ggml : fix a few instances of missing GGML_TYPE_Q1_0 cases (#21716)

* hexagon: add support for debian on ex2

* hexagon: add -fvectotize to c/c++ cmake flags

* hexagon: remove trailing white space

* update onboarding steps

* hexagon: update linux setup documentation

* hexagon: update intallation scripts

* Hexagon: update docs

* hexagon: update onboarding scripts

---------

Co-authored-by: Zack Li <zackli@qti.qualcomm.com>

cmake/arm64-linux-clang.cmake

@@ -0,0 +1,17 @@
+set( CMAKE_SYSTEM_NAME Linux )
+set( CMAKE_SYSTEM_PROCESSOR arm64 )
+
+set( target aarch64-linux-gnu )
+
+set( CMAKE_C_COMPILER    clang )
+set( CMAKE_CXX_COMPILER  clang++ )
+
+set( CMAKE_C_COMPILER_TARGET   ${target} )
+set( CMAKE_CXX_COMPILER_TARGET ${target} )
+
+set( arch_c_flags "-march=armv8.7-a -fvectorize -ffp-model=fast -fno-finite-math-only" )
+set( warn_c_flags "-Wno-format -Wno-unused-variable -Wno-unused-function -Wno-gnu-zero-variadic-macro-arguments" )
+
+set( CMAKE_C_FLAGS_INIT   "${arch_c_flags} ${warn_c_flags}" )
+set( CMAKE_CXX_FLAGS_INIT "${arch_c_flags} ${warn_c_flags}" )
+

common/chat-auto-parser-generator.cpp

@@ -69,6 +69,10 @@ common_chat_params peg_generator::generate_parser(const common_chat_template &
                 auto         schema   = function.contains("parameters") ? function.at("parameters") : json::object();
                 builder.resolve_refs(schema);
             });
+            if (has_response_format) {
+                auto schema = inputs.json_schema;
+                builder.resolve_refs(schema);
+            }
             parser.build_grammar(builder, data.grammar_lazy);
         });
 

common/chat.cpp

@@ -865,9 +865,10 @@ static common_chat_params common_chat_params_init_ministral_3(const common_chat_
         adjusted_messages.push_back(adjusted);
     }
 
-    auto has_tools         = inputs.tools.is_array() && !inputs.tools.empty();
-    auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
-    auto include_grammar   = true;
+    auto has_tools            = inputs.tools.is_array() && !inputs.tools.empty();
+    auto has_response_format  = inputs.json_schema.is_object() && !inputs.json_schema.empty();
+    auto extract_reasoning    = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
+    auto include_grammar      = true;
 
     data.supports_thinking  = true;
     data.thinking_start_tag = "[THINK]";
@@ -887,7 +888,7 @@ static common_chat_params common_chat_params_init_ministral_3(const common_chat_
             extract_reasoning ? p.optional("[THINK]" + p.reasoning(p.until("[/THINK]")) + "[/THINK]") : p.eps();
 
         // Response format parser
-        if (inputs.json_schema.is_object() && !inputs.json_schema.empty()) {
+        if (has_response_format) {
             // Ministral wants to emit json surrounded by code fences
             return generation_prompt + (reasoning << "```json" << p.content(p.schema(p.json(), "response-format", inputs.json_schema)) << "```");
         }
@@ -928,6 +929,10 @@ static common_chat_params common_chat_params_init_ministral_3(const common_chat_
                 auto         schema   = function.at("parameters");
                 builder.resolve_refs(schema);
             });
+            if (has_response_format) {
+                auto schema = inputs.json_schema;
+                builder.resolve_refs(schema);
+            }
             parser.build_grammar(builder, data.grammar_lazy);
         });
 
@@ -1063,6 +1068,10 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
                 auto         schema   = function.at("parameters");
                 builder.resolve_refs(schema);
             });
+            if (has_response_format) {
+                auto schema = inputs.json_schema;
+                builder.resolve_refs(schema);
+            }
             parser.build_grammar(builder, data.grammar_lazy);
         });
 
@@ -1193,6 +1202,10 @@ static common_chat_params common_chat_params_init_gemma4(const common_chat_templ
                 auto         schema   = function.at("parameters");
                 builder.resolve_refs(schema);
             });
+            if (has_response_format) {
+                auto schema = inputs.json_schema;
+                builder.resolve_refs(schema);
+            }
             parser.build_grammar(builder, data.grammar_lazy);
         });
 

