sync : llama.cpp

examples/gpt-2/main-backend.cpp

@@ -178,6 +178,8 @@ bool gpt2_model_load(const std::string & fname, gpt2_model & model, gpt_vocab &
         return false;
     }
 
+    ggml_log_set(ggml_log_callback_default, nullptr);
+
     auto & ctx = model.ctx_w;
 
     // create the ggml context
@@ -210,7 +212,6 @@ bool gpt2_model_load(const std::string & fname, gpt2_model & model, gpt_vocab &
 #ifdef GGML_USE_METAL
     if (n_gpu_layers > 0) {
         fprintf(stderr, "%s: using Metal backend\n", __func__);
-        ggml_backend_metal_log_set_callback(ggml_log_callback_default, nullptr);
         model.backend = ggml_backend_metal_init();
         if (!model.backend) {
             fprintf(stderr, "%s: ggml_backend_metal_init() failed\n", __func__);

examples/gpt-2/main-batched.cpp

@@ -268,6 +268,8 @@ bool gpt2_model_load(const std::string & fname, gpt2_model & model, gpt_vocab &
         printf("%s: backend buffer size = %6.2f MB\n", __func__, buffer_size/(1024.0*1024.0));
     }
 
+    ggml_log_set(ggml_log_callback_default, nullptr);
+
     // create the ggml context
     {
         size_t n_tensors = 2 + 6 + 12*model.hparams.n_layer;
@@ -298,7 +300,6 @@ bool gpt2_model_load(const std::string & fname, gpt2_model & model, gpt_vocab &
 #ifdef GGML_USE_METAL
     if (n_gpu_layers > 0) {
         fprintf(stderr, "%s: using Metal backend\n", __func__);
-        ggml_backend_metal_log_set_callback(ggml_log_callback_default, nullptr);
         model.backend = ggml_backend_metal_init();
         if (!model.backend) {
             fprintf(stderr, "%s: ggml_backend_metal_init() failed\n", __func__);

examples/gpt-2/main-sched.cpp

@@ -108,6 +108,8 @@ struct gpt2_model {
 void init_backends(gpt2_model & model, const gpt_params & params) {
     ggml_backend_t gpu_backend = NULL;
 
+    ggml_log_set(ggml_log_callback_default, nullptr);
+
     // initialize the backends
 #ifdef GGML_USE_CUDA
     if (params.n_gpu_layers > 0) {
@@ -122,7 +124,6 @@ void init_backends(gpt2_model & model, const gpt_params & params) {
 #ifdef GGML_USE_METAL
     if (params.n_gpu_layers > 0) {
         fprintf(stderr, "%s: using Metal backend\n", __func__);
-        ggml_backend_metal_log_set_callback(ggml_log_callback_default, nullptr);
         gpu_backend = ggml_backend_metal_init();
         if (!gpu_backend) {
             fprintf(stderr, "%s: ggml_backend_metal_init() failed\n", __func__);

examples/mnist/mnist-common.h

@@ -57,17 +57,18 @@ struct mnist_model {
     ggml_backend_buffer_t buf_compute = nullptr;
 
     mnist_model(const std::string & backend_name) {
-        const size_t backend_index = ggml_backend_reg_find_by_name(backend_name.c_str());
-        if (backend_index == SIZE_MAX) {
+        const ggml_backend_dev_t dev = ggml_backend_dev_by_name(backend_name.c_str());
+        if (dev == nullptr) {
             fprintf(stderr, "%s: ERROR: backend %s not found, available:\n", __func__, backend_name.c_str());
-            for (size_t i = 0; i < ggml_backend_reg_get_count(); ++i) {
-                fprintf(stderr, "  - %s\n", ggml_backend_reg_get_name(i));
+            for (size_t i = 0; i < ggml_backend_reg_count(); ++i) {
+                fprintf(stderr, "  - %s\n", ggml_backend_reg_name(ggml_backend_reg_get(i)));
             }
             exit(1);
         }
 
         fprintf(stderr, "%s: using %s backend\n", __func__, backend_name.c_str());
-        backend = ggml_backend_reg_init_backend(backend_index, nullptr);
+
+        ggml_backend_t backend = ggml_backend_dev_init(dev, NULL);
         if (ggml_backend_is_cpu(backend)) {
             const int ncores_logical = std::thread::hardware_concurrency();
             ggml_backend_cpu_set_n_threads(backend, std::min(ncores_logical, (ncores_logical + 4)/2));

