format code

Author: stduhpf

examples/cli/main.cpp

@@ -828,11 +828,10 @@ void parse_args(int argc, const char** argv, SDParams& params) {
          "--taesd-preview-only",
          std::string("prevents usage of taesd for decoding the final image. (for use with --preview ") + previews_str[PREVIEW_TAE] + ")",
          true, &params.taesd_preview},
-         {"",
-        "--preview-noisy",
-        "enables previewing noisy inputs of the models rather than the denoised outputs",
-        true, &params.preview_noisy}
-    };
+        {"",
+         "--preview-noisy",
+         "enables previewing noisy inputs of the models rather than the denoised outputs",
+         true, &params.preview_noisy}};
 
     auto on_mode_arg = [&](int argc, const char** argv, int index) {
         if (++index >= argc) {

latent-preview.h

@@ -126,7 +126,7 @@ const float sd_latent_rgb_proj[4][3]{
     {0.3250f, 0.4974f, 0.2350f},
     {-0.2829f, 0.1762f, 0.2721f},
     {-0.2120f, -0.2616f, -0.7177f}};
-float sd_latent_rgb_bias[3] = {0,0,0};
+float sd_latent_rgb_bias[3] = {0, 0, 0};
 
 void preview_latent_video(uint8_t* buffer, struct ggml_tensor* latents, const float (*latent_rgb_proj)[3], const float latent_rgb_bias[3], int width, int height, int frames, int dim) {
     size_t buffer_head = 0;
@@ -135,7 +135,7 @@ void preview_latent_video(uint8_t* buffer, struct ggml_tensor* latents, const fl
             for (int i = 0; i < width; i++) {
                 size_t latent_id = (i * latents->nb[0] + j * latents->nb[1] + k * latents->nb[2]);
                 float r = 0, g = 0, b = 0;
-                if(latent_rgb_proj!=NULL){
+                if (latent_rgb_proj != NULL) {
                     for (int d = 0; d < dim; d++) {
                         float value = *(float*)((char*)latents->data + latent_id + d * latents->nb[ggml_n_dims(latents) - 1]);
                         r += value * latent_rgb_proj[d][0];
@@ -148,7 +148,7 @@ void preview_latent_video(uint8_t* buffer, struct ggml_tensor* latents, const fl
                     g = *(float*)((char*)latents->data + latent_id + 1 * latents->nb[ggml_n_dims(latents) - 1]);
                     b = *(float*)((char*)latents->data + latent_id + 2 * latents->nb[ggml_n_dims(latents) - 1]);
                 }
-                if(latent_rgb_bias!=NULL){
+                if (latent_rgb_bias != NULL) {
                     // bias
                     r += latent_rgb_bias[0];
                     g += latent_rgb_bias[1];

stable-diffusion.cpp

@@ -369,7 +369,7 @@ class StableDiffusionGGML {
                 diffusion_model  = std::make_shared<MMDiTModel>(backend,
                                                                 offload_params_to_cpu,
                                                                 sd_ctx_params->diffusion_flash_attn,
-                                                               model_loader.tensor_storages_types);
+                                                                model_loader.tensor_storages_types);
             } else if (sd_version_is_flux(version)) {
                 bool is_chroma = false;
                 for (auto pair : model_loader.tensor_storages_types) {
@@ -443,11 +443,11 @@ class StableDiffusionGGML {
                                                                             "",
                                                                             enable_vision);
                 diffusion_model  = std::make_shared<QwenImageModel>(backend,
-                                                                   offload_params_to_cpu,
-                                                                   model_loader.tensor_storages_types,
-                                                                   "model.diffusion_model",
-                                                                   version,
-                                                                   sd_ctx_params->diffusion_flash_attn);
+                                                                    offload_params_to_cpu,
+                                                                    model_loader.tensor_storages_types,
+                                                                    "model.diffusion_model",
+                                                                    version,
+                                                                    sd_ctx_params->diffusion_flash_attn);
             } else {  // SD1.x SD2.x SDXL
                 if (strstr(SAFE_STR(sd_ctx_params->photo_maker_path), "v2")) {
                     cond_stage_model = std::make_shared<FrozenCLIPEmbedderWithCustomWords>(clip_backend,
@@ -1157,7 +1157,7 @@ class StableDiffusionGGML {
 
         if (preview_mode == PREVIEW_PROJ) {
             const float (*latent_rgb_proj)[channel] = NULL;
-            float *latent_rgb_bias = NULL;
+            float* latent_rgb_bias                  = NULL;
 
             if (dim == 48) {
                 if (sd_version_is_wan(version)) {
@@ -1214,7 +1214,7 @@ class StableDiffusionGGML {
 
             uint8_t* data = (uint8_t*)malloc(frames * width * height * channel * sizeof(uint8_t));
 
-            preview_latent_video(data, latents, latent_rgb_proj,latent_rgb_bias, width, height, frames, dim);
+            preview_latent_video(data, latents, latent_rgb_proj, latent_rgb_bias, width, height, frames, dim);
             sd_image_t* images = (sd_image_t*)malloc(frames * sizeof(sd_image_t));
             for (int i = 0; i < frames; i++) {
                 images[i] = {width, height, channel, data + i * width * height * channel};
@@ -1274,7 +1274,7 @@ class StableDiffusionGGML {
             }
 
             step_callback(step, frames, images, is_noisy);
-            
+
             ggml_tensor_scale(result, 0);
             for (int i = 0; i < frames; i++) {
                 free(images[i].data);