fix: fix building shared library (#188)

.gitmodules

@@ -1,3 +1,3 @@
 [submodule "ggml"]
     path = ggml
-	url = https://github.com/ggerganov/ggml.git
+	url = https://github.com/leejet/ggml.git

CMakeLists.txt

@@ -69,14 +69,15 @@ file(GLOB SD_LIB_SOURCES
 # we can get only one share lib
 if(SD_BUILD_SHARED_LIBS)
     message("Build shared library")
-    set(BUILD_SHARED_LIBS OFF)
     message(${SD_LIB_SOURCES})
+    set(BUILD_SHARED_LIBS OFF)
     add_library(${SD_LIB} SHARED ${SD_LIB_SOURCES})
     add_definitions(-DSD_BUILD_SHARED_LIB)
     target_compile_definitions(${SD_LIB} PRIVATE -DSD_BUILD_DLL)
     set(CMAKE_POSITION_INDEPENDENT_CODE ON)
 else()
     message("Build static library")
+    set(BUILD_SHARED_LIBS OFF)
     add_library(${SD_LIB} STATIC ${SD_LIB_SOURCES})
 endif()
 

clip.hpp

@@ -891,6 +891,10 @@ struct FrozenCLIPEmbedderWithCustomWords : public GGMLModule {
             LOG_ERROR("embedding '%s' failed", embd_name.c_str());
             return false;
         }
+        if (std::find(readed_embeddings.begin(), readed_embeddings.end(), embd_name) != readed_embeddings.end()) {
+            LOG_DEBUG("embedding already read in: %s", embd_name.c_str());
+            return true;
+        }
         struct ggml_init_params params;
         params.mem_size               = 10 * 1024 * 1024;  // max for custom embeddings 10 MB
         params.mem_buffer             = NULL;

ggml_extend.hpp

@@ -846,7 +846,7 @@ public:
             return NULL;
         }
         // it's performing a compute, check if backend isn't cpu
-        if (!ggml_backend_is_cpu(backend) && tensor->backend == GGML_BACKEND_CPU) {
+        if (!ggml_backend_is_cpu(backend) && tensor->backend == GGML_BACKEND_TYPE_CPU) {
             // pass input tensors to gpu memory
             auto backend_tensor = ggml_dup_tensor(compute_ctx, tensor);
 

lora.hpp

@@ -33,6 +33,7 @@ struct LoraModel : public GGMLModule {
         return model_loader.get_params_mem_size(NULL);
     }
 
+
     bool load_from_file() {
         LOG_INFO("loading LoRA from '%s'", file_path.c_str());
 
@@ -55,6 +56,7 @@ struct LoraModel : public GGMLModule {
                 auto real   = lora_tensors[name];
                 *dst_tensor = real;
             }
+
             return true;
         };
 
@@ -64,6 +66,7 @@ struct LoraModel : public GGMLModule {
         dry_run = false;
         model_loader.load_tensors(on_new_tensor_cb, backend);
 
+
         LOG_DEBUG("finished loaded lora");
         return true;
     }

stable-diffusion.h

@@ -65,17 +65,20 @@ enum sd_type_t {
     SD_TYPE_Q8_0 = 8,
     SD_TYPE_Q8_1 = 9,
     // k-quantizations
-    SD_TYPE_Q2_K    = 10,
-    SD_TYPE_Q3_K    = 11,
-    SD_TYPE_Q4_K    = 12,
-    SD_TYPE_Q5_K    = 13,
-    SD_TYPE_Q6_K    = 14,
-    SD_TYPE_Q8_K    = 15,
+    SD_TYPE_Q2_K = 10,
+    SD_TYPE_Q3_K = 11,
+    SD_TYPE_Q4_K = 12,
+    SD_TYPE_Q5_K = 13,
+    SD_TYPE_Q6_K = 14,
+    SD_TYPE_Q8_K = 15,
     SD_TYPE_IQ2_XXS = 16,
     SD_TYPE_IQ2_XS  = 17,
     SD_TYPE_IQ3_XXS = 18,
     SD_TYPE_IQ1_S   = 19,
     SD_TYPE_IQ4_NL  = 20,
+    SD_TYPE_IQ3_S   = 21,
+    SD_TYPE_IQ2_S   = 22,
+    SD_TYPE_IQ4_XS  = 23,
     SD_TYPE_I8,
     SD_TYPE_I16,
     SD_TYPE_I32,
@@ -92,8 +95,10 @@ enum sd_log_level_t {
 };
 
 typedef void (*sd_log_cb_t)(enum sd_log_level_t level, const char* text, void* data);
+typedef void (*sd_progress_cb_t)(int step,int steps,float time, void* data);
 
 SD_API void sd_set_log_callback(sd_log_cb_t sd_log_cb, void* data);
+SD_API void sd_set_progress_callback(sd_progress_cb_t cb, void* data);
 SD_API int32_t get_num_physical_cores();
 SD_API const char* sd_get_system_info();
 

util.cpp

@@ -161,6 +161,9 @@ int32_t get_num_physical_cores() {
     return n_threads > 0 ? (n_threads <= 4 ? n_threads : n_threads / 2) : 4;
 }
 
+static sd_progress_cb_t sd_progress_cb  = NULL;
+void* sd_progress_cb_data               = NULL;
+
 std::u32string utf8_to_utf32(const std::string& utf8_str) {
     std::wstring_convert<std::codecvt_utf8<char32_t>, char32_t> converter;
     return converter.from_bytes(utf8_str);
@@ -205,6 +208,10 @@ std::string path_join(const std::string& p1, const std::string& p2) {
 }
 
 void pretty_progress(int step, int steps, float time) {
+    if (sd_progress_cb) {
+        sd_progress_cb(step,steps,time, sd_progress_cb_data);
+        return;
+    }
     if (step == 0) {
         return;
     }
@@ -248,8 +255,9 @@ std::string trim(const std::string& s) {
     return rtrim(ltrim(s));
 }
 
-static sd_log_cb_t sd_log_cb = NULL;
-void* sd_log_cb_data         = NULL;
+static sd_log_cb_t sd_log_cb            = NULL;
+void* sd_log_cb_data                    = NULL;
+
 
 #define LOG_BUFFER_SIZE 1024
 
@@ -286,7 +294,10 @@ void sd_set_log_callback(sd_log_cb_t cb, void* data) {
     sd_log_cb      = cb;
     sd_log_cb_data = data;
 }
-
+void sd_set_progress_callback(sd_progress_cb_t cb, void* data) {
+    sd_progress_cb      = cb;
+    sd_progress_cb_data = data;
+}
 const char* sd_get_system_info() {
     static char buffer[1024];
     std::stringstream ss;

vae.hpp

@@ -6,7 +6,7 @@
 
 /*================================================== AutoEncoderKL ===================================================*/
 
-#define VAE_GRAPH_SIZE 10240
+#define VAE_GRAPH_SIZE 20480
 
 class ResnetBlock : public UnaryBlock {
 protected: