llama : refactor unicode stuff (#5992)

* llama : refactor unicode stuff

ggml-ci

* unicode : names

* make : fix c++ compiler

* unicode : names

* unicode : straighten tables

* zig : fix build

* unicode : put nfd normalization behind API

ggml-ci

* swift : fix build

* unicode : add BOM

* unicode : add <cstdint>

ggml-ci

* unicode : pass as cpts as const ref

.github/workflows/build.yml

@@ -425,6 +425,8 @@ jobs:
             defines: '-DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DLLAMA_KOMPUTE=ON -DKOMPUTE_OPT_DISABLE_VULKAN_VERSION_CHECK=ON -DBUILD_SHARED_LIBS=ON'
           - build: 'vulkan'
             defines: '-DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DLLAMA_VULKAN=ON -DBUILD_SHARED_LIBS=ON'
+          - build: 'arm64'
+            defines: '-A ARM64 -DLLAMA_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DBUILD_SHARED_LIBS=ON'
 
     steps:
       - name: Clone
@@ -520,7 +522,7 @@ jobs:
       - name: Test
         id: cmake_test
         # not all machines have native AVX-512
-        if: ${{ matrix.build != 'clblast' && matrix.build != 'kompute' && matrix.build != 'vulkan' && (matrix.build != 'avx512' || env.HAS_AVX512F == '1') }}
+        if: ${{ matrix.build != 'arm64' && matrix.build != 'clblast' && matrix.build != 'kompute' && matrix.build != 'vulkan' && (matrix.build != 'avx512' || env.HAS_AVX512F == '1') }}
         run: |
           cd build
           ctest -L main -C Release --verbose --timeout 900

.github/workflows/server.yml

@@ -47,6 +47,8 @@ jobs:
       - name: Clone
         id: checkout
         uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
 
       - name: Dependencies
         id: depends
@@ -58,7 +60,6 @@ jobs:
             cmake \
             python3-pip \
             wget \
-            psmisc \
             language-pack-en
 
       - name: Build
@@ -90,3 +91,46 @@ jobs:
         run: |
           cd examples/server/tests
           PORT=8888 ./tests.sh --stop --no-skipped --no-capture --tags slow
+
+
+  server-windows:
+    runs-on: windows-latest
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+
+      - name: Build
+        id: cmake_build
+        run: |
+          mkdir build
+          cd build
+          cmake ..  -DLLAMA_BUILD_SERVER=ON -DCMAKE_BUILD_TYPE=Release ;
+          cmake --build . --config Release -j ${env:NUMBER_OF_PROCESSORS} --target server
+
+      - name: Python setup
+        id: setup_python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+
+      - name: Tests dependencies
+        id: test_dependencies
+        run: |
+          pip install -r examples/server/tests/requirements.txt
+
+      - name: Tests
+        id: server_integration_tests
+        run: |
+          cd examples/server/tests
+          behave.exe --summary --stop --no-capture --exclude 'issues|wrong_usages|passkey' --tags llama.cpp
+
+      - name: Slow tests
+        id: server_integration_tests_slow
+        if: ${{ github.event.schedule != '' || github.event.inputs.slow_tests == 'true' }}
+        run: |
+          cd examples/server/tests
+          behave.exe --stop --no-skipped --no-capture --tags slow

.gitignore

@@ -45,6 +45,7 @@ models-mnt
 /embedding
 /gguf
 /gguf-llama-simple
+/gritlm
 /imatrix
 /infill
 /libllama.so

CMakeLists.txt

@@ -116,6 +116,7 @@ option(LLAMA_MPI                             "llama: use MPI"
 option(LLAMA_QKK_64                          "llama: use super-block size of 64 for k-quants"   OFF)
 option(LLAMA_SYCL                            "llama: use SYCL"                                  OFF)
 option(LLAMA_SYCL_F16                        "llama: use 16 bit floats for sycl calculations"   OFF)
+set(LLAMA_SYCL_TARGET   "INTEL" CACHE STRING "llama: sycl target device")
 option(LLAMA_CPU_HBM                         "llama: use memkind for CPU HBM"                   OFF)
 
 option(LLAMA_BUILD_TESTS                     "llama: build tests"    ${LLAMA_STANDALONE})
@@ -207,7 +208,7 @@ if (LLAMA_METAL)
         enable_language(ASM)
         add_compile_definitions(GGML_METAL_EMBED_LIBRARY)
 
-        set(METALLIB_SOURCE "${CMAKE_SOURCE_DIR}/ggml-metal.metal")
+        set(METALLIB_SOURCE "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal.metal")
         file(MAKE_DIRECTORY "${CMAKE_BINARY_DIR}/autogenerated")
         set(EMBED_METALLIB_ASSEMBLY "${CMAKE_BINARY_DIR}/autogenerated/ggml-embed-metallib.s")
 
