llama: Decouple patching script from submodule (#7139)

* Refine llama.cpp vendoring workflow tools

Switch from the sync.sh over to make based tooling

* Run new make sync and patch flow

llama/patches/0005-embeddings.patch

@@ -0,0 +1,51 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Michael Yang <mxyng@pm.me>
+Date: Mon, 16 Sep 2024 15:53:14 -0700
+Subject: [PATCH] embeddings
+
+---
+ src/llama.cpp | 15 +++++++++------
+ 1 file changed, 9 insertions(+), 6 deletions(-)
+
+diff --git a/src/llama.cpp b/src/llama.cpp
+index 800dfb95..a639522d 100644
+--- a/src/llama.cpp
++++ b/src/llama.cpp
+@@ -16920,7 +16920,7 @@ static size_t llama_output_reserve(llama_context & lctx, size_t n_outputs) {
+     const auto n_embd  = hparams.n_embd;
+ 
+     // TODO: use a per-batch flag for logits presence instead
+-    const bool has_logits = !cparams.embeddings;
++    const bool has_logits =  cparams.causal_attn;
+     const bool has_embd   =  cparams.embeddings && (cparams.pooling_type == LLAMA_POOLING_TYPE_NONE);
+ 
+     const size_t logits_size = has_logits ? n_vocab*n_outputs_max : 0;
+@@ -17192,20 +17192,23 @@ static int llama_decode_internal(
+             // no output
+             res  = nullptr;
+             embd = nullptr;
+-        } else if (cparams.embeddings) {
+-            res  = nullptr; // do not extract logits for embedding case
+-            embd = nullptr;
++        }
++
++        if (cparams.embeddings) {
+             for (int i = ggml_graph_n_nodes(gf) - 1; i >= 0; --i) {
++                embd = ggml_graph_node(gf, i);
+                 if (strcmp(ggml_graph_node(gf, i)->name, "result_embd_pooled") == 0) {
+-                    embd = ggml_graph_node(gf, i);
+                     break;
+                 }
+             }
+-            GGML_ASSERT(embd != nullptr && "missing embeddings tensor");
+         } else {
+             embd = nullptr; // do not extract embeddings when not needed
+             GGML_ASSERT(strcmp(res->name, "result_output") == 0 && "missing result_output tensor");
+         }
++
++        if (!cparams.causal_attn) {
++            res = nullptr; // do not extract logits when not needed
++        }
+         // LLAMA_LOG_INFO("graph build time: %.3f ms (%d nodes, %d leafs)\n", (ggml_time_us() - t_start_us)/1000.0, gf->n_nodes, gf->n_leafs);
+ 
+         ggml_backend_sched_alloc_graph(lctx.sched, gf);