); return NULL; } diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index e740e58b2..de500a675 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -319,26 +319,63 @@ void ggml_abort(const char * file, int line, const char * fmt, ...) { // logging // +struct ggml_logger_state { + ggml_log_callback log_callback; + void * log_callback_user_data; +}; +static struct ggml_logger_state g_logger_state = {ggml_log_callback_default, NULL}; + +static void ggml_log_internal_v(enum ggml_log_level level, const char * format, va_list args) { + if (format == NULL) + return; + va_list args_copy; + va_copy(args_copy, args); + char buffer[128]; + int len = vsnprintf(buffer, 128, format, args); + if (len < 128) { + g_logger_state.log_callback(level, buffer, g_logger_state.log_callback_user_data); + } else { + char * buffer2 = (char *) calloc(len + 1, sizeof(char)); + vsnprintf(buffer2, len + 1, format, args_copy); + buffer2[len] = 0; + g_logger_state.log_callback(level, buffer2, g_logger_state.log_callback_user_data); + free(buffer2); + } + va_end(args_copy); +} + +void ggml_log_internal(enum ggml_log_level level, const char * format, ...) { + va_list args; + va_start(args, format); + ggml_log_internal_v(level, format, args); + va_end(args); +} + +void ggml_log_callback_default(enum ggml_log_level level, const char * text, void * user_data) { + (void) level; + (void) user_data; + fputs(text, stderr); + fflush(stderr); +} + #if (GGML_DEBUG >= 1) -#define GGML_PRINT_DEBUG(...) printf(__VA_ARGS__) +#define GGML_PRINT_DEBUG(...) GGML_LOG_DEBUG(__VA_ARGS__) #else #define GGML_PRINT_DEBUG(...) #endif #if (GGML_DEBUG >= 5) -#define GGML_PRINT_DEBUG_5(...) printf(__VA_ARGS__) +#define GGML_PRINT_DEBUG_5(...) GGML_LOG_DEBUG(__VA_ARGS__) #else #define GGML_PRINT_DEBUG_5(...) #endif #if (GGML_DEBUG >= 10) -#define GGML_PRINT_DEBUG_10(...) printf(__VA_ARGS__) +#define GGML_PRINT_DEBUG_10(...) GGML_LOG_DEBUG(__VA_ARGS__) #else #define GGML_PRINT_DEBUG_10(...) #endif -#define GGML_PRINT(...) printf(__VA_ARGS__) - // // end of logging block // @@ -355,7 +392,7 @@ void ggml_abort(const char * file, int line, const char * fmt, ...) { #else inline static void * ggml_aligned_malloc(size_t size) { if (size == 0) { - GGML_PRINT("WARNING: Behavior may be unexpected when allocating 0 bytes for ggml_aligned_malloc!\n"); + GGML_LOG_WARN("Behavior may be unexpected when allocating 0 bytes for ggml_aligned_malloc!\n"); return NULL; } void * aligned_memory = NULL; @@ -377,7 +414,7 @@ inline static void * ggml_aligned_malloc(size_t size) { error_desc = "insufficient memory"; break; } - GGML_PRINT("%s: %s (attempted to allocate %6.2f MB)\n", __func__, error_desc, size/(1024.0*1024.0)); + GGML_LOG_ERROR("%s: %s (attempted to allocate %6.2f MB)\n", __func__, error_desc, size/(1024.0*1024.0)); GGML_ABORT("fatal error"); return NULL; } @@ -393,12 +430,12 @@ inline static void * ggml_aligned_malloc(size_t size) { inline static void * ggml_malloc(size_t size) { if (size == 0) { - GGML_PRINT("WARNING: Behavior may be unexpected when allocating 0 bytes for ggml_malloc!\n"); + GGML_LOG_WARN("Behavior may be unexpected when allocating 0 bytes for ggml_malloc!\n"); return NULL; } void * result = malloc(size); if (result == NULL) { - GGML_PRINT("%s: failed to allocate %6.2f MB\n", __func__, size/(1024.0*1024.0)); + GGML_LOG_ERROR("%s: failed to allocate %6.2f MB\n", __func__, size/(1024.0*1024.0)); GGML_ABORT("fatal error"); } return result; @@ -407,12 +444,12 @@ inline static void * ggml_malloc(size_t size) { // calloc inline static void * ggml_calloc(size_t num, size_t size) { if (num == 0 || size == 0) { - GGML_PRINT("WARNING: Behavior may be unexpected when allocating 0 bytes for ggml_calloc!