@@ -534,6 +535,10 @@ if (LLAMA_HIPBLAS)
 endif()
 
 if (LLAMA_SYCL)
+    if (NOT LLAMA_SYCL_TARGET MATCHES "^(INTEL|NVIDIA)$")
+        message(FATAL_ERROR "Invalid backend chosen, supported options are INTEL or NVIDIA")
+    endif()
+
     if ( NOT DEFINED ENV{ONEAPI_ROOT})
         message(FATAL_ERROR "Not detect ENV {ONEAPI_ROOT}, please install oneAPI & source it, like: source /opt/intel/oneapi/setvars.sh")
     endif()
@@ -555,6 +560,9 @@ if (LLAMA_SYCL)
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-narrowing")
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O3")
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl -L${MKLROOT}/lib")
+    if (LLAMA_SYCL_TARGET STREQUAL "NVIDIA")
+        set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl-targets=nvptx64-nvidia-cuda")
+    endif()
 
     set(GGML_HEADERS_SYCL ggml-sycl.h)
     set(GGML_SOURCES_SYCL ggml-sycl.cpp)
@@ -562,7 +570,11 @@ if (LLAMA_SYCL)
     if (WIN32)
         set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} -fsycl sycl7 OpenCL mkl_sycl_blas_dll.lib mkl_intel_ilp64_dll.lib mkl_sequential_dll.lib mkl_core_dll.lib)
     else()
-        set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} -fsycl OpenCL mkl_core pthread m dl mkl_sycl_blas mkl_intel_ilp64 mkl_tbb_thread)
+        if (LLAMA_SYCL_TARGET STREQUAL "INTEL")
+            set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} -fsycl OpenCL mkl_core pthread m dl mkl_sycl_blas mkl_intel_ilp64 mkl_tbb_thread)
+        elseif (LLAMA_SYCL_TARGET STREQUAL "NVIDIA")
+            set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} -fsycl pthread m dl onemkl)
+        endif()
     endif()
 endif()
 
@@ -1129,6 +1141,8 @@ endif()
 add_library(llama
             llama.cpp
             llama.h
+            unicode.h
+            unicode.cpp
             )
 
 target_include_directories(llama PUBLIC .)

Makefile

@@ -2,7 +2,7 @@
 BUILD_TARGETS = \
 	main quantize quantize-stats perplexity imatrix embedding vdot q8dot train-text-from-scratch convert-llama2c-to-ggml \
 	simple batched batched-bench save-load-state server gguf llama-bench libllava.a llava-cli baby-llama beam-search  \
-	speculative infill tokenize benchmark-matmult parallel finetune export-lora lookahead lookup passkey tests/test-c.o
+	speculative infill tokenize benchmark-matmult parallel finetune export-lora lookahead lookup passkey gritlm tests/test-c.o
 
 # Binaries only useful for tests
 TEST_TARGETS = \
@@ -633,9 +633,12 @@ ggml-backend.o: ggml-backend.c ggml.h ggml-backend.h
 ggml-quants.o: ggml-quants.c ggml.h ggml-quants.h ggml-common.h
 	$(CC) $(CFLAGS)    -c $< -o $@
 
-OBJS += ggml-alloc.o ggml-backend.o ggml-quants.o
+unicode.o: unicode.cpp unicode.h
+	$(CXX) $(CXXFLAGS) -c $< -o $@
 
-llama.o: llama.cpp ggml.h ggml-alloc.h ggml-backend.h ggml-cuda.h ggml-metal.h llama.h
+OBJS += ggml-alloc.o ggml-backend.o ggml-quants.o unicode.o
+
+llama.o: llama.cpp unicode.h ggml.h ggml-alloc.h ggml-backend.h ggml-cuda.h ggml-metal.h llama.h
 	$(CXX) $(CXXFLAGS) -c $< -o $@
 
 COMMON_H_DEPS = common/common.h common/sampling.h common/log.h
@@ -724,6 +727,10 @@ embedding: examples/embedding/embedding.cpp                   ggml.o llama.o $(C
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
 
+gritlm: examples/gritlm/gritlm.cpp                         ggml.o llama.o $(COMMON_DEPS) $(OBJS)
+	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+
 save-load-state: examples/save-load-state/save-load-state.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)

Package.swift

@@ -31,6 +31,7 @@ let package = Package(
             sources: [
                 "ggml.c",
                 "llama.cpp",
+                "unicode.cpp",
                 "ggml-alloc.c",
                 "ggml-backend.c",
                 "ggml-quants.c",

README-sycl.md

@@ -73,6 +73,29 @@ For iGPU, please make sure the shared memory from host memory is enough. For lla
 
 For dGPU, please make sure the device memory is enough. For llama-2-7b.Q4_0, recommend the device memory is 4GB+.
 
+## Nvidia GPU
+
+### Verified
+
+|Intel GPU| Status | Verified Model|
+|-|-|-|
+|Ampere Series| Support| A100|
+
+### oneMKL
+
+The current oneMKL release does not contain the oneMKL cuBlas backend.
+As a result for Nvidia GPU's oneMKL must be built from source.
+
+```
+git clone https://github.com/oneapi-src/oneMKL
+cd oneMKL
+mkdir build
+cd build
+cmake -G Ninja .. -DCMAKE_CXX_COMPILER=icpx -DCMAKE_C_COMPILER=icx -DENABLE_MKLGPU_BACKEND=OFF -DENABLE_MKLCPU_BACKEND=OFF -DENABLE_CUBLAS_BACKEND=ON
+ninja
+// Add paths as necessary
+```
+
 ## Docker
 
 Note:
@@ -186,6 +209,9 @@ source /opt/intel/oneapi/setvars.sh
 # Or, for FP32:
 cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
 
+# For Nvidia GPUs
+cmake .. -DLLAMA_SYCL=ON -DLLAMA_SYCL_TARGET=NVIDIA -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
+
 # Build example/main only
 #cmake --build . --config Release --target main
 

