1 files changed, 98 insertions, 0 deletions
diff --git a/llama.cpp/tools/mtmd/models/cogvlm.cpp b/llama.cpp/tools/mtmd/models/cogvlm.cpp
new file mode 100644
index 0000000..d5b739c
--- /dev/null
+++ b/llama.cpp/tools/mtmd/models/cogvlm.cpp
@@ -0,0 +1,98 @@
+#include "models.h"
+
+ggml_cgraph * clip_graph_cogvlm::build() {
+    GGML_ASSERT(model.class_embedding != nullptr);
+    GGML_ASSERT(model.position_embeddings != nullptr);
+
+    const int n_pos = n_patches + 1; // +1 for [CLS]
+
+    // build input and concatenate class embedding
+    ggml_tensor * inp = build_inp();
+    inp = ggml_concat(ctx0, inp, model.class_embedding, 1);
+
+    inp = ggml_add(ctx0, inp, model.position_embeddings);
+    cb(inp, "inp_pos", -1);
+
+    ggml_tensor * inpL = inp;
+
+    for (int il = 0; il < n_layer; il++) {
+        auto & layer = model.layers[il];
+        ggml_tensor * cur = inpL;
+
+        cur = ggml_mul_mat(ctx0, layer.qkv_w, cur);
+
+        cur = ggml_add(ctx0, cur, layer.qkv_b);
+
+        ggml_tensor * Qcur = ggml_view_3d(ctx0, cur, d_head, n_head, n_pos, d_head*sizeof(float),
+            cur->nb[1], 0);
+        ggml_tensor * Kcur = ggml_view_3d(ctx0, cur, d_head, n_head, n_pos, d_head*sizeof(float),
+            cur->nb[1], n_embd * sizeof(float));
+        ggml_tensor * Vcur = ggml_view_3d(ctx0, cur, d_head, n_head, n_pos, d_head*sizeof(float),
+            cur->nb[1], 2 * n_embd * sizeof(float));
+
+        cb(Qcur, "Qcur", il);
+        cb(Kcur, "Kcur", il);
+        cb(Vcur, "Vcur", il);
+
+        cur = build_attn(layer.o_w, layer.o_b,
+            Qcur, Kcur, Vcur, nullptr, kq_scale, il);
+        cb(cur, "attn_out", il);
+
+        cur = build_norm(cur, layer.ln_1_w, layer.ln_1_b, NORM_TYPE_NORMAL, eps, il);
+        cb(cur, "attn_post_norm", il);
+
+        cur = ggml_add(ctx0, cur, inpL);
+        inpL = cur;
+
+        cur = build_ffn(cur,
+            layer.ff_up_w, layer.ff_up_b,
+            layer.ff_gate_w, layer.ff_gate_b,
+            layer.ff_down_w, layer.ff_down_b,
+            hparams.ffn_op, il);
+
+        cb(cur, "ffn_out", il);
+
+        cur = build_norm(cur, layer.ln_2_w, layer.ln_2_b, NORM_TYPE_NORMAL, eps, il);
+        cb(cur, "ffn_post_norm", il);
+
+        cur = ggml_add(ctx0, cur, inpL);
+        cb(cur, "layer_out", il);
+        inpL = cur;
+
+    }
+
+    // remove CLS token (like build_llama4 does)
+    ggml_tensor * cur = ggml_view_2d(ctx0, inpL,
+        n_embd, n_patches,
+        ggml_row_size(inpL->type, n_embd), 0);
+
+    // Multiply with mm_model_proj
+    cur = ggml_mul_mat(ctx0, model.mm_model_proj, cur);
+
+    // Apply layernorm, weight, bias
+    cur = build_norm(cur, model.mm_post_fc_norm_w, model.mm_post_fc_norm_b, NORM_TYPE_NORMAL, 1e-5, -1);
+
+    // Apply GELU
+    cur = ggml_gelu_inplace(ctx0, cur);
+
+    // Branch 1: multiply with mm_h_to_4h_w
+    ggml_tensor * h_to_4h = ggml_mul_mat(ctx0, model.mm_h_to_4h_w, cur);
+
+    // Branch 2: multiply with mm_gate_w
+    ggml_tensor * gate = ggml_mul_mat(ctx0, model.mm_gate_w, cur);
+
+    // Apply silu
+    gate = ggml_swiglu_split(ctx0, gate, h_to_4h);
+
+    // Apply mm_4h_to_h_w
+    cur = ggml_mul_mat(ctx0, model.mm_4h_to_h_w, gate);
+
+    // Concatenate with boi and eoi
+    cur = ggml_concat(ctx0, model.mm_boi, cur, 1);
+    cur = ggml_concat(ctx0, cur, model.mm_eoi, 1);
+
+    // build the graph
+    ggml_build_forward_expand(gf, cur);
+
+    return gf;
+}