rwkv: skip computing output for unused tokens for hybrid models

Signed-off-by: Molly Sophia <[email protected]>

Author: MollySophia

src/llama.cpp

@@ -7775,7 +7775,6 @@ struct llm_build_context {
 
         cur = inpL;
         struct ggml_tensor * inp_out_ids = build_inp_out_ids();
-        cur = ggml_reshape_2d(ctx0, cur, n_embd, n_tokens);
         cur = ggml_get_rows(ctx0, cur, inp_out_ids);
 
         cur = llm_build_norm(ctx0, cur, hparams, model.output_norm, model.output_norm_b, LLM_NORM, cb, -1);
@@ -7863,6 +7862,13 @@ struct llm_build_context {
 
             cb(ffn_inp, "ffn_inp", il);
 
+            if (il == n_layer - 1) {
+                // skip computing output for unused tokens
+                struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+                cur     = ggml_get_rows(ctx0, cur, inp_out_ids);
+                ffn_inp = ggml_get_rows(ctx0, ffn_inp, inp_out_ids);
+            }
+
             // feed-forward network
             cur = llm_build_norm(ctx0, ffn_inp, hparams,
                     model.layers[il].ffn_norm, NULL,
@@ -7886,10 +7892,6 @@ struct llm_build_context {
         }
 
         cur = inpL;
-        struct ggml_tensor * inp_out_ids = build_inp_out_ids();
-        cur = ggml_reshape_2d(ctx0, cur, n_embd, n_tokens);
-        cur = ggml_get_rows(ctx0, cur, inp_out_ids);
-
         cur = llm_build_norm(ctx0, cur, hparams, model.output_norm, model.output_norm_b, LLM_NORM_RMS, cb, -1);
         cb(cur, "result_norm", -1);
 
@@ -8000,7 +8002,6 @@ struct llm_build_context {
 
         cur = inpL;
         struct ggml_tensor * inp_out_ids = build_inp_out_ids();
-        cur = ggml_reshape_2d(ctx0, cur, n_embd, n_tokens);
         cur = ggml_get_rows(ctx0, cur, inp_out_ids);
 
         cur = llm_build_norm(ctx0, cur, hparams, model.output_norm, model.output_norm_b, LLM_NORM, cb, -1);
@@ -8084,6 +8085,13 @@ struct llm_build_context {
 
             cb(ffn_inp, "ffn_inp", il);
 
+            if (il == n_layer - 1) {
+                // skip computing output for unused tokens
+                struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+                cur     = ggml_get_rows(ctx0, cur, inp_out_ids);
+                ffn_inp = ggml_get_rows(ctx0, ffn_inp, inp_out_ids);
+            }
+
             // feed-forward network
             cur = llm_build_norm(ctx0, ffn_inp, hparams,
                     model.layers[il].ffn_norm, NULL,
@@ -8107,10 +8115,6 @@ struct llm_build_context {
         }
 
         cur = inpL;
-        struct ggml_tensor * inp_out_ids = build_inp_out_ids();
-        cur = ggml_reshape_2d(ctx0, cur, n_embd, n_tokens);
-        cur = ggml_get_rows(ctx0, cur, inp_out_ids);
-
         cur = llm_build_norm(ctx0, cur, hparams, model.output_norm, model.output_norm_b, LLM_NORM_RMS, cb, -1);
         cb(cur, "result_norm", -1);