README.md

@@ -16,11 +16,9 @@ Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others)
 
 ### Hot topics
 
-- The `api_like_OAI.py` script has been removed - use `server` instead ([#5766](https://github.com/ggerganov/llama.cpp/issues/5766#issuecomment-1969037761))
-- Support for chat templates: [Wiki (contributions welcome)](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template)
-- Support for Gemma models: https://github.com/ggerganov/llama.cpp/pull/5631
-- Non-linear quantization IQ4_NL: https://github.com/ggerganov/llama.cpp/pull/5590
-- Looking for contributions to improve and maintain the `server` example: https://github.com/ggerganov/llama.cpp/issues/4216
+- Looking for contributions to add Deepseek support: https://github.com/ggerganov/llama.cpp/issues/5981
+- Quantization blind testing: https://github.com/ggerganov/llama.cpp/discussions/5962
+- Initial Mamba support has been added: https://github.com/ggerganov/llama.cpp/pull/5328
 
 ----
 

build.zig

@@ -115,6 +115,7 @@ pub fn build(b: *std.build.Builder) !void {
     const ggml_alloc = make.obj("ggml-alloc", "ggml-alloc.c");
     const ggml_backend = make.obj("ggml-backend", "ggml-backend.c");
     const ggml_quants = make.obj("ggml-quants", "ggml-quants.c");
+    const unicode = make.obj("unicode", "unicode.cpp");
     const llama = make.obj("llama", "llama.cpp");
     const buildinfo = make.obj("common", "common/build-info.cpp");
     const common = make.obj("common", "common/common.cpp");
@@ -125,14 +126,14 @@ pub fn build(b: *std.build.Builder) !void {
     const clip = make.obj("clip", "examples/llava/clip.cpp");
     const llava = make.obj("llava", "examples/llava/llava.cpp");
 
-    _ = make.exe("main", "examples/main/main.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, common, buildinfo, sampling, console, grammar_parser });
-    _ = make.exe("quantize", "examples/quantize/quantize.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, common, buildinfo });
-    _ = make.exe("perplexity", "examples/perplexity/perplexity.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, common, buildinfo });
-    _ = make.exe("embedding", "examples/embedding/embedding.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, common, buildinfo });
-    _ = make.exe("finetune", "examples/finetune/finetune.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, common, buildinfo, train });
-    _ = make.exe("train-text-from-scratch", "examples/train-text-from-scratch/train-text-from-scratch.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, common, buildinfo, train });
+    _ = make.exe("main", "examples/main/main.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, common, buildinfo, sampling, console, grammar_parser });
+    _ = make.exe("quantize", "examples/quantize/quantize.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, common, buildinfo });
+    _ = make.exe("perplexity", "examples/perplexity/perplexity.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, common, buildinfo });
+    _ = make.exe("embedding", "examples/embedding/embedding.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, common, buildinfo });
+    _ = make.exe("finetune", "examples/finetune/finetune.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, common, buildinfo, train });
+    _ = make.exe("train-text-from-scratch", "examples/train-text-from-scratch/train-text-from-scratch.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, common, buildinfo, train });
 
-    const server = make.exe("server", "examples/server/server.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, common, buildinfo, sampling, grammar_parser, clip, llava });
+    const server = make.exe("server", "examples/server/server.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, common, buildinfo, sampling, grammar_parser, clip, llava });
     if (server.target.isWindows()) {
         server.linkSystemLibrary("ws2_32");
     }

common/grammar-parser.cpp

@@ -278,6 +278,22 @@ namespace grammar_parser {
             while (*pos) {
                 pos = parse_rule(state, pos);
             }
+            // Validate the state to ensure that all rules are defined
+            for (const auto & rule : state.rules) {
+                for (const auto & elem : rule) {
+                    if (elem.type == LLAMA_GRETYPE_RULE_REF) {
+                        // Ensure that the rule at that location exists
+                        if (elem.value >= state.rules.size() || state.rules[elem.value].empty()) {
+                            // Get the name of the rule that is missing
+                            for (const auto & kv : state.symbol_ids) {
+                                if (kv.second == elem.value) {
+                                    throw std::runtime_error("Undefined rule identifier '" + kv.first + "'");
+                                }
+                            }
+                        }
+                    }
+                }
+            }
             return state;
         } catch (const std::exception & err) {
             fprintf(stderr, "%s: error parsing grammar: %s\n", __func__, err.what());

examples/CMakeLists.txt

@@ -20,6 +20,7 @@ else()
     add_subdirectory(convert-llama2c-to-ggml)
     add_subdirectory(embedding)
     add_subdirectory(finetune)
+    add_subdirectory(gritlm)
     add_subdirectory(infill)
     add_subdirectory(llama-bench)
     add_subdirectory(llava)

examples/benchmark/benchmark-matmult.cpp

@@ -189,12 +189,10 @@ int main(int argc, char ** argv)  {
 
     int32_t nelements = sizex*sizey;
 
-    std::vector<int64_t> hist_cur(1 << 4, 0);
-
     // Set up a the benchmark matrices
     // printf("Creating new tensor q11 & Running quantize\n");
     struct ggml_tensor * q11 = ggml_new_tensor_2d(ctx, qtype, sizex, sizey);
-    ggml_quantize_chunk(qtype, (const float *) m11->data, q11->data, 0, nelements/m11->ne[0], m11->ne[0], hist_cur.data(), nullptr);
+    ggml_quantize_chunk(qtype, (const float *) m11->data, q11->data, 0, nelements/m11->ne[0], m11->ne[0], nullptr);
 
     // Set up a the compute graph
     // printf("Creating new tensor q31\n");
@@ -207,7 +205,7 @@ int main(int argc, char ** argv)  {
     // Set up a second graph computation to make sure we override the CPU cache lines
     // printf("Creating new tensor q12 & Running quantize\n");
     struct ggml_tensor * q12 = ggml_new_tensor_2d(ctx, qtype, sizex, sizey);
-    ggml_quantize_chunk(qtype, (const float *) m12->data, q12->data, 0, nelements/m12->ne[0], m12->ne[0], hist_cur.data(), nullptr);
+    ggml_quantize_chunk(qtype, (const float *) m12->data, q12->data, 0, nelements/m12->ne[0], m12->ne[0], nullptr);
 
     // printf("Creating new tensor q32\n");
     struct ggml_tensor * q32 = ggml_mul_mat(ctx, q12, m2);

examples/gritlm/CMakeLists.txt

@@ -0,0 +1,5 @@
+set(TARGET gritlm)
+add_executable(${TARGET} gritlm.cpp)
+install(TARGETS ${TARGET} RUNTIME)
+target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
+target_compile_features(${TARGET} PRIVATE cxx_std_11)

examples/gritlm/gritlm.cpp

@@ -0,0 +1,229 @@
+#include "common.h"
+#include "llama.h"
+
+#include <string>
+#include <vector>
+
+// #define GRIT_DEBUG
+
+static float dot_product(const std::vector<float> & v1, const std::vector<float> & v2) {
+    float dot = 0.0f;
+    for (uint64_t i = 0; i < v1.size(); ++i) {
+        dot += v1[i] * v2[i];
+    }
+    return dot;
+}
+
+static float norm(const std::vector<float> & v) {
+    return std::sqrt(dot_product(v, v));
+}
+
+static float cosine_similarity(const std::vector<float> & v1, const std::vector<float> & v2) {
+    return dot_product(v1, v2) / (norm(v1) * norm(v2));
+}
+
+static std::vector<std::vector<float>> encode(llama_context * ctx, const std::vector<std::string> & sentences, const std::string & instruction) {
+    std::vector<std::vector<float>> result;
+
+    const llama_model * mdl = llama_get_model(ctx);
+
+    llama_batch batch = llama_batch_init(llama_n_batch(ctx), 0, 1);
+
+    for (uint64_t i = 0; i < sentences.size(); i++) {
+        llama_batch_clear(batch);
+
+        const std::string input_string = instruction + sentences[i];
+
+        std::vector<llama_token> inputs = llama_tokenize(mdl, input_string, true, false);
+
+        const int32_t n_toks = inputs.size();
+
+        // GritLM seems to have EOS = ""
+        // https://github.com/ContextualAI/gritlm/blob/92025b16534712b31b3c4aaaf069350e222bd5f8/gritlm/gritlm.py#L18
+        // inputs.push_back(llama_token_eos(mdl));
+
+        // we want to ignore instruction tokens for mean pooling
+        const int32_t n_inst = llama_tokenize(mdl, instruction, true, false).size();
+
+#ifdef GRIT_DEBUG
+        // debug tokens - should be matching as referenced in the GritLM sample
+        std::for_each(inputs.begin(), inputs.end(), [&ctx](llama_token t) {
+            std::printf("[%u:%s]", t, llama_token_to_piece(ctx, t).c_str());
+        });
+        std::printf("\n");
+#endif
+
+        // add input to batch (this increments n_tokens)
+        for (int32_t j = 0; j < n_toks; j++) {
+            llama_batch_add(batch, inputs[j], j, { 0 }, j >= n_inst);
+        }
+
+        // clear previous kv_cache values (irrelevant for embeddings)
+        llama_kv_cache_clear(ctx);
+        llama_set_causal_attn(ctx, false);
+
+        // run model
+        llama_decode(ctx, batch);
+
+        // get embedding dimensions
+        uint64_t n_embd = llama_n_embd(mdl);
+
+        // allocate embedding output
+        std::vector<float> emb_unorm(n_embd, 0.0f);
+
+        // sum up all token embeddings
+        for (int32_t k = n_inst; k < n_toks; k++) {
+            float * emb = llama_get_embeddings_ith(ctx, k);
+            for (uint64_t j = 0; j < n_embd; j++) {
+                emb_unorm[j] += emb[j];
+            }
+        }
+
+        // divide by number of tokens (mean pooling)
+        {
+            const uint64_t n_sent = n_toks - n_inst;
+
+            for (uint64_t j = 0; j < n_embd; j++) {
+                emb_unorm[j] /= n_sent;
+            }
+        }
+
+        std::vector<float> emb_norm(emb_unorm.size());
+        llama_embd_normalize(emb_unorm.data(), emb_norm.data(), n_embd);
+        result.push_back(emb_norm);
+
+#ifdef GRIT_DEBUG
+        // print out emb_norm
+        std::printf("embedding %ld: ", i);
+        for (uint64_t j = 0; j < n_embd; j++) {
+            std::printf("%.5f ", emb_norm[j]);
+        }
+        std::printf("\n\n");
+#endif
+    }
+
+    llama_batch_free(batch);
+
+    return result;
+}
+
+static std::string generate(llama_context * ctx, const std::string & prompt, bool stream) {
+    std::string result;
+
+    const llama_model * mdl = llama_get_model(ctx);
+    llama_token eos_token = llama_token_eos(mdl);
+
+    llama_kv_cache_clear(ctx);
+    llama_set_causal_attn(ctx, true);
+    llama_batch bat = llama_batch_init(llama_n_batch(ctx), 0, 1);
+
+    std::vector<llama_token> inputs = llama_tokenize(mdl, prompt, false, true);
+    int32_t i_current_token = 0;
+
+    while (true) {
+        llama_batch_clear(bat);
+        auto n_inputs = (int32_t)inputs.size();
+        for (int32_t i = 0; i < n_inputs; i++) {
+            llama_batch_add(bat, inputs[i], i_current_token++, { 0 }, i == n_inputs - 1);
+        }
