chore: silence narrowing conversion warnings (#1717)

src/model/diffusion/sefi_image.hpp

@@ -76,8 +76,8 @@ namespace SefiImage {
             auto semantic_embedder = std::dynamic_pointer_cast<SefiTimestepEmbedding>(blocks["semantic_embedder"]);
             auto texture_embedder  = std::dynamic_pointer_cast<SefiTimestepEmbedding>(blocks["texture_embedder"]);
 
-            auto sem_proj = ggml_ext_timestep_embedding(ctx->ggml_ctx, timestep_sem, timestep_guidance_in_dim, 10000, 1.f);
+            auto sem_proj = ggml_ext_timestep_embedding(ctx->ggml_ctx, timestep_sem, (int)timestep_guidance_in_dim, 10000, 1.f);
-            auto tex_proj = ggml_ext_timestep_embedding(ctx->ggml_ctx, timestep_tex, timestep_guidance_in_dim, 10000, 1.f);
+            auto tex_proj = ggml_ext_timestep_embedding(ctx->ggml_ctx, timestep_tex, (int)timestep_guidance_in_dim, 10000, 1.f);
             auto sem_emb  = semantic_embedder->forward(ctx, sem_proj);
             auto tex_emb  = texture_embedder->forward(ctx, tex_proj);
             return ggml_concat(ctx->ggml_ctx, sem_emb, tex_emb, 0);

src/model/vae/wan_vae.hpp

@@ -113,14 +113,13 @@ namespace WAN {
         }
     };
 
-
     class Conv2dBut3d : public Conv2d {
     public:
         using Conv2d::Conv2d;
 
         ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) {
             ggml_tensor* x_swapped = ggml_permute(ctx->ggml_ctx, x, 0, 1, 3, 2);
-            x_swapped = ggml_cont(ctx->ggml_ctx, x_swapped);
+            x_swapped              = ggml_cont(ctx->ggml_ctx, x_swapped);
 
             ggml_tensor* out = Conv2d::forward(ctx, x_swapped);
 
@@ -132,7 +131,6 @@ namespace WAN {
         }
     };
 
-
     class Resample : public GGMLBlock {
     protected:
         int64_t dim;
@@ -397,7 +395,7 @@ namespace WAN {
             ggml_tensor* h = x;
             if (in_dim != out_dim) {
                 if (is_2D) {
-                   auto shortcut = std::dynamic_pointer_cast<Conv2dBut3d>(blocks["shortcut"]);
+                    auto shortcut = std::dynamic_pointer_cast<Conv2dBut3d>(blocks["shortcut"]);
 
                     h = shortcut->forward(ctx, x);
                 } else {
@@ -843,9 +841,9 @@ namespace WAN {
             }
 
             // init block
-            if(is_2D){
+            if (is_2D) {
                 blocks["conv1"] = std::shared_ptr<GGMLBlock>(new Conv2dBut3d(z_dim, dims[0], {3, 3}, {1, 1}, {1, 1}));
-            }else{
+            } else {
                 blocks["conv1"] = std::shared_ptr<GGMLBlock>(new CausalConv3d(z_dim, dims[0], {3, 3, 3}, {1, 1, 1}, {1, 1, 1}));
             }
 
@@ -890,7 +888,7 @@ namespace WAN {
             }
 
             // output blocks
-            blocks["head.0"] = std::shared_ptr<GGMLBlock>(new RMS_norm(out_dim));
+            blocks["head.0"]  = std::shared_ptr<GGMLBlock>(new RMS_norm(out_dim));
             int64_t final_dim = wan2_2 ? 12 : 3;
             // head.1 is nn.SiLU()
             if (is_2D) {
@@ -919,7 +917,7 @@ namespace WAN {
             // conv1
             if (is_2D) {
                 auto conv1 = std::dynamic_pointer_cast<Conv2dBut3d>(blocks["conv1"]);
-                x     = conv1->forward(ctx, x);
+                x          = conv1->forward(ctx, x);
             } else if (feat_cache.size() > 0) {
                 int idx      = feat_idx;
                 auto cache_x = ggml_ext_slice(ctx->ggml_ctx, x, 2, -CACHE_T, x->ne[2]);
@@ -1011,7 +1009,7 @@ namespace WAN {
         int num_res_blocks                    = 2;
         std::vector<bool> temperal_upsample   = {true, true, false};
         std::vector<bool> temperal_downsample = {false, true, true};
-        bool is_2D = false;
+        bool is_2D                            = false;
 
         int _conv_num = 33;
         int _conv_idx = 0;
@@ -1040,8 +1038,8 @@ namespace WAN {
                 _enc_conv_num = 26;
             }
 
-            if(is_2D){
+            if (is_2D) {
-                temperal_upsample = {false, false, false};
+                temperal_upsample   = {false, false, false};
                 temperal_downsample = {false, false, false};
             }
 
@@ -1149,7 +1147,7 @@ namespace WAN {
                 auto conv1 = std::dynamic_pointer_cast<Conv2dBut3d>(blocks["conv1"]);
                 out        = conv1->forward(ctx, out);
             } else {
-                out     = conv1->forward(ctx, out);
+                out = conv1->forward(ctx, out);
             }
             auto mu = ggml_ext_chunk(ctx->ggml_ctx, out, 2, 3)[0];
             // sd::ggml_graph_cut::mark_graph_cut(mu, "wan_vae.encode.final", "mu");
@@ -1170,9 +1168,9 @@ namespace WAN {
 
             int64_t iter_ = z->ne[2];
             auto x        = z;
-            if(is_2D){
+            if (is_2D) {
-                auto conv2   = std::dynamic_pointer_cast<Conv2dBut3d>(blocks["conv2"]);
+                auto conv2 = std::dynamic_pointer_cast<Conv2dBut3d>(blocks["conv2"]);
-                x = conv2->forward(ctx, z);
+                x          = conv2->forward(ctx, z);
             } else {
                 x = conv2->forward(ctx, z);
             }

src/name_conversion.cpp

@@ -914,7 +914,6 @@ std::string convert_diffusers_to_original_wan_vae(std::string name) {
         replace_with_name_map(name, resnet_name_map);
     }
 
-    
     return name;
 }
 

src/runtime/denoiser.hpp

@@ -602,7 +602,7 @@ struct LogitNormalScheduler : SigmaScheduler {
             }
         }
         if (image_seq_len > 0 && resolution_aware) {
-            mean += 0.5 * std::log(static_cast<float>(image_seq_len) / static_cast<float>(known_seq_len));
+            mean += 0.5f * std::log(static_cast<float>(image_seq_len) / static_cast<float>(known_seq_len));
         }
     }
 
@@ -735,7 +735,7 @@ struct LogitNormalScheduler : SigmaScheduler {
             float t = static_cast<float>(i) / static_cast<float>(n);
 
             // ndtri(1-t) == -ndtri(t)
-            float z = -ndtri(t);
+            float z = static_cast<float>(-ndtri(t));
 
             float y = mean + std * z;