mamba : move state_seq and state_mask views outside layer loop

A few tensors were also missing `struct` in front of `ggml_tensor`.

llama.cpp

@@ -5540,9 +5540,11 @@ struct llm_build_context {
     struct ggml_cgraph * build_s_copy() {
         struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
 
+        GGML_ASSERT(kv_self.recurrent);
+
         for (int il = 0; il < n_layer; ++il) {
-            ggml_tensor * conv_states = ggml_reshape_2d(ctx0, kv_self.k_l[il], hparams.n_embd_k_s(), kv_self.size);
-            ggml_tensor * ssm_states  = ggml_reshape_2d(ctx0, kv_self.v_l[il], hparams.n_embd_v_s(), kv_self.size);
+            struct ggml_tensor * conv_states = ggml_reshape_2d(ctx0, kv_self.k_l[il], hparams.n_embd_k_s(), kv_self.size);
+            struct ggml_tensor * ssm_states  = ggml_reshape_2d(ctx0, kv_self.v_l[il], hparams.n_embd_v_s(), kv_self.size);
 
             conv_states = ggml_get_rows(ctx0, conv_states, lctx.inp_s_copy);
             ssm_states  = ggml_get_rows(ctx0,  ssm_states, lctx.inp_s_copy);
@@ -8171,14 +8173,16 @@ struct llm_build_context {
         inpL = llm_build_inp_embd(ctx0, hparams, batch, model.tok_embd, lctx.inp_tokens, lctx.inp_embd, cb);
         cb(inpL, "inp_embd", -1);
 
+        struct ggml_tensor * state_mask = ggml_view_2d(ctx0, lctx.inp_s_mask, 1, n_kv, lctx.inp_s_mask->nb[0], 0);
+        struct ggml_tensor * state_seq  = ggml_view_2d(ctx0, lctx.inp_s_seq, n_kv, n_tokens, n_kv*ggml_element_size(lctx.inp_s_seq), 0);
+
         for (int il = 0; il < n_layer; ++il) {
             // (ab)using the KV cache to store the states
-            ggml_tensor * conv_states = ggml_reshape_2d(ctx0, kv_self.k_l[il], hparams.n_embd_k_s(), kv_self.size);
-            ggml_tensor * ssm_states  = ggml_reshape_2d(ctx0, kv_self.v_l[il], hparams.n_embd_v_s(), kv_self.size);
+            struct ggml_tensor * conv_states = ggml_reshape_2d(ctx0, kv_self.k_l[il], hparams.n_embd_k_s(), kv_self.size);
+            struct ggml_tensor * ssm_states  = ggml_reshape_2d(ctx0, kv_self.v_l[il], hparams.n_embd_v_s(), kv_self.size);
 
             // clear states of sequences which are starting at the beginning of this batch
             {
-                ggml_tensor * state_mask = ggml_view_2d(ctx0, lctx.inp_s_mask, 1, n_kv, lctx.inp_s_mask->nb[0], 0);
                 conv_states = ggml_mul(ctx0,
                     ggml_view_2d(ctx0, conv_states, conv_states->ne[0], n_kv, conv_states->nb[1], kv_head*conv_states->nb[1]),
                     state_mask);
@@ -8203,8 +8207,6 @@ struct llm_build_context {
             struct ggml_tensor * x = ggml_view_2d(ctx0, xz, d_inner, xz->ne[1], xz->nb[1], 0);
             struct ggml_tensor * z = ggml_view_2d(ctx0, xz, d_inner, xz->ne[1], xz->nb[1], ggml_element_size(xz)*d_inner);
 
-            struct ggml_tensor * state_seq = ggml_view_2d(ctx0, lctx.inp_s_seq, n_kv, n_tokens, n_kv*ggml_element_size(lctx.inp_s_seq), 0);
-
             // conv
             {
                 // Custom operator which is needed only to ease simultaneous sequence processing.