examples/simple/simple-backend.cpp

@@ -43,6 +43,8 @@ struct simple_model {
 
 // initialize the tensors of the model in this case two matrices 2x2
 void load_model(simple_model & model, float * a, float * b, int rows_A, int cols_A, int rows_B, int cols_B) {
+    ggml_log_set(ggml_log_callback_default, nullptr);
+
     // initialize the backend
 #ifdef GGML_USE_CUDA
     fprintf(stderr, "%s: using CUDA backend\n", __func__);
@@ -54,7 +56,6 @@ void load_model(simple_model & model, float * a, float * b, int rows_A, int cols
 
 #ifdef GGML_USE_METAL
     fprintf(stderr, "%s: using Metal backend\n", __func__);
-    ggml_backend_metal_log_set_callback(ggml_log_callback_default, nullptr);
     model.backend = ggml_backend_metal_init();
     if (!model.backend) {
         fprintf(stderr, "%s: ggml_backend_metal_init() failed\n", __func__);

include/ggml-blas.h

@@ -9,13 +9,13 @@ extern "C" {
 #endif
 
 // backend API
-GGML_API GGML_CALL ggml_backend_t ggml_backend_blas_init(void);
+GGML_API ggml_backend_t ggml_backend_blas_init(void);
 
-GGML_API GGML_CALL bool ggml_backend_is_blas(ggml_backend_t backend);
+GGML_API bool ggml_backend_is_blas(ggml_backend_t backend);
 
 // number of threads used for conversion to float
 // for openblas and blis, this will also set the number of threads used for blas operations
-GGML_API GGML_CALL void ggml_backend_blas_set_n_threads(ggml_backend_t backend_blas, int n_threads);
+GGML_API void ggml_backend_blas_set_n_threads(ggml_backend_t backend_blas, int n_threads);
 
 
 #ifdef  __cplusplus

include/ggml-cann.h

@@ -44,7 +44,7 @@ extern "C" {
  * @param device The index of the device to initialize.
  * @return A pointer to the initialized backend instance, or nullptr on failure.
  */
-GGML_API GGML_CALL ggml_backend_t ggml_backend_cann_init(int32_t device);
+GGML_API ggml_backend_t ggml_backend_cann_init(int32_t device);
 
 /**
  * @brief Checks if a given backend is a CANN backend.
@@ -55,7 +55,7 @@ GGML_API GGML_CALL ggml_backend_t ggml_backend_cann_init(int32_t device);
  * @param backend The backend instance to check.
  * @return True if the backend is a CANN backend, false otherwise.
  */
-GGML_API GGML_CALL bool ggml_backend_is_cann(ggml_backend_t backend);
+GGML_API bool ggml_backend_is_cann(ggml_backend_t backend);
 
 /**
  * @brief Retrieves the CANN buffer type for a specified device.
@@ -67,7 +67,7 @@ GGML_API GGML_CALL bool ggml_backend_is_cann(ggml_backend_t backend);
  * @return A pointer to the buffer type interface for the specified device, or
  * nullptr if the device index is out of range.
  */
-GGML_API GGML_CALL ggml_backend_buffer_type_t
+GGML_API ggml_backend_buffer_type_t
 ggml_backend_cann_buffer_type(int32_t device);
 
 /**
@@ -78,14 +78,14 @@ ggml_backend_cann_buffer_type(int32_t device);
  *
  * @return The number of CANN devices available.
  */
-GGML_API GGML_CALL int32_t ggml_backend_cann_get_device_count(void);
+GGML_API int32_t ggml_backend_cann_get_device_count(void);
 
 /**
  * @brief pinned host buffer for use with the CPU backend for faster copies between CPU and NPU.
  *
  * @return A pointer to the host buffer type interface.
  */
-GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cann_host_buffer_type(void);
+GGML_API ggml_backend_buffer_type_t ggml_backend_cann_host_buffer_type(void);
 
 /**
  * @brief Retrieves the description of a specific CANN device.
@@ -97,7 +97,7 @@ GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cann_host_buffer_type
  * @param description Pointer to a buffer where the description will be written.
  * @param description_size Size of the description buffer.
  */
-GGML_API GGML_CALL void ggml_backend_cann_get_device_description(
+GGML_API void ggml_backend_cann_get_device_description(
     int32_t device, char* description, size_t description_size);
 
