mtmd, model: allow skip build_vit() (#24077)

* add model

* nits

tools/mtmd/models/gemma4ua.cpp

@@ -0,0 +1,19 @@
+#include "models.h"
+#include <cmath>
+
+ggml_cgraph * clip_graph_gemma4ua::build() {
+    ggml_tensor * inp = build_inp_raw(1);
+
+    auto cur = ggml_cont(ctx0, ggml_permute(ctx0, inp, 1, 0, 2, 3));
+
+    // Gemma4UnifiedMultimodalEmbedder
+    {
+        // embedding_pre_projection_norm
+        cur = ggml_rms_norm(ctx0, cur, hparams.eps);
+        cur = build_mm(model.mm_input_proj_w, cur);
+        cb(cur, "projected", -1);
+    }
+
+    ggml_build_forward_expand(gf, cur);
+    return gf;
+}

tools/mtmd/models/gemma4uv.cpp

@@ -0,0 +1,71 @@
+#include "models.h"
+#include <cmath>
+
+ggml_cgraph * clip_graph_gemma4uv::build() {
+    ggml_tensor * inp_raw = build_inp_raw();
+
+    // Gemma4UnifiedVisionEmbedder uses default pytorch LayerNorm, not RMSNorm
+    float eps = 1e-5f; // default eps for pytorch LayerNorm
+
+    ggml_tensor * inp = nullptr;
+    {
+        // note: we cannot use ggml_conv_2d here because we need to apply norm after im2col
+        auto c = inp_raw->ne[2];
+        ggml_tensor * kernel = ggml_new_tensor_3d(ctx0, GGML_TYPE_F32, patch_size, patch_size, c);
+        inp = ggml_im2col(ctx0, kernel, inp_raw, patch_size, patch_size, 0, 0, 1, 1, true, inp_raw->type);
+        // inp shape: [patch_size * patch_size * c, n_patches_w, n_patches_h]
+
+        inp = ggml_reshape_2d(ctx0, inp, inp->ne[0], inp->ne[1] * inp->ne[2] * inp->ne[3]);
+        inp = build_norm(inp, model.patch_norm_1_w, model.patch_norm_1_b, NORM_TYPE_NORMAL, eps, -1);
+        // inp shape: [patch_size * patch_size * c, n_patches]
+
+        inp = ggml_mul_mat(ctx0, model.patch_embeddings_0, inp);
+        inp = ggml_add(ctx0, inp, model.patch_bias);
+        // inp shape: [n_embd, n_patches]
+
+        inp = build_norm(inp, model.patch_norm_2_w, model.patch_norm_2_b, NORM_TYPE_NORMAL, eps, -1);
+    }
+
+    ggml_tensor * pos_x = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, n_patches);
+    ggml_set_name(pos_x, "pos_x");
+    ggml_set_input(pos_x);
+
+    ggml_tensor * pos_y = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, n_patches);
+    ggml_set_name(pos_y, "pos_y");
+    ggml_set_input(pos_y);
+
+    {
+        const int64_t pos_size = model.position_embeddings->ne[1];
+        const size_t  nb1      = ggml_row_size(model.position_embeddings->type, n_embd);
+
+        // positional embeddings are stored as lookup tables (one for x, one for y)
+        ggml_tensor * tbl_x = ggml_view_2d(ctx0, model.position_embeddings,
+                                             n_embd, pos_size, nb1, 0);
+        ggml_tensor * tbl_y = ggml_view_2d(ctx0, model.position_embeddings,
+                                             n_embd, pos_size, nb1, pos_size * nb1);
+
+        // ggml_get_rows: [n_embd, n_patches]
+        ggml_tensor * emb_x = ggml_get_rows(ctx0, tbl_x, pos_x);
+        ggml_tensor * emb_y = ggml_get_rows(ctx0, tbl_y, pos_y);
+
+        inp = ggml_add(ctx0, inp, emb_x);
+        inp = ggml_add(ctx0, inp, emb_y);
+        cb(inp, "pos_embd", -1);
+
+        // pos_norm
+        inp = build_norm(inp, model.patch_norm_3_w, model.patch_norm_3_b, NORM_TYPE_NORMAL, eps, -1);
+    }
+
+    auto cur = inp;
+
+    // Gemma4UnifiedMultimodalEmbedder
+    {
+        // embedding_pre_projection_norm
+        cur = ggml_rms_norm(ctx0, cur, hparams.eps);
+        cur = build_mm(model.mm_input_proj_w, cur);
+        cb(cur, "projected", -1);
+    }
+
+    ggml_build_forward_expand(gf, cur);
+    return gf;
+}

tools/mtmd/models/models.h

@@ -18,6 +18,11 @@ struct clip_graph_gemma4v : clip_graph {
     ggml_tensor * build_mm(ggml_tensor * w, ggml_tensor * x) const override;
 };
 
+struct clip_graph_gemma4uv : clip_graph {
+    clip_graph_gemma4uv(clip_ctx * ctx, const clip_image_f32 & img) : clip_graph(ctx, img) {}
+    ggml_cgraph * build() override;
+};
+
 struct clip_graph_pixtral : clip_graph {
     clip_graph_pixtral(clip_ctx * ctx, const clip_image_f32 & img) : clip_graph(ctx, img) {}
     ggml_cgraph * build() override;
@@ -142,6 +147,11 @@ struct clip_graph_gemma4a : clip_graph {
     ggml_tensor * build_mm(ggml_tensor * w, ggml_tensor * x) const override;
 };
 
+struct clip_graph_gemma4ua : clip_graph {
+    clip_graph_gemma4ua(clip_ctx * ctx, const clip_image_f32 & img) : clip_graph(ctx, img) {}
+    ggml_cgraph * build() override;
+};
+
 struct clip_graph_glm4v : clip_graph {
     clip_graph_glm4v(clip_ctx * ctx, const clip_image_f32 & img) : clip_graph(ctx, img) {}
     ggml_cgraph * build() override;