\n"); + GGML_LOG_WARN("Behavior may be unexpected when allocating 0 bytes for ggml_calloc!\n"); return NULL; } void * result = calloc(num, size); if (result == NULL) { - GGML_PRINT("%s: failed to allocate %6.2f MB\n", __func__, size/(1024.0*1024.0)); + GGML_LOG_ERROR("%s: failed to allocate %6.2f MB\n", __func__, size/(1024.0*1024.0)); GGML_ABORT("fatal error"); } return result; @@ -3347,7 +3384,7 @@ void ggml_numa_init(enum ggml_numa_strategy numa_flag) { if (fptr != NULL) { char buf[42]; if (fgets(buf, sizeof(buf), fptr) && strncmp(buf, "0\n", sizeof(buf)) != 0) { - GGML_PRINT("WARNING: /proc/sys/kernel/numa_balancing is enabled, this has been observed to impair performance\n"); + GGML_LOG_WARN("/proc/sys/kernel/numa_balancing is enabled, this has been observed to impair performance\n"); } fclose(fptr); } @@ -3365,21 +3402,21 @@ bool ggml_is_numa(void) { //////////////////////////////////////////////////////////////////////////////// void ggml_print_object(const struct ggml_object * obj) { - GGML_PRINT(" - ggml_object: type = %d, offset = %zu, size = %zu, next = %p\n", + GGML_LOG_INFO(" - ggml_object: type = %d, offset = %zu, size = %zu, next = %p\n", obj->type, obj->offs, obj->size, (const void *) obj->next); } void ggml_print_objects(const struct ggml_context * ctx) { struct ggml_object * obj = ctx->objects_begin; - GGML_PRINT("%s: objects in context %p:\n", __func__, (const void *) ctx); + GGML_LOG_INFO("%s: objects in context %p:\n", __func__, (const void *) ctx); while (obj != NULL) { ggml_print_object(obj); obj = obj->next; } - GGML_PRINT("%s: --- end ---\n", __func__); + GGML_LOG_INFO("%s: --- end ---\n", __func__); } int64_t ggml_nelements(const struct ggml_tensor * tensor) { @@ -3962,7 +3999,7 @@ static struct ggml_object * ggml_new_object(struct ggml_context * ctx, enum ggml struct ggml_object * const obj_new = (struct ggml_object *)(mem_buffer + cur_end); if (cur_end + size_needed + GGML_OBJECT_SIZE > ctx->mem_size) { - GGML_PRINT("%s: not enough space in the context's memory pool (needed %zu, available %zu)\n", + GGML_LOG_WARN("%s: not enough space in the context's memory pool (needed %zu, available %zu)\n", __func__, cur_end + size_needed + GGML_OBJECT_SIZE, ctx->mem_size); assert(false); return NULL; @@ -4026,7 +4063,7 @@ static struct ggml_tensor * ggml_new_tensor_impl( if (ctx->scratch.data != NULL) { // allocate tensor data in the scratch buffer if (ctx->scratch.offs + data_size > ctx->scratch.size) { - GGML_PRINT("%s: not enough space in the scratch memory pool (needed %zu, available %zu)\n", + GGML_LOG_WARN("%s: not enough space in the scratch memory pool (needed %zu, available %zu)\n", __func__, ctx->scratch.offs + data_size, ctx->scratch.size); assert(false); return NULL; @@ -20013,7 +20050,7 @@ enum ggml_status ggml_graph_compute(struct ggml_cgraph * cgraph, struct ggml_cpl } #else if (n_threads > threadpool->n_threads_max) { - GGML_PRINT("WARNING: cplan requested more threads (%d) than available (%d)\n", n_threads, threadpool->n_threads_max); + GGML_LOG_WARN("cplan requested more threads (%d) than available (%d)\n", n_threads, threadpool->n_threads_max); n_threads = threadpool->n_threads_max; } @@ -20552,30 +20589,30 @@ struct ggml_cgraph * ggml_graph_import(const char * fname, struct ggml_context * } void ggml_graph_print(const struct ggml_cgraph * cgraph) { - GGML_PRINT("=== GRAPH ===\n"); + GGML_LOG_INFO("=== GRAPH ===\n"); - GGML_PRINT("n_nodes = %d\n", cgraph->n_nodes); + GGML_LOG_INFO("n_nodes = %d\n", cgraph->n_nodes); for (int i = 0; i < cgraph->n_nodes; i++) { struct ggml_tensor * node = cgraph->nodes[i]; - GGML_PRINT(" - %3d: [ %5" PRId64 ", %5" PRId64 ", %5" PRId64 "] %16s %s\n", + GGML_LOG_INFO(" - %3d: [ %5" PRId64 ", %5" PRId64 ", %5" PRId64 "] %16s %s\n", i, node->ne[0], node->ne[1], node->ne[2], ggml_op_name(node->op), (node->flags & GGML_TENSOR_FLAG_PARAM) ? "x" : node->grad ? "g" : " "); } - GGML_PRINT("n_leafs = %d\n", cgraph->n_leafs); + GGML_LOG_INFO("n_leafs = %d\n", cgraph->n_leafs); for (int i = 0; i < cgraph->n_leafs; i++) { struct ggml_tensor * node = cgraph->leafs[i]; - GGML_PRINT(" - %3d: [ %5" PRId64 ", %5" PRId64 "] %8s %16s\n", + GGML_LOG_INFO(" - %3d: [ %5" PRId64 ", %5" PRId64 "] %8s %16s\n", i, node->ne[0], node->ne[1], ggml_op_name(node->op), ggml_get_name(node)); } - GGML_PRINT("========================================\n"); + GGML_LOG_INFO("========================================\n"); } // check if node is part of the graph @@ -20746,7 +20783,7 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph fclose(fp); - GGML_PRINT("%s: dot -Tpng %s -o %s.png && open %s.png\n", __func__, filename, filename, filename); + GGML_LOG_INFO("%s: dot -Tpng %s -o %s.png && open %s.png\n", __func__, filename, filename, filename); } //////////////////////////////////////////////////////////////////////////////// @@ -23241,4 +23278,9 @@ int ggml_cpu_get_sve_cnt(void) { return 0; #endif } + +void ggml_log_set(ggml_log_callback log_callback, void * user_data) { + g_logger_state.log_callback = log_callback ? log_callback : ggml_log_callback_default; + g_logger_state.log_callback_user_data = user_data; +} //////////////////////////////////////////////////////////////////////////////// diff --git a/src/llama.cpp b/src/llama.cpp index 69ba65395..3443b0689 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -2266,17 +2266,12 @@ static std::string llama_token_to_piece(const struct llama_model * model, llama_ // globals // -struct llama_state { - llama_state() { - llama_log_set(log_callback, log_callback_user_data); - } - - // We save the log callback globally +struct llama_logger_state { ggml_log_callback log_callback = llama_log_callback_default; void * log_callback_user_data = nullptr; }; -static llama_state g_state; +static llama_logger_state g_logger_state; // available llama models enum e_model { @@ -21850,16 +21845,9 @@ const std::vector> & llama_internal } void llama_log_set(ggml_log_callback log_callback, void * user_data) { - g_state.log_callback = log_callback ? log_callback : llama_log_callback_default; - g_state.log_callback_user_data = user_data; - - ggml_backend_set_log_callback(log_callback, user_data); - -#ifdef GGML_USE_METAL - ggml_backend_metal_log_set_callback(g_state.log_callback, g_state.log_callback_user_data); -#elif defined(GGML_USE_CANN) - ggml_backend_cann_log_set_callback(g_state.log_callback, g_state.log_callback_user_data); -#endif + ggml_log_set(log_callback, user_data); + g_logger_state.log_callback = log_callback ? log_callback : llama_log_callback_default; + g_logger_state.log_callback_user_data = user_data; } static void llama_log_internal_v(ggml_log_level level, const char * format, va_list args) { @@ -21868,12 +21856,12 @@ static void llama_log_internal_v(ggml_log_level level, const char * format, va_l char buffer[128]; int len = vsnprintf(buffer, 128, format, args); if (len < 128) { - g_state.log_callback(level, buffer, g_state.log_callback_user_data); + g_logger_state.log_callback(level, buffer, g_logger_state.log_callback_user_data); } else { char * buffer2 = new char[len + 1]; vsnprintf(buffer2, len + 1, format, args_copy); buffer2[len] = 0; - g_state.log_callback(level, buffer2, g_state.log_callback_user_data); + g_logger_state.log_callback(level, buffer2, g_logger_state.log_callback_user_data); delete[] buffer2; } va_end(args_copy);