llama : rename n_embed to n_embd in rwkv6_time_mix (#9504)

This commit renames n_embed to n_embd in llm_build_rwkv6_time_mix.

The motivation for this change is consistency with the other rwkv6
functions like build_rwkv6 (and other parts of the code base).

src/llama.cpp

@@ -9571,7 +9571,7 @@ static struct ggml_tensor * llm_build_rwkv6_time_mix(
         struct ggml_tensor * cur,
         struct ggml_tensor * x_prev,
         struct ggml_tensor ** wkv_state) {
-    size_t n_embed      = cur->ne[0];
+    size_t n_embd       = cur->ne[0];
     size_t n_seq_tokens = cur->ne[1];
     size_t n_seqs       = cur->ne[2];
 
@@ -9582,8 +9582,8 @@ static struct ggml_tensor * llm_build_rwkv6_time_mix(
 
     struct ggml_tensor * sx = ggml_sub(ctx, x_prev, cur);
 
-    sx  = ggml_reshape_2d(ctx, sx,  n_embed, n_tokens);
-    cur = ggml_reshape_2d(ctx, cur, n_embed, n_tokens);
+    sx  = ggml_reshape_2d(ctx, sx,  n_embd, n_tokens);
+    cur = ggml_reshape_2d(ctx, cur, n_embd, n_tokens);
 
     struct ggml_tensor * xxx = ggml_add(ctx, ggml_mul(ctx, sx, layer->time_mix_lerp_x), cur);
 
@@ -9608,11 +9608,11 @@ static struct ggml_tensor * llm_build_rwkv6_time_mix(
         xxx
     );
 
-    struct ggml_tensor *mw = ggml_view_2d(ctx, xxx, n_embed, n_tokens, xxx->nb[1], 0);
-    struct ggml_tensor *mk = ggml_view_2d(ctx, xxx, n_embed, n_tokens, xxx->nb[1], n_embed * n_tokens * sizeof(float));
-    struct ggml_tensor *mv = ggml_view_2d(ctx, xxx, n_embed, n_tokens, xxx->nb[1], n_embed * n_tokens * 2 * sizeof(float));
-    struct ggml_tensor *mr = ggml_view_2d(ctx, xxx, n_embed, n_tokens, xxx->nb[1], n_embed * n_tokens * 3 * sizeof(float));
-    struct ggml_tensor *mg = ggml_view_2d(ctx, xxx, n_embed, n_tokens, xxx->nb[1], n_embed * n_tokens * 4 * sizeof(float));
+    struct ggml_tensor *mw = ggml_view_2d(ctx, xxx, n_embd, n_tokens, xxx->nb[1], 0);
+    struct ggml_tensor *mk = ggml_view_2d(ctx, xxx, n_embd, n_tokens, xxx->nb[1], n_embd * n_tokens * sizeof(float));
+    struct ggml_tensor *mv = ggml_view_2d(ctx, xxx, n_embd, n_tokens, xxx->nb[1], n_embd * n_tokens * 2 * sizeof(float));
+    struct ggml_tensor *mr = ggml_view_2d(ctx, xxx, n_embd, n_tokens, xxx->nb[1], n_embd * n_tokens * 3 * sizeof(float));
+    struct ggml_tensor *mg = ggml_view_2d(ctx, xxx, n_embd, n_tokens, xxx->nb[1], n_embd * n_tokens * 4 * sizeof(float));
 
     struct ggml_tensor * xw = ggml_add(
         ctx,
@@ -9681,7 +9681,7 @@ static struct ggml_tensor * llm_build_rwkv6_time_mix(
         )
     );
 
-    w = ggml_add(ctx, w, ggml_reshape_1d(ctx, layer->time_mix_decay, n_embed));
+    w = ggml_add(ctx, w, ggml_reshape_1d(ctx, layer->time_mix_decay, n_embd));
     w = ggml_exp(ctx, ggml_neg(ctx, ggml_exp(ctx, w)));
     w = ggml_reshape_4d(ctx, w, 1, head_size, head_count, n_tokens);
 
@@ -9690,21 +9690,21 @@ static struct ggml_tensor * llm_build_rwkv6_time_mix(
     r = ggml_transpose(ctx, r);
 
     struct ggml_tensor * wkv_output = ggml_rwkv_wkv(ctx, k, v, r, layer->time_mix_first, w, *wkv_state);
-    cur = ggml_view_1d(ctx, wkv_output, n_embed * n_tokens, 0);
-    *wkv_state = ggml_view_1d(ctx, wkv_output, n_embed * head_size * n_seqs, n_embed * n_tokens * sizeof(float));
+    cur = ggml_view_1d(ctx, wkv_output, n_embd * n_tokens, 0);
+    *wkv_state = ggml_view_1d(ctx, wkv_output, n_embd * head_size * n_seqs, n_embd * n_tokens * sizeof(float));
 
     // group norm with head_count groups
-    cur = ggml_reshape_3d(ctx, cur, n_embed / head_count, head_count, n_tokens);
+    cur = ggml_reshape_3d(ctx, cur, n_embd / head_count, head_count, n_tokens);
     cur = ggml_norm(ctx, cur, 64e-5f);
 
     // Convert back to regular vectors.
-    cur = ggml_reshape_2d(ctx, cur, n_embed, n_tokens);
+    cur = ggml_reshape_2d(ctx, cur, n_embd, n_tokens);
     cur = ggml_add(ctx, ggml_mul(ctx, cur, layer->time_mix_ln), layer->time_mix_ln_b);
 
     cur = ggml_mul(ctx, cur, g);
     cur = llm_build_lora_mm(lctx, ctx, layer->time_mix_output, cur);
 
-    return ggml_reshape_3d(ctx, cur, n_embed, n_seq_tokens, n_seqs);
+    return ggml_reshape_3d(ctx, cur, n_embd, n_seq_tokens, n_seqs);
 }
 
 static struct ggml_tensor * llm_build_rwkv6_channel_mix(