+        inputs.clear();
+
+        llama_decode(ctx, bat);
+        auto logits = llama_get_logits_ith(ctx, bat.n_tokens - 1);
+
+        auto candidates = std::vector<llama_token_data>(llama_n_vocab(mdl));
+        auto n_candidates = (int32_t)candidates.size();
+        for (int32_t token = 0; token < n_candidates; token++) {
+            candidates[token] = llama_token_data{ token, logits[token], 0.0f };
+        }
+        auto candidates_p = llama_token_data_array{ candidates.data(), candidates.size(), false };
+
+        llama_token token = llama_sample_token_greedy(ctx, &candidates_p);
+        if (token == eos_token) {
+            break;
+        }
+
+        std::string piece = llama_token_to_piece(ctx, token);
+        if (stream) {
+            std::printf("%s", piece.c_str());
+            std::fflush(stdout);
+        }
+
+        inputs.push_back(token);
+
+        result += piece;
+    }
+
+    if (stream) {
+        std::printf("\n");
+    }
+
+    llama_batch_free(bat);
+
+    return result;
+}
+
+static std::string gritlm_instruction(const std::string & instruction) {
+    return !instruction.empty() ? "<|user|>\n" + instruction + "\n<|embed|>\n" : "<|embed|>\n";
+}
+
+int main(int argc, char * argv[]) {
+    gpt_params params;
+    if (!gpt_params_parse(argc, argv, params)) {
+        return 1;
+    }
+
+    llama_model_params mparams = llama_model_params_from_gpt_params(params);
+    llama_context_params cparams = llama_context_params_from_gpt_params(params);
+
+    llama_backend_init();
+
+    llama_model * mdl = llama_load_model_from_file(params.model.c_str(), mparams);
+
+    // create new context - set to embedding mode
+    cparams.embeddings = true;
+    llama_context * ctx = llama_new_context_with_model(mdl, cparams);
+
+    // ### Embedding/Representation ###
+    // samples taken from: https://github.com/ContextualAI/gritlm#basic
+    {
+        const std::string instruction = "Given a scientific paper title, retrieve the paper's abstract";
+
+        const std::vector<std::string> queries = {
+            "Bitcoin: A Peer-to-Peer Electronic Cash System",
+            "Generative Representational Instruction Tuning",
+        };
+
+        const std::vector<std::string> documents = {
+            "A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they'll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone.",
+            "All text-based language problems can be reduced to either generation or embedding. Current models only perform well at one or the other. We introduce generative representational instruction tuning (GRIT) whereby a large language model is trained to handle both generative and embedding tasks by distinguishing between them through instructions. Compared to other open models, our resulting GritLM 7B sets a new state of the art on the Massive Text Embedding Benchmark (MTEB) and outperforms all models up to its size on a range of generative tasks. By scaling up further, GritLM 8X7B outperforms all open generative language models that we tried while still being among the best embedding models. Notably, we find that GRIT matches training on only generative or embedding data, thus we can unify both at no performance loss. Among other benefits, the unification via GRIT speeds up Retrieval-Augmented Generation (RAG) by > 60% for long documents, by no longer requiring separate retrieval and generation models. Models, code, etc. are freely available at https://github.com/ContextualAI/gritlm.",
+        };
+
+        // No need to add instruction for retrieval documents
+        const std::vector<std::vector<float>> d_rep = encode(ctx, documents, gritlm_instruction(""));
+        const std::vector<std::vector<float>> q_rep = encode(ctx, queries,   gritlm_instruction(instruction));
+
+        const float cosine_sim_q0_d0 = cosine_similarity(q_rep[0], d_rep[0]);
+        const float cosine_sim_q0_d1 = cosine_similarity(q_rep[0], d_rep[1]);
+        const float cosine_sim_q1_d0 = cosine_similarity(q_rep[1], d_rep[0]);
+        const float cosine_sim_q1_d1 = cosine_similarity(q_rep[1], d_rep[1]);
+
+        std::printf("Cosine similarity between \"%.50s\" and \"%.50s\" is: %.3f\n", queries[0].c_str(), documents[0].c_str(), cosine_sim_q0_d0);
+        std::printf("Cosine similarity between \"%.50s\" and \"%.50s\" is: %.3f\n", queries[0].c_str(), documents[1].c_str(), cosine_sim_q0_d1);
+        std::printf("Cosine similarity between \"%.50s\" and \"%.50s\" is: %.3f\n", queries[1].c_str(), documents[0].c_str(), cosine_sim_q1_d0);
+        std::printf("Cosine similarity between \"%.50s\" and \"%.50s\" is: %.3f\n", queries[1].c_str(), documents[1].c_str(), cosine_sim_q1_d1);
+    }
+
+    // ### Generation ###
+    // GritLM models are not finetuned with system prompts, as you can just include system-like instructions together with your user instruction
+    {
+        const std::string prompt = "<|user|>\nPlease write me a poem about my recent hike of Mt. Fuji at midnight in the style of Shakespeare.\n<|assistant|>\n";
+        std::string response = generate(ctx, prompt, true);
+    }
+
+    llama_free(ctx);
+    llama_free_model(mdl);
+    llama_backend_free();
+
+    return 0;
+}

examples/llama.android/app/src/main/cpp/llama-android.cpp

@@ -33,6 +33,45 @@ jclass la_int_var;
 jmethodID la_int_var_value;
 jmethodID la_int_var_inc;
 
+std::string cached_token_chars;
+
+bool is_valid_utf8(const char * string) {
+    if (!string) {
+        return true;
+    }
+
+    const unsigned char * bytes = (const unsigned char *)string;
+    int num;
+
+    while (*bytes != 0x00) {
+        if ((*bytes & 0x80) == 0x00) {
+            // U+0000 to U+007F
+            num = 1;
+        } else if ((*bytes & 0xE0) == 0xC0) {
+            // U+0080 to U+07FF
+            num = 2;
+        } else if ((*bytes & 0xF0) == 0xE0) {
+            // U+0800 to U+FFFF
+            num = 3;
+        } else if ((*bytes & 0xF8) == 0xF0) {
+            // U+10000 to U+10FFFF
+            num = 4;
+        } else {
+            return false;
+        }
+
+        bytes += 1;
+        for (int i = 1; i < num; ++i) {
+            if ((*bytes & 0xC0) != 0x80) {
+                return false;
+            }
+            bytes += 1;
+        }
+    }
+
+    return true;
+}
+
 static void log_callback(ggml_log_level level, const char * fmt, void * data) {
     if (level == GGML_LOG_LEVEL_ERROR)     __android_log_print(ANDROID_LOG_ERROR, TAG, fmt, data);
     else if (level == GGML_LOG_LEVEL_INFO) __android_log_print(ANDROID_LOG_INFO, TAG, fmt, data);
@@ -295,6 +334,8 @@ Java_com_example_llama_Llm_completion_1init(
         jint n_len
     ) {
 
+    cached_token_chars.clear();
+
     const auto text = env->GetStringUTFChars(jtext, 0);
     const auto context = reinterpret_cast<llama_context *>(context_pointer);
     const auto batch = reinterpret_cast<llama_batch *>(batch_pointer);
@@ -372,8 +413,16 @@ Java_com_example_llama_Llm_completion_1loop(
     }
 
     auto new_token_chars = llama_token_to_piece(context, new_token_id);
-    LOGi("new_token_chars: `%s`", new_token_chars.c_str());
-    auto new_token = env->NewStringUTF(new_token_chars.c_str());
+    cached_token_chars += new_token_chars;
+
+    jstring new_token = nullptr;
+    if (is_valid_utf8(cached_token_chars.c_str())) {
+        new_token = env->NewStringUTF(cached_token_chars.c_str());
+        LOGi("cached: %s, new_token_chars: `%s`, id: %d", cached_token_chars.c_str(), new_token_chars.c_str(), new_token_id);
+        cached_token_chars.clear();
+    } else {
+        new_token = env->NewStringUTF("");
+    }
 
     llama_batch_clear(*batch);
     llama_batch_add(*batch, new_token_id, n_cur, { 0 }, true);

examples/llama.android/app/src/main/java/com/example/llama/Llm.kt

@@ -71,7 +71,7 @@ class Llm {
         batch: Long,
         nLen: Int,
         ncur: IntVar
-    ): String
+    ): String?
 
     private external fun kv_cache_clear(context: Long)
 
@@ -115,7 +115,7 @@ class Llm {
                 val ncur = IntVar(completion_init(state.context, state.batch, message, nlen))
                 while (ncur.value <= nlen) {
                     val str = completion_loop(state.context, state.batch, nlen, ncur)
-                    if (str.isEmpty()) {
+                    if (str == null) {
                         break
                     }
                     emit(str)

examples/llava/clip.cpp

@@ -1862,7 +1862,6 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
 
     std::vector<uint8_t> work(512);
     std::vector<float> conv_buf(512);
-    std::vector<int64_t> hist_all(1 << 4, 0);
     size_t total_size_org = 0;
     size_t total_size_new = 0;
 
@@ -1917,48 +1916,7 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
             }
             new_data = work.data();
 
