Eliminated need for ggml_repeat2 by using a modified version of ggerg…

…anov#224 instead

examples/falcon/main.cpp

@@ -441,7 +441,6 @@ bool falcon_eval(
 
     // wte
     struct ggml_tensor * inpL = ggml_get_rows(ctx0, model.tok_embeddings, embd);
-    struct ggml_tensor* repeat_dummy = ggml_new_tensor_3d(ctx0, inpL->type, head_dim, N + n_past, n_head);
 
     ggml_type wtype = GGML_TYPE_F32;
     const int sizeof_wtype = ggml_type_sizef(wtype);
@@ -539,8 +538,6 @@ bool falcon_eval(
 
             // K * Q
 
-            K = ggml_cont(ctx0, ggml_repeat2(ctx0, K, repeat_dummy));
-
             struct ggml_tensor * Q = ggml_permute(ctx0, Qcur, 0, 2, 1, 3);
             struct ggml_tensor * KQ = ggml_mul_mat(ctx0, K, Q);
 
@@ -570,7 +567,7 @@ bool falcon_eval(
                     head_dim, n_head_kv, n_past + N),
                 0, 2, 1, 3);
 
-            V = ggml_cont(ctx0, ggml_transpose(ctx0, ggml_repeat2(ctx0, V, repeat_dummy)));
+            V = ggml_cont(ctx0, ggml_transpose(ctx0, V));
 
             // KQV = transpose(V) * KQ_soft_max
             struct ggml_tensor * KQV = ggml_mul_mat(ctx0, V, KQ_soft_max);

src/ggml.c

@@ -10735,7 +10735,11 @@ static void ggml_compute_forward_mul_mat_f32(
 
         const int64_t ir0 = (ir1/ne11)%(ne02*ne03);
         const int64_t i03 = (ir0/(ne02));
-        const int64_t i02 = (ir0 - i03*ne02);
+        // Hack for "Falcon multi-query-attention key stutter" / alternative to ggml_repeat2.
+        // See https://github.com/ggerganov/llama.cpp/issues/1602#issuecomment-1606087470:
+        const int64_t i02 = (i12 / (ne12 / ne02));
+        // Original from PR/224 (and also essential/correct for non-broadcast matmuls in Falcon)
+        // const int64_t i02 = (ir0 - i03*ne02);
 
         const int64_t i1 = i11;
         const int64_t i2 = i12;