DarthAffe/stable-diffusion.cpp
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feat: use log_printf to print ggml logs (#545)

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clibdev 2025-09-11 17:16:05 +03:00 committed by GitHub
parent b017918106
commit 87cdbd5978
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4 changed files with 26 additions and 10 deletions
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26
ggml_extend.hpp
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@ -56,6 +56,25 @@
#define __STATIC_INLINE__ static inline #define __STATIC_INLINE__ static inline
#endif #endif
__STATIC_INLINE__ void ggml_log_callback_default(ggml_log_level level, const char* text, void*) {
switch (level) {
case GGML_LOG_LEVEL_DEBUG:
LOG_DEBUG(text);
break;
case GGML_LOG_LEVEL_INFO:
LOG_INFO(text);
break;
case GGML_LOG_LEVEL_WARN:
LOG_WARN(text);
break;
case GGML_LOG_LEVEL_ERROR:
LOG_ERROR(text);
break;
default:
LOG_DEBUG(text);
}
}
static_assert(GGML_MAX_NAME >= 128, "GGML_MAX_NAME must be at least 128"); static_assert(GGML_MAX_NAME >= 128, "GGML_MAX_NAME must be at least 128");
// n-mode trensor-matrix product // n-mode trensor-matrix product
@ -124,13 +143,6 @@ __STATIC_INLINE__ struct ggml_tensor* ggml_kronecker(ggml_context* ctx, struct g
b); b);
} }
__STATIC_INLINE__ void ggml_log_callback_default(ggml_log_level level, const char* text, void* user_data) {
(void)level;
(void)user_data;
fputs(text, stderr);
fflush(stderr);
}
__STATIC_INLINE__ void ggml_tensor_set_f32_randn(struct ggml_tensor* tensor, std::shared_ptr<RNG> rng) { __STATIC_INLINE__ void ggml_tensor_set_f32_randn(struct ggml_tensor* tensor, std::shared_ptr<RNG> rng) {
uint32_t n = (uint32_t)ggml_nelements(tensor); uint32_t n = (uint32_t)ggml_nelements(tensor);
std::vector<float> random_numbers = rng->randn(n); std::vector<float> random_numbers = rng->randn(n);

3
stable-diffusion.cpp
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@ -145,7 +145,6 @@ public:
#endif #endif
#ifdef SD_USE_METAL #ifdef SD_USE_METAL
LOG_DEBUG("Using Metal backend"); LOG_DEBUG("Using Metal backend");
ggml_log_set(ggml_log_callback_default, nullptr);
backend = ggml_backend_metal_init(); backend = ggml_backend_metal_init();
#endif #endif
#ifdef SD_USE_VULKAN #ifdef SD_USE_VULKAN
@ -192,6 +191,8 @@ public:
rng = std::make_shared<PhiloxRNG>(); rng = std::make_shared<PhiloxRNG>();
} }
ggml_log_set(ggml_log_callback_default, nullptr);
init_backend(); init_backend();
ModelLoader model_loader; ModelLoader model_loader;

2
upscaler.cpp
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@ -19,13 +19,13 @@ struct UpscalerGGML {
bool load_from_file(const std::string& esrgan_path, bool load_from_file(const std::string& esrgan_path,
bool offload_params_to_cpu) { bool offload_params_to_cpu) {
ggml_log_set(ggml_log_callback_default, nullptr);
#ifdef SD_USE_CUDA #ifdef SD_USE_CUDA
LOG_DEBUG("Using CUDA backend"); LOG_DEBUG("Using CUDA backend");
backend = ggml_backend_cuda_init(0); backend = ggml_backend_cuda_init(0);
#endif #endif
#ifdef SD_USE_METAL #ifdef SD_USE_METAL
LOG_DEBUG("Using Metal backend"); LOG_DEBUG("Using Metal backend");
ggml_log_set(ggml_log_callback_default, nullptr);
backend = ggml_backend_metal_init(); backend = ggml_backend_metal_init();
#endif #endif
#ifdef SD_USE_VULKAN #ifdef SD_USE_VULKAN

5
util.cpp
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@ -414,7 +414,10 @@ void log_printf(sd_log_level_t level, const char* file, int line, const char* fo
if (written >= 0 && written < LOG_BUFFER_SIZE) { if (written >= 0 && written < LOG_BUFFER_SIZE) {
vsnprintf(log_buffer + written, LOG_BUFFER_SIZE - written, format, args); vsnprintf(log_buffer + written, LOG_BUFFER_SIZE - written, format, args);
} }
strncat(log_buffer, "\n", LOG_BUFFER_SIZE - strlen(log_buffer)); size_t len = strlen(log_buffer);
if (log_buffer[len - 1] != '\n') {
strncat(log_buffer, "\n", LOG_BUFFER_SIZE - len);
}
if (sd_log_cb) { if (sd_log_cb) {
sd_log_cb(level, log_buffer, sd_log_cb_data); sd_log_cb(level, log_buffer, sd_log_cb_data);