-            std::vector<int64_t> hist_cur(1 << 4, 0);
-
-            switch (new_type) {
-                case GGML_TYPE_Q4_0: {
-                    new_size = ggml_quantize_q4_0(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
-                } break;
-                case GGML_TYPE_Q4_1: {
-                    new_size = ggml_quantize_q4_1(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
-                } break;
-                case GGML_TYPE_Q5_0: {
-                    new_size = ggml_quantize_q5_0(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
-                } break;
-                case GGML_TYPE_Q5_1: {
-                    new_size = ggml_quantize_q5_1(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
-                } break;
-                case GGML_TYPE_Q8_0: {
-                    new_size = ggml_quantize_q8_0(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
-                } break;
-                case GGML_TYPE_Q2_K: {
-                    new_size = ggml_quantize_q2_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
-                } break;
-                case GGML_TYPE_Q3_K: {
-                    new_size = ggml_quantize_q3_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
-                } break;
-                case GGML_TYPE_Q4_K: {
-                    new_size = ggml_quantize_q4_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
-                } break;
-                case GGML_TYPE_Q5_K: {
-                    new_size = ggml_quantize_q5_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
-                } break;
-                case GGML_TYPE_Q6_K: {
-                    new_size = ggml_quantize_q6_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
-                } break;
-                default: {
-                    fprintf(stderr, "%s: unsupported quantization type %d\n", __func__, new_type);
-                    return false;
-                }
-            }
-
-            for (size_t j = 0; j < hist_cur.size(); ++j) {
-                hist_all[j] += hist_cur[j];
-            }
+            new_size = ggml_quantize_chunk(new_type, f32_data, new_data, 0, n_elms/cur->ne[0], cur->ne[0], nullptr);
         } else {
             new_type = cur->type;
             new_data = cur->data;
@@ -1993,17 +1951,6 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
     {
         printf("%s: original  size = %8.2f MB\n", __func__, total_size_org / 1024.0 / 1024.0);
         printf("%s: quantized size = %8.2f MB\n", __func__, total_size_new / 1024.0 / 1024.0);
-
-        int64_t sum_all = 0;
-        for (size_t i = 0; i < hist_all.size(); ++i) {
-            sum_all += hist_all[i];
-        }
-
-        printf("%s: hist: ", __func__);
-        for (size_t i = 0; i < hist_all.size(); ++i) {
-            printf("%5.3f ", hist_all[i] / (float)sum_all);
-        }
-        printf("\n");
     }
 
     return true;

examples/perplexity/perplexity.cpp

@@ -442,7 +442,7 @@ static results_perplexity perplexity_v2(llama_context * ctx, const gpt_params &
     return {tokens, std::exp(nll / count), logit_history, prob_history};
 }
 
-static results_perplexity perplexity(llama_context * ctx, const gpt_params & params) {
+static results_perplexity perplexity(llama_context * ctx, const gpt_params & params, const int32_t n_ctx) {
     if (params.ppl_stride > 0) {
         return perplexity_v2(ctx, params);
     }
@@ -453,7 +453,6 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par
     // BOS tokens will be added for each chunk before eval
 
     const bool add_bos = llama_should_add_bos_token(llama_get_model(ctx));
-    const int n_ctx = llama_n_ctx(ctx);
 
     std::ofstream logits_stream;
     if (!params.logits_file.empty()) {
@@ -499,13 +498,19 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par
     double nll2 = 0.0;
 
     const int num_batches = (n_ctx + n_batch - 1) / n_batch;
+    const int n_seq = std::max(1, n_batch / n_ctx);
+
+    GGML_ASSERT(n_batch < n_ctx || n_batch % n_ctx == 0);
+    GGML_ASSERT(params.n_ctx == n_seq * n_ctx);
+
+    llama_batch batch = llama_batch_init(std::min(n_batch, n_ctx*n_seq), 0, 1);
 
     std::vector<float> logits;
     if (num_batches > 1) {
         logits.reserve((size_t)n_ctx * n_vocab);
     }
 
-    fprintf(stderr, "%s: calculating perplexity over %d chunks, batch_size=%d\n", __func__, n_chunk, n_batch);
+    fprintf(stderr, "%s: calculating perplexity over %d chunks, n_ctx=%d, batch_size=%d, n_seq=%d\n", __func__, n_chunk, n_ctx, n_batch, n_seq);
 
     std::vector<std::thread> workers(std::thread::hardware_concurrency() - 1);
 
@@ -518,10 +523,26 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par
         log_probs.resize(n_ctx * nv);
     }
 
-    for (int i = 0; i < n_chunk; ++i) {
+    // We get the logits for all the tokens in the context window (params.n_ctx)
+    // from llama_eval above.  Now, based on https://huggingface.co/docs/transformers/perplexity,
+    // calculate the perplexity over the last half of the window (so the model always has
+    // some context to predict the token).
+    //
+    // We rely on the fact that attention in the forward pass only looks at previous
+    // tokens here, so the logits returned for each token are an accurate representation
+    // of what the model would have predicted at that point.
+    //
+    // Example, we have a context window of 512, we will compute perplexity for each of the
+    // last 256 tokens.  Then, we split the input up into context window size chunks to
+    // process the entire prompt.
+    const int first = n_ctx/2;
+
+    for (int i = 0; i < n_chunk; i += n_seq) {
         const int start =     i * n_ctx;
         const int end   = start + n_ctx;
 
+        const int n_seq_batch = std::min(n_seq, n_chunk - i);
+
         const auto t_start = std::chrono::high_resolution_clock::now();
 
         // clear the KV cache
@@ -531,22 +552,37 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par
             const int batch_start = start + j * n_batch;
             const int batch_size  = std::min(end - batch_start, n_batch);
 
-            // save original token and restore it after eval
-            const auto token_org = tokens[batch_start];
+            batch.n_tokens = 0;
+            for (int seq = 0; seq < n_seq_batch; seq++) {
+                int seq_start = batch_start + seq*n_ctx;
 