 /**
@@ -112,20 +112,9 @@ GGML_API GGML_CALL void ggml_backend_cann_get_device_description(
  * @param total Pointer to a variable where the total memory size will be
  * stored.
  */
-GGML_API GGML_CALL 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);
+GGML_API void ggml_backend_cann_get_device_memory(int32_t device,
+                                                  size_t* free,
+                                                  size_t* total);
 
 #ifdef __cplusplus
 }

include/ggml-cuda.h

@@ -3,6 +3,10 @@
 #include "ggml.h"
 #include "ggml-backend.h"
 
+#ifdef  __cplusplus
+extern "C" {
+#endif
+
 #ifdef GGML_USE_HIPBLAS
 #define GGML_CUDA_NAME "ROCm"
 #define GGML_CUBLAS_NAME "hipBLAS"
@@ -13,35 +17,31 @@
 #define GGML_CUDA_NAME "CUDA"
 #define GGML_CUBLAS_NAME "cuBLAS"
 #endif
-
-#ifdef  __cplusplus
-extern "C" {
-#endif
-
 #define GGML_CUDA_MAX_DEVICES       16
 
 // backend API
-GGML_API GGML_CALL ggml_backend_t ggml_backend_cuda_init(int device);
+GGML_API ggml_backend_t ggml_backend_cuda_init(int device);
 
-GGML_API GGML_CALL bool ggml_backend_is_cuda(ggml_backend_t backend);
+GGML_API bool ggml_backend_is_cuda(ggml_backend_t backend);
 
 // device buffer
-GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device);
+GGML_API ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device);
 
 // split tensor buffer that splits matrices by rows across multiple devices
-GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const float * tensor_split);
+GGML_API ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const float * tensor_split);
 
 // pinned host buffer for use with the CPU backend for faster copies between CPU and GPU
-GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type(void);
+GGML_API ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type(void);
+
+GGML_API int  ggml_backend_cuda_get_device_count(void);
+GGML_API void ggml_backend_cuda_get_device_description(int device, char * description, size_t description_size);
+GGML_API void ggml_backend_cuda_get_device_memory(int device, size_t * free, size_t * total);
 
-GGML_API GGML_CALL int  ggml_backend_cuda_get_device_count(void);
-GGML_API GGML_CALL void ggml_backend_cuda_get_device_description(int device, char * description, size_t description_size);
-GGML_API GGML_CALL void ggml_backend_cuda_get_device_memory(int device, size_t * free, size_t * total);
+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 GGML_CALL bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size);
-GGML_API GGML_CALL void ggml_backend_cuda_unregister_host_buffer(void * buffer);
+GGML_API ggml_backend_reg_t ggml_backend_cuda_reg(void);
 
-GGML_API void ggml_backend_cuda_log_set_callback(ggml_log_callback log_callback, void * user_data);
 #ifdef  __cplusplus
 }
 #endif

include/ggml-metal.h

@@ -1,3 +1,5 @@
+// Note: this description is outdated
+//
 // An interface allowing to compute ggml_cgraph with Metal
 //
 // This is a fully functional interface that extends ggml with GPU support for Apple devices.
@@ -37,17 +39,15 @@ 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);
 
-GGML_API GGML_CALL ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t size, size_t max_size);
+GGML_API ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t size, size_t max_size);
 
 GGML_API void ggml_backend_metal_set_abort_callback(ggml_backend_t backend, ggml_abort_callback abort_callback, void * user_data);
 
-GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void);
+GGML_API ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void);
 
 // helper to check if the device supports a specific family
 // ideally, the user code should be doing these checks

include/ggml-rpc.h

@@ -10,14 +10,14 @@ extern "C" {
 #define GGML_RPC_MAX_SERVERS       16
 
 // backend API
-GGML_API GGML_CALL ggml_backend_t ggml_backend_rpc_init(const char * endpoint);
-GGML_API GGML_CALL bool ggml_backend_is_rpc(ggml_backend_t backend);
+GGML_API ggml_backend_t ggml_backend_rpc_init(const char * endpoint);
+GGML_API bool ggml_backend_is_rpc(ggml_backend_t backend);
 
-GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_rpc_buffer_type(const char * endpoint);
+GGML_API ggml_backend_buffer_type_t ggml_backend_rpc_buffer_type(const char * endpoint);
 
-GGML_API GGML_CALL void ggml_backend_rpc_get_device_memory(const char * endpoint, size_t * free, size_t * total);
+GGML_API void ggml_backend_rpc_get_device_memory(const char * endpoint, size_t * free, size_t * total);
 
-GGML_API GGML_CALL void start_rpc_server(ggml_backend_t backend, const char * endpoint, size_t free_mem, size_t total_mem);
+GGML_API void start_rpc_server(ggml_backend_t backend, const char * endpoint, size_t free_mem, size_t total_mem);
 
 #ifdef  __cplusplus
 }

include/ggml-sycl.h

@@ -23,20 +23,20 @@ GGML_API ggml_backend_t ggml_backend_sycl_init(int device);
 GGML_API ggml_backend_buffer_type_t ggml_backend_sycl_buffer_type(int device);
 
 // split tensor buffer that splits matrices by rows across multiple devices
-GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_sycl_split_buffer_type(const float * tensor_split);
+GGML_API ggml_backend_buffer_type_t ggml_backend_sycl_split_buffer_type(const float * tensor_split);
 
 // pinned host buffer for use with the CPU backend for faster copies between CPU and GPU
 GGML_API ggml_backend_buffer_type_t ggml_backend_sycl_host_buffer_type(void);
 
-GGML_API void   ggml_backend_sycl_print_sycl_devices(void);
-GGML_API GGML_CALL void   ggml_sycl_get_gpu_list(int *id_list, int max_len);
-GGML_API GGML_CALL void   ggml_sycl_get_device_description(int device, char *description, size_t description_size);
-GGML_API GGML_CALL int   ggml_backend_sycl_get_device_count();
-GGML_API GGML_CALL void ggml_backend_sycl_get_device_memory(int device, size_t *free, size_t *total);
+GGML_API void ggml_backend_sycl_print_sycl_devices(void);
+GGML_API void ggml_sycl_get_gpu_list(int *id_list, int max_len);
+GGML_API void ggml_sycl_get_device_description(int device, char *description, size_t description_size);
+GGML_API int  ggml_backend_sycl_get_device_count();
+GGML_API void ggml_backend_sycl_get_device_memory(int device, size_t *free, size_t *total);
 
 // SYCL doesn't support registering host memory, keep here for reference
-// GGML_API GGML_CALL bool ggml_backend_sycl_register_host_buffer(void * buffer, size_t size);
-// GGML_API GGML_CALL void ggml_backend_sycl_unregister_host_buffer(void * buffer);
+// GGML_API bool ggml_backend_sycl_register_host_buffer(void * buffer, size_t size);
+// GGML_API void ggml_backend_sycl_unregister_host_buffer(void * buffer);
 #ifdef  __cplusplus
 }
 #endif

include/ggml-vulkan.h

@@ -13,16 +13,16 @@ extern "C" {
 GGML_API void ggml_vk_instance_init(void);
 
 // backend API
-GGML_API GGML_CALL ggml_backend_t ggml_backend_vk_init(size_t dev_num);
+GGML_API ggml_backend_t ggml_backend_vk_init(size_t dev_num);
 
-GGML_API GGML_CALL bool ggml_backend_is_vk(ggml_backend_t backend);
-GGML_API GGML_CALL int  ggml_backend_vk_get_device_count(void);
-GGML_API GGML_CALL void ggml_backend_vk_get_device_description(int device, char * description, size_t description_size);
-GGML_API GGML_CALL void ggml_backend_vk_get_device_memory(int device, size_t * free, size_t * total);
+GGML_API bool ggml_backend_is_vk(ggml_backend_t backend);
+GGML_API int  ggml_backend_vk_get_device_count(void);
+GGML_API void ggml_backend_vk_get_device_description(int device, char * description, size_t description_size);
+GGML_API void ggml_backend_vk_get_device_memory(int device, size_t * free, size_t * total);
 
-GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_buffer_type(size_t dev_num);
+GGML_API ggml_backend_buffer_type_t ggml_backend_vk_buffer_type(size_t dev_num);
 // pinned host buffer for use with the CPU backend for faster copies between CPU and GPU
-GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_host_buffer_type(void);
+GGML_API ggml_backend_buffer_type_t ggml_backend_vk_host_buffer_type(void);
 
 #ifdef  __cplusplus
 }