Merge branch 'upstream' into concedo_experimental

# Conflicts:
#	docs/backend/SYCL.md
#	ggml/src/ggml-cpu/ggml-cpu.c
#	ggml/src/ggml-opencl/CMakeLists.txt
#	ggml/src/ggml-opencl/ggml-opencl.cpp
#	ggml/src/ggml-opencl/kernels/cvt.cl
#	ggml/src/ggml-opencl/kernels/gemv_moe_mxfp4_f32_ns.cl
#	ggml/src/ggml-opencl/kernels/gemv_moe_q4_k_f32_ns.cl
#	ggml/src/ggml-sycl/backend.hpp
#	ggml/src/ggml-sycl/common.hpp
#	ggml/src/ggml-sycl/dmmv.cpp
#	ggml/src/ggml-sycl/ggml-sycl.cpp
#	scripts/sync_vendor.py
#	tests/CMakeLists.txt
#	tests/test-alloc.cpp
#	tests/test-backend-ops.cpp
#	tests/test-chat.cpp
#	tests/test-gguf.cpp
#	tests/test-save-load-state.cpp

Author: LostRuins

common/chat-auto-parser-generator.cpp

@@ -147,7 +147,8 @@ common_peg_arena autoparser::build_parser(const generation_params & inputs, cons
         } else {
             parser = content.build_parser(ctx);
         }
-        return pure_content ? p.prefix(generation_prompt, reasoning.start) + parser : p.prefix(generation_prompt, reasoning.start) << parser;
+        const std::string reasoning_start = trim_whitespace(reasoning.start);
+        return pure_content ? p.prefix(generation_prompt, reasoning_start) + parser : p.prefix(generation_prompt, reasoning_start) << parser;
     });
 }
 

common/chat-diff-analyzer.cpp

@@ -124,16 +124,16 @@ static std::vector<std::function<void(const common_chat_template & tmpl, autopar
               analysis.tools.format.section_end    = "";
               analysis.tools.format.per_call_start = "<TOOLCALL>";
               analysis.tools.format.per_call_end   = "</TOOLCALL>";
+              analysis.tools.format.tools_array_wrapped = true;
               analysis.content.mode                = content_mode::PLAIN;
               analysis.content.start               = "";
               analysis.content.end                 = "";
               analysis.reasoning.mode              = reasoning_mode::TAG_BASED;
-              analysis.reasoning.start             = "<think>\n\n";
+              analysis.reasoning.start             = "<think>\n";
               analysis.reasoning.end               = "</think>";
               analysis.assistant_start             = "<SPECIAL_11>Assistant";
               analysis.user_start                  = "<SPECIAL_11>User";
               analysis.preserved_tokens.clear();
-              analysis.preserved_tokens.push_back("<SPECIAL_12>");
               analysis.preserved_tokens.push_back("<SPECIAL_11>");
               analysis.preserved_tokens.push_back("</think>");
               analysis.preserved_tokens.push_back("<TOOLCALL>");

common/common.h

@@ -1082,6 +1082,9 @@ enum ggml_opt_optimizer_type common_opt_get_optimizer(const char *);
 struct common_prompt_checkpoint {
     int64_t n_tokens;
 
+    // (optional) id of the task that created the checkpoint
+    int id_task = -1;
+
     llama_pos pos_min;
     llama_pos pos_max;
 

embd_res/klite.embd

@@ -7765,7 +7765,7 @@ Current version indicated by LITEVER below.
 		const codeContainer = btn.parentElement.querySelector('pre code');
 		let innercode = codeContainer.innerText;
 		//remove common language descriptiors from the start
-		let langsmatched = ["matlab","jsonc","powershell","ps1","haskell","hs","vbnet","vb","apache","apacheconf","makefile","mk","ini","protobuf","proto","typescript","tsx","markdown","md","mkdown","mkd","python","py","javascript","js","jsx","html","xhtml","xml","css","json","typescript","ts","tsx","bash","sh","zsh","java","csharp","cs","c","h","cpp","hpp","php","sql","ruby","rb","go","golang","kotlin","kt","swift","rust","rs","r","dart","scala","dockerfile","docker","yaml","yml","ini","toml","perl","pl","shell","console","powershell","ps1","lua","typescript","ts"];
+		let langsmatched = ["matlab","jsonc","powershell","ps1","haskell","hs","vbnet","vb","apache","apacheconf","makefile","mk","ini","protobuf","proto","typescript","tsx","markdown","md","mkdown","mkd","python","py","javascript","js","jsx","html","xhtml","xml","css","json","typescript","ts","tsx","bash","sh","zsh","java","csharp","cs","c","h","cpp","hpp","php","sql","ruby","rb","go","golang","kotlin","kt","swift","rust","rs","r","dart","scala","dockerfile","docker","yaml","yml","ini","toml","perl","pl","shell","console","powershell","ps1","lua","typescript","ts","patch","diff"];
 		for(let i = 0; i < langsmatched.length; ++i) {
 			let matcher = langsmatched[i]+"\n";
 			if (innercode.startsWith(matcher)) {

ggml/include/ggml-rpc.h

@@ -8,10 +8,10 @@ extern "C" {
 
 #define RPC_PROTO_MAJOR_VERSION    4
 #define RPC_PROTO_MINOR_VERSION    0
-#define RPC_PROTO_PATCH_VERSION    1
+#define RPC_PROTO_PATCH_VERSION    2
 
 #ifdef  __cplusplus
-static_assert(GGML_OP_COUNT == 97, "GGML_OP_COUNT has changed - update RPC_PROTO_PATCH_VERSION");
+static_assert(GGML_OP_COUNT == 98, "GGML_OP_COUNT has changed - update RPC_PROTO_PATCH_VERSION");
 #endif
 
 #define GGML_RPC_MAX_SERVERS       16

ggml/include/ggml.h

@@ -576,6 +576,7 @@ extern "C" {
         GGML_OP_RWKV_WKV7,
         GGML_OP_SOLVE_TRI,
         GGML_OP_GATED_DELTA_NET,
+        GGML_OP_LIGHTNING_INDEXER,
 
         GGML_OP_UNARY,
 
@@ -2593,6 +2594,24 @@ extern "C" {
             struct ggml_tensor  * state,
             int64_t               K);
 
+    // DSA lightning indexer
+    //
+    // q:       [n_embd_idx, n_head_idx, n_batch, ne3 ]
+    // k:       [n_embd_idx, 1,          n_kv,    ne3 ]
+    // weights: [n_head_idx, n_batch,    1,       ne3 ] !! prescaled !!
+    // mask:    [n_kv,       n_batch,    1,       ne33] !! f16 !!
+    // res:     [n_kv,       n_batch,    1,       ne3 ]
+    //
+    // broadcast:
+    //   ne3 % ne33 == 0
+    //
+    GGML_API struct ggml_tensor * ggml_lightning_indexer(
+        struct ggml_context * ctx,
+        struct ggml_tensor  * q,
+        struct ggml_tensor  * k,
+        struct ggml_tensor  * weights,
+        struct ggml_tensor  * mask);
+
     // custom operators
 
     typedef void (*ggml_custom1_op_t)(struct ggml_tensor * dst , const struct ggml_tensor * a, int ith, int nth, void * userdata);

ggml/include/gguf.h

@@ -125,12 +125,13 @@ extern "C" {
     // get ith C string from array with given key_id
     GGML_API const char * gguf_get_arr_str (const struct gguf_context * ctx, int64_t key_id, size_t i);
 
-    GGML_API int64_t        gguf_get_n_tensors    (const struct gguf_context * ctx);
-    GGML_API int64_t        gguf_find_tensor      (const struct gguf_context * ctx, const char * name); // returns -1 if the tensor is not found
-    GGML_API size_t         gguf_get_tensor_offset(const struct gguf_context * ctx, int64_t tensor_id);
-    GGML_API const char *   gguf_get_tensor_name  (const struct gguf_context * ctx, int64_t tensor_id);
-    GGML_API enum ggml_type gguf_get_tensor_type  (const struct gguf_context * ctx, int64_t tensor_id);
-    GGML_API size_t         gguf_get_tensor_size  (const struct gguf_context * ctx, int64_t tensor_id);
+    GGML_API int64_t         gguf_get_n_tensors    (const struct gguf_context * ctx);
+    GGML_API int64_t         gguf_find_tensor      (const struct gguf_context * ctx, const char * name); // returns -1 if the tensor is not found
+    GGML_API size_t          gguf_get_tensor_offset(const struct gguf_context * ctx, int64_t tensor_id);
+    GGML_API const char *    gguf_get_tensor_name  (const struct gguf_context * ctx, int64_t tensor_id);
+    GGML_API const int64_t * gguf_get_tensor_ne    (const struct gguf_context * ctx, int64_t tensor_id); // returns ne, an array of GGML_MAX_DIMS elements; ne[dim] is 1 for dim >= n_dims
+    GGML_API enum ggml_type  gguf_get_tensor_type  (const struct gguf_context * ctx, int64_t tensor_id);
+    GGML_API size_t          gguf_get_tensor_size  (const struct gguf_context * ctx, int64_t tensor_id);
 
     // removes key if it exists, returns id that the key had prior to removal (-1 if it didn't exist)
     GGML_API int64_t gguf_remove_key(struct gguf_context * ctx, const char * key);

ggml/src/ggml-cpu/ggml-cpu.c

@@ -2832,6 +2832,10 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm
             {
                 ggml_compute_forward_gated_delta_net(params, tensor);
             } break;
+        case GGML_OP_LIGHTNING_INDEXER:
+            {
+                ggml_compute_forward_lightning_indexer(params, tensor);
+            } break;
         case GGML_OP_MAP_CUSTOM1:
             {
                 ggml_compute_forward_map_custom1(params, tensor);
@@ -3193,6 +3197,7 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) {
         case GGML_OP_FLASH_ATTN_BACK:
         case GGML_OP_SSM_CONV:
         case GGML_OP_SSM_SCAN:
+        case GGML_OP_LIGHTNING_INDEXER:
             {
                 n_tasks = n_threads;
             } break;
@@ -3814,6 +3819,12 @@ struct ggml_cplan ggml_graph_plan(
                         // to prepare magnitude and phase for inverted FFTs.
                         cur = ggml_type_size(node->type)*(n_tasks + node->ne[0] * n_tasks * 4);
                     } break;
+                case GGML_OP_LIGHTNING_INDEXER:
+                    {
+                        // temp buffer for dequantizing lightning indexer keys
+                        const int64_t ne10 = node->src[1]->ne[0];
+                        cur += sizeof(float)*ne10*n_tasks;
+                    } break;
                 default:
                     break;
             }

