gpt-2 : experimenting with attention mask

examples/gpt-2/main.cpp

@@ -496,6 +496,7 @@ bool gpt2_eval(
                         ggml_new_f32(ctx0, 1.0f/sqrt(float(n_embd)/n_head))
                         );
 
+#if 0
             // KQ_masked = mask_past(KQ_scaled)
             // [n_past + N, N, 12]
             struct ggml_tensor * KQ_masked = ggml_diag_mask_inf(ctx0, KQ_scaled, n_past);
@@ -503,6 +504,15 @@ bool gpt2_eval(
             // KQ = soft_max(KQ_masked)
             // [n_past + N, N, 12]
             struct ggml_tensor * KQ_soft_max = ggml_soft_max(ctx0, KQ_masked);
+#else
+            // KQ_masked = mask_past(KQ_scaled)
+            // [n_past + N, N, 12]
+            //struct ggml_tensor * KQ_masked = ggml_diag_mask_inf(ctx0, KQ_scaled, n_past);
+
+            // KQ = soft_max(KQ_masked)
+            // [n_past + N, N, 12]
+            struct ggml_tensor * KQ_soft_max = ggml_soft_max(ctx0, KQ_scaled);
+#endif
 
             // V_trans = Vmem.view(n_embd/n_head, n_head, n_past + N).permute(1, 2, 0, 3).contiguous()
             // [n_past + N, 64, 12]