feat: add wan2.1/2.2 support (#778)

* add wan vae suppport

* add wan model support

* add umt5 support

* add wan2.1 t2i support

* make flash attn work with wan

* make wan a little faster

* add wan2.1 t2v support

* add wan gguf support

* add offload params to cpu support

* add wan2.1 i2v support

* crop image before resize

* set default fps to 16

* add diff lora support

* fix wan2.1 i2v

* introduce sd_sample_params_t

* add wan2.2 t2v support

* add wan2.2 14B i2v support

* add wan2.2 ti2v support

* add high noise lora support

* sync: update ggml submodule url

* avoid build failure on linux

* avoid build failure

* update ggml

* update ggml

* fix sd_version_is_wan

* update ggml, fix cpu im2col_3d

* fix ggml_nn_attention_ext mask

* add cache support to ggml runner

* fix the issue of illegal memory access

* unify image loading processing

* add wan2.1/2.2 FLF2V support

* fix end_image mask

* update to latest ggml

* add GGUFReader

* update docs

diffusion_model.hpp

@@ -4,8 +4,10 @@
 #include "flux.hpp"
 #include "mmdit.hpp"
 #include "unet.hpp"
+#include "wan.hpp"
 
 struct DiffusionModel {
+    virtual std::string get_desc()                                                      = 0;
     virtual void compute(int n_threads,
                          struct ggml_tensor* x,
                          struct ggml_tensor* timesteps,
@@ -32,10 +34,15 @@ struct UNetModel : public DiffusionModel {
     UNetModelRunner unet;
 
     UNetModel(ggml_backend_t backend,
+              bool offload_params_to_cpu,
               const String2GGMLType& tensor_types = {},
               SDVersion version                   = VERSION_SD1,
               bool flash_attn                     = false)
-        : unet(backend, tensor_types, "model.diffusion_model", version, flash_attn) {
+        : unet(backend, offload_params_to_cpu, tensor_types, "model.diffusion_model", version, flash_attn) {
+    }
+
+    std::string get_desc() {
+        return unet.get_desc();
     }
 
     void alloc_params_buffer() {
@@ -85,8 +92,13 @@ struct MMDiTModel : public DiffusionModel {
     MMDiTRunner mmdit;
 
     MMDiTModel(ggml_backend_t backend,
+               bool offload_params_to_cpu,
                const String2GGMLType& tensor_types = {})
-        : mmdit(backend, tensor_types, "model.diffusion_model") {
+        : mmdit(backend, offload_params_to_cpu, tensor_types, "model.diffusion_model") {
+    }
+
+    std::string get_desc() {
+        return mmdit.get_desc();
     }
 
     void alloc_params_buffer() {
@@ -135,11 +147,16 @@ struct FluxModel : public DiffusionModel {
     Flux::FluxRunner flux;
 
     FluxModel(ggml_backend_t backend,
+              bool offload_params_to_cpu,
               const String2GGMLType& tensor_types = {},
               SDVersion version                   = VERSION_FLUX,
               bool flash_attn                     = false,
               bool use_mask                       = false)
-        : flux(backend, tensor_types, "model.diffusion_model", version, flash_attn, use_mask) {
+        : flux(backend, offload_params_to_cpu, tensor_types, "model.diffusion_model", version, flash_attn, use_mask) {
+    }
+
+    std::string get_desc() {
+        return flux.get_desc();
     }
 
     void alloc_params_buffer() {
@@ -184,4 +201,63 @@ struct FluxModel : public DiffusionModel {
     }
 };
 
+struct WanModel : public DiffusionModel {
+    std::string prefix;
+    WAN::WanRunner wan;
+
+    WanModel(ggml_backend_t backend,
+             bool offload_params_to_cpu,
+             const String2GGMLType& tensor_types = {},
+             const std::string prefix            = "model.diffusion_model",
+             SDVersion version                   = VERSION_WAN2,
+             bool flash_attn                     = false)
+        : prefix(prefix), wan(backend, offload_params_to_cpu, tensor_types, prefix, version, flash_attn) {
+    }
+
+    std::string get_desc() {
+        return wan.get_desc();
+    }
+
+    void alloc_params_buffer() {
+        wan.alloc_params_buffer();
+    }
+
+    void free_params_buffer() {
+        wan.free_params_buffer();
+    }
+
+    void free_compute_buffer() {
+        wan.free_compute_buffer();
+    }
+
+    void get_param_tensors(std::map<std::string, struct ggml_tensor*>& tensors) {
+        wan.get_param_tensors(tensors, prefix);
+    }
+
+    size_t get_params_buffer_size() {
+        return wan.get_params_buffer_size();
+    }
+
+    int64_t get_adm_in_channels() {
+        return 768;
+    }
+
+    void compute(int n_threads,
+                 struct ggml_tensor* x,
+                 struct ggml_tensor* timesteps,
+                 struct ggml_tensor* context,
+                 struct ggml_tensor* c_concat,
+                 struct ggml_tensor* y,
+                 struct ggml_tensor* guidance,
+                 std::vector<ggml_tensor*> ref_latents     = {},
+                 int num_video_frames                      = -1,
+                 std::vector<struct ggml_tensor*> controls = {},
+                 float control_strength                    = 0.f,
+                 struct ggml_tensor** output               = NULL,
+                 struct ggml_context* output_ctx           = NULL,
+                 std::vector<int> skip_layers              = std::vector<int>()) {
+        return wan.compute(n_threads, x, timesteps, context, y, c_concat, NULL, output, output_ctx);
+    }
+};
+
 #endif