ggml/src/ggml-cpu/ops.cpp

@@ -11568,3 +11568,87 @@ void ggml_compute_forward_fwht(const ggml_compute_params * params, ggml_tensor *
             }
     }
 }
+
+// ggml_compute_forward_lightning_indexer
+
+void ggml_compute_forward_lightning_indexer(
+        const ggml_compute_params * params,
+        ggml_tensor * dst) {
+
+    const ggml_tensor * q = dst->src[0];
+    const ggml_tensor * k = dst->src[1];
+    const ggml_tensor * w = dst->src[2]; // weights
+    const ggml_tensor * m = dst->src[3]; // mask
+
+    GGML_ASSERT(dst->type  == GGML_TYPE_F32);
+    GGML_ASSERT(   q->type == GGML_TYPE_F32);
+    GGML_ASSERT(   w->type == GGML_TYPE_F32);
+    GGML_ASSERT(   m->type == GGML_TYPE_F16);
+
+    GGML_TENSOR_LOCALS(int64_t, neq,  q, ne)
+    GGML_TENSOR_LOCALS(size_t,  nbq,  q, nb)
+    GGML_TENSOR_LOCALS(int64_t, nek,  k, ne)
+    GGML_TENSOR_LOCALS(size_t,  nbk,  k, nb)
+    GGML_TENSOR_LOCALS(int64_t, new,  w, ne)
+    GGML_TENSOR_LOCALS(size_t,  nbw,  w, nb)
+    GGML_TENSOR_LOCALS(int64_t, nem,  m, ne)
+    GGML_TENSOR_LOCALS(size_t,  nbm,  m, nb)
+    GGML_TENSOR_LOCALS(int64_t, ne, dst, ne)
+    GGML_TENSOR_LOCALS(size_t,  nb, dst, nb)
+
+    GGML_ASSERT( nb0 == ggml_type_size(dst->type));
+    GGML_ASSERT(nbq0 == ggml_type_size(  q->type));
+    GGML_ASSERT(nbk0 == ggml_type_size(  k->type));
+    GGML_ASSERT(nbw0 == ggml_type_size(  w->type));
+    GGML_ASSERT(nbm0 == ggml_type_size(  m->type));
+
+    const int n_embd    = q->ne[0];
+    const int n_head    = q->ne[1];
+    const int n_tokens  = q->ne[2];
+    const int n_stream  = q->ne[3];
+    const int n_kv      = k->ne[2];
+
+    ggml_to_float_t const k_to_float = ggml_get_type_traits(k->type)->to_float;
+    GGML_ASSERT((k->type == GGML_TYPE_F32 || k_to_float) && "lightning indexer: unsupported K-type");
+
+    const int nr  = n_kv;
+    const int ith = params->ith;
+    const int nth = params->nth;
+
+    // (temporary) buffer for K converted to float
+    float * k_row_f32 = (float *) params->wdata + ith*(1*n_embd + CACHE_LINE_SIZE_F32);
+
+    // rows per thread
+    const int dr = (nr + nth - 1)/nth;
+
+    // row range for this thread
+    const int ir0 = dr*ith;
+    const int ir1 = MIN(ir0 + dr, nr);
+
+    for (int s = 0; s < n_stream; ++s) {
+        for (int t = 0; t < n_tokens; ++t) {
+            const float       *   w_row =       (float *) ((char *)   w->data + t*nbw1 +        s*nbw3);
+            const ggml_fp16_t *   m_row = (ggml_fp16_t *) ((char *)   m->data + t*nbm1 + (s%nem3)*nbm3);
+            float             * dst_row =       (float *) ((char *) dst->data + t*nb1  +        s*nb3 );
+            for (int ik = ir0; ik < ir1; ++ik) {
+                char * k_row = (char *) k->data + ik*nbk2 + s*nbk3;
+                if (k_to_float) {
+                    k_to_float(k_row, k_row_f32, n_embd);
+                } else {
+                    k_row_f32 = (float *) k_row;
+                }
+                float score = 0.0f;
+                for (int h = 0; h < n_head; ++h) {
+                    // dot product of q and k for head h
+                    float qk = 0.0f;
+                    const float * q_row = (float *) ((char *) q->data + h*nbq1 + t*nbq2 + s*nbq3);
+                    ggml_vec_dot_f32(n_embd, &qk, 0, q_row, 0, k_row_f32, 0, 1);
+                    // ReLU and weights (prescaled)
+                    score += MAX(qk, 0.0f) * w_row[h];
+                }
+                // apply mask
+                dst_row[ik] = score + GGML_CPU_FP16_TO_FP32(m_row[ik]);
+            }
+        }
+    }
+}

ggml/src/ggml-cpu/ops.h

@@ -105,6 +105,7 @@ void ggml_compute_forward_rwkv_wkv7(const struct ggml_compute_params * params, s
 void ggml_compute_forward_solve_tri(const struct ggml_compute_params * params, struct ggml_tensor * dst);
 void ggml_compute_forward_gla(const struct ggml_compute_params * params, struct ggml_tensor * dst);
 void ggml_compute_forward_gated_delta_net(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_lightning_indexer(const struct ggml_compute_params * params, struct ggml_tensor * dst);
 void ggml_compute_forward_map_custom1(const struct ggml_compute_params * params, struct ggml_tensor * dst);
 void ggml_compute_forward_map_custom2(const struct ggml_compute_params * params, struct ggml_tensor * dst);
 void ggml_compute_forward_map_custom3(const struct ggml_compute_params * params, struct ggml_tensor * dst);