docs/backend/snapdragon/CMakeUserPresets.json

@@ -52,10 +52,39 @@
         }
     },
 
+    {
+        "name": "arm64-linux-snapdragon",
+        "hidden": true,
+        "architecture": { "value": "arm64",       "strategy": "external" },
+        "toolset":      { "value": "host=x86_64", "strategy": "external" },
+        "cacheVariables": {
+            "CMAKE_TOOLCHAIN_FILE": "cmake/arm64-linux-clang.cmake",
+            "CMAKE_C_FLAGS":   "-march=armv8 -fno-finite-math-only -flto -D_GNU_SOURCE",
+            "CMAKE_CXX_FLAGS": "-march=armv8 -fno-finite-math-only -flto -D_GNU_SOURCE",
+            "CMAKE_C_FLAGS_RELEASE":          "-O3 -DNDEBUG",
+            "CMAKE_CXX_FLAGS_RELEASE":        "-O3 -DNDEBUG",
+            "CMAKE_C_FLAGS_RELWITHDEBINFO":   "-O3 -DNDEBUG -g",
+            "CMAKE_CXX_FLAGS_RELWITHDEBINFO": "-O3 -DNDEBUG -g",
+            "CMAKE_PREFIX_PATH":  "$env{OPENCL_SDK_ROOT}",
+            "HEXAGON_SDK_ROOT":   "$env{HEXAGON_SDK_ROOT}",
+            "HEXAGON_TOOLS_ROOT": "$env{HEXAGON_TOOLS_ROOT}",
+            "PREBUILT_LIB_DIR": "linux_aarch64",
+            "GGML_OPENMP":      "OFF",
+            "GGML_LLAMAFILE":   "OFF",
+            "GGML_OPENCL":      "OFF",
+            "GGML_HEXAGON":     "ON",
+            "GGML_HEXAGON_FP32_QUANTIZE_GROUP_SIZE": "128",
+            "LLAMA_OPENSSL":    "OFF"
+        }
+    },
+
     { "name": "arm64-android-snapdragon-debug"  , "inherits": [ "base", "arm64-android-snapdragon", "debug" ] },
     { "name": "arm64-android-snapdragon-release", "inherits": [ "base", "arm64-android-snapdragon", "release" ] },
 
     { "name": "arm64-windows-snapdragon-debug"  , "inherits": [ "base", "arm64-windows-snapdragon", "debug" ] },
-    { "name": "arm64-windows-snapdragon-release", "inherits": [ "base", "arm64-windows-snapdragon", "release" ] }
+    { "name": "arm64-windows-snapdragon-release", "inherits": [ "base", "arm64-windows-snapdragon", "release" ] },
+
+    { "name": "arm64-linux-snapdragon-debug"  , "inherits": [ "base", "arm64-linux-snapdragon", "debug" ] },
+    { "name": "arm64-linux-snapdragon-release", "inherits": [ "base", "arm64-linux-snapdragon", "release" ] }
   ]
 }

docs/backend/snapdragon/linux.md

@@ -0,0 +1,58 @@
+# Snapdragon-based Linux devices
+
+## Docker Setup
+
+The easiest way to build llama.cpp for a Snapdragon-based Linux device is using the toolchain Docker image (see [github.com/snapdragon-toolchain](https://github.com/snapdragon-toolchain)).
+This image includes OpenCL SDK, Hexagon SDK, CMake, and the ARM64 Linux cross-compilation toolchain.
+
+Cross-compilation is supported on **Linux X86** hosts. The resulting binaries are deployed to and run on the target **Qualcomm Snapdragon ARM64 Linux** device.
+
+```
+~/src/llama.cpp$ docker run -it -u $(id -u):$(id -g) --volume $(pwd):/workspace --platform linux/amd64 ghcr.io/snapdragon-toolchain/arm64-linux:v0.1
+[d]/> cd /workspace
+```
+
+Note: The rest of the **Linux** build process assumes that you're running inside the toolchain container.
+
+
+## How to Build
+
+Let's build llama.cpp with CPU, OpenCL, and Hexagon backends via CMake presets:
+
+```
+[d]/workspace> cp docs/backend/snapdragon/CMakeUserPresets.json .
+
+[d]/workspace> cmake --preset arm64-linux-snapdragon-release -B build-snapdragon
+
+[d]/workspace> cmake --build build-snapdragon -j $(nproc)
+```
+
+To generate an installable "package" simply use cmake --install, then zip it:
+
+```
+[d]/workspace> cmake --install build-snapdragon --prefix pkg-snapdragon
+[d]/workspace> zip -r pkg-snapdragon.zip pkg-snapdragon
+```
+
+## How to Install
+
+For this step, you will deploy the built binaries and libraries to the target Linux device. Transfer `pkg-snapdragon.zip` to the target device, then unzip it and set up the environment variables:
+
+```
+$ unzip pkg-snapdragon.zip
+$ cd pkg-snapdragon
+$ export LD_LIBRARY_PATH=./lib
+$ export ADSP_LIBRARY_PATH=./lib
+```
+
+At this point, you should also download some models onto the device:
+
+```
+$ wget https://huggingface.co/bartowski/Llama-3.2-3B-Instruct-GGUF/resolve/main/Llama-3.2-3B-Instruct-Q4_0.gguf
+```
+
+## How to Run
+Next, since we have setup the environment variables, we can run the llama-cli with the Hexagon backends:
+```
+$ ./bin/llama-cli -m Llama-3.2-3B-Instruct-Q4_0.gguf --device HTP0 -ngl 99 -p "what is the most popular cookie in the world?"
+```

ggml/src/ggml-cpu/ops.cpp

@@ -664,6 +664,7 @@ void ggml_compute_forward_add(
             {
                 ggml_compute_forward_add_non_quantized(params, dst);
             } break;
+        case GGML_TYPE_Q1_0:
         case GGML_TYPE_Q4_0:
         case GGML_TYPE_Q4_1:
         case GGML_TYPE_Q5_0:
@@ -1113,6 +1114,7 @@ void ggml_compute_forward_add1(
                     GGML_ABORT("fatal error");
                 }
             } break;
+        case GGML_TYPE_Q1_0:
         case GGML_TYPE_Q4_0:
         case GGML_TYPE_Q4_1:
         case GGML_TYPE_Q5_0:
@@ -1242,6 +1244,7 @@ void ggml_compute_forward_acc(
             } break;
         case GGML_TYPE_F16:
         case GGML_TYPE_BF16:
+        case GGML_TYPE_Q1_0:
         case GGML_TYPE_Q4_0:
         case GGML_TYPE_Q4_1:
         case GGML_TYPE_Q5_0:
@@ -4331,6 +4334,7 @@ void ggml_compute_forward_out_prod(
     const ggml_tensor * src0 = dst->src[0];
 
     switch (src0->type) {
+        case GGML_TYPE_Q1_0:
         case GGML_TYPE_Q4_0:
         case GGML_TYPE_Q4_1:
         case GGML_TYPE_Q5_0:
@@ -4606,6 +4610,7 @@ void ggml_compute_forward_set(
             } break;
         case GGML_TYPE_F16:
         case GGML_TYPE_BF16:
+        case GGML_TYPE_Q1_0:
         case GGML_TYPE_Q4_0:
         case GGML_TYPE_Q4_1:
         case GGML_TYPE_Q5_0:

ggml/src/ggml-cuda/common.cuh

@@ -1185,7 +1185,9 @@ struct ggml_cuda_graph {
     bool warmup_complete = false;
     struct node_properties {
         ggml_tensor node;
-        void * node_src_data_ptrs[GGML_MAX_SRC];
+        void *   node_src_data_ptrs[GGML_MAX_SRC];
+        int64_t  node_src_ne[GGML_MAX_SRC][GGML_MAX_DIMS];
+        size_t   node_src_nb[GGML_MAX_SRC][GGML_MAX_DIMS];
     };
     std::vector<node_properties> node_props;
 

ggml/src/ggml-cuda/ggml-cuda.cu

@@ -3070,16 +3070,18 @@ static bool ggml_cuda_graph_update_required(ggml_backend_cuda_context * cuda_ctx
         ggml_cuda_graph::node_properties prop = {};
         memcpy(&prop.node, cgraph->nodes[i], sizeof(ggml_tensor));
 
-        // if the backend scheduler is making copies of CPU tensors, the src pointers can be the same but with different data, see:
-        // https://github.com/ggml-org/llama.cpp/pull/21472#discussion_r3052235188
         for (int j = 0; j < GGML_MAX_SRC; ++j) {
-            prop.node_src_data_ptrs[j] = cgraph->nodes[i]->src[j] ? cgraph->nodes[i]->src[j]->data : nullptr;
+            if (cgraph->nodes[i]->src[j]) {
+                prop.node_src_data_ptrs[j] = cgraph->nodes[i]->src[j]->data;
+                memcpy(prop.node_src_ne[j], cgraph->nodes[i]->src[j]->ne, sizeof(prop.node_src_ne[j]));
+                memcpy(prop.node_src_nb[j], cgraph->nodes[i]->src[j]->nb, sizeof(prop.node_src_nb[j]));
+            }
         }
 
-        if (!res && memcmp(&graph->node_props[i], &prop, sizeof(prop)) != 0) {
+        if (res || memcmp(&graph->node_props[i], &prop, sizeof(prop)) != 0) {
+            graph->node_props[i] = prop;
             res = true;
         }
-        graph->node_props[i] = prop;
     }
 
     return res;

requirements/requirements-tool_bench.txt

@@ -8,5 +8,5 @@ pandas~=2.2.3
 prometheus-client~=0.20.0
 requests~=2.32.3
 wget~=3.2
-typer~=0.15.1
+typer~=0.24.1
 seaborn~=0.13.2