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);
// 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]