-            // add BOS token for the first batch of each chunk
-            if (add_bos && j == 0) {
-                tokens[batch_start] = llama_token_bos(llama_get_model(ctx));
+                // save original token and restore it after eval
+                const auto token_org = tokens[seq_start];
+
+                // add BOS token for the first batch of each chunk
+                if (add_bos && j == 0) {
+                    tokens[seq_start] = llama_token_bos(llama_get_model(ctx));
+                }
+
+                for (int k = 0; k < batch_size; ++k) {
+                    const int idx = seq*n_ctx + k;
+                    batch.token[idx] = tokens[seq_start + k];
+                    batch.pos[idx] = j*n_batch + k;
+                    batch.n_seq_id[idx] = 1;
+                    batch.seq_id[idx][0] = seq;
+                    batch.logits[idx] = batch.pos[idx] >= first ? 1 : 0;
+                }
+                batch.n_tokens += batch_size;
+
+                // restore the original token in case it was set to BOS
+                tokens[seq_start] = token_org;
             }
 
-            if (llama_decode(ctx, llama_batch_get_one(tokens.data() + batch_start, batch_size, j * n_batch, 0))) {
+            if (llama_decode(ctx, batch)) {
                 fprintf(stderr, "%s : failed to eval\n", __func__);
                 return {tokens, -1, logit_history, prob_history};
             }
 
-            // restore the original token in case it was set to BOS
-            tokens[batch_start] = token_org;
-
             if (num_batches > 1) {
                 const auto * batch_logits = llama_get_logits(ctx);
                 logits.insert(logits.end(), batch_logits, batch_logits + batch_size * n_vocab);
@@ -558,7 +594,7 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par
         if (i == 0) {
             const float t_total = std::chrono::duration<float>(t_end - t_start).count();
             fprintf(stderr, "%s: %.2f seconds per pass - ETA ", __func__, t_total);
-            int total_seconds = (int)(t_total * n_chunk);
+            int total_seconds = (int)(t_total*n_chunk/n_seq);
             if (total_seconds >= 60*60) {
                 fprintf(stderr, "%d hours ", total_seconds / (60*60));
                 total_seconds = total_seconds % (60*60);
@@ -566,37 +602,31 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par
             fprintf(stderr, "%.2f minutes\n", total_seconds / 60.0);
         }
 
-        // We get the logits for all the tokens in the context window (params.n_ctx)
-        // from llama_eval above.  Now, based on https://huggingface.co/docs/transformers/perplexity,
-        // calculate the perplexity over the last half of the window (so the model always has
-        // some context to predict the token).
-        //
-        // We rely on the fact that attention in the forward pass only looks at previous
-        // tokens here, so the logits returned for each token are an accurate representation
-        // of what the model would have predicted at that point.
-        //
-        // Example, we have a context window of 512, we will compute perplexity for each of the
-        // last 256 tokens.  Then, we split the input up into context window size chunks to
-        // process the entire prompt.
-        const int first = n_ctx/2;
-        const float * all_logits = num_batches > 1 ? logits.data() : llama_get_logits(ctx);
-        if (!params.logits_file.empty()) {
-            process_logits(logits_stream, n_vocab, all_logits + first*n_vocab, tokens.data() + start + first, n_ctx - 1 - first,
-                    workers, log_probs, nll, nll2);
-        } else {
-            process_logits(n_vocab, all_logits + first*n_vocab, tokens.data() + start + first, n_ctx - 1 - first,
-                    workers, nll, nll2, logit_history.data() + start + first, prob_history.data() + start + first);
-        }
-        count += n_ctx - first - 1;
+        for (int seq = 0; seq < n_seq_batch; seq++) {
+            const float * all_logits = num_batches > 1 ? logits.data() : llama_get_logits_ith(ctx, seq*n_ctx);
+            llama_token * tokens_data = tokens.data() + start + seq*n_ctx + first;
+            if (!params.logits_file.empty()) {
+                process_logits(logits_stream, n_vocab, all_logits + first*n_vocab,
+                        tokens_data, n_ctx - 1 - first,
+                        workers, log_probs, nll, nll2);
+            } else {
+                process_logits(n_vocab, all_logits + first*n_vocab,
+                        tokens_data, n_ctx - 1 - first,
+                        workers, nll, nll2,
+                        logit_history.data() + start + seq*n_ctx + first,
+                        prob_history.data()  + start + seq*n_ctx + first);
+            }
+            count += n_ctx - first - 1;
 
-        // perplexity is e^(average negative log-likelihood)
-        if (params.ppl_output_type == 0) {
-            printf("[%d]%.4lf,", i + 1, std::exp(nll / count));
-        } else {
-            double av = nll/count;
-            double av2 = nll2/count - av*av;
-            if (av2 > 0) av2 = sqrt(av2/(count-1));
-            printf("%8d  %.4lf  %4lf  %4lf\n", i*n_ctx, std::exp(nll / count), av, av2);
+            // perplexity is e^(average negative log-likelihood)
+            if (params.ppl_output_type == 0) {
+                printf("[%d]%.4lf,", i + seq + 1, std::exp(nll / count));
+            } else {
+                double av = nll/count;
+                double av2 = nll2/count - av*av;
+                if (av2 > 0) av2 = sqrt(av2/(count-1));
+                printf("%8d  %.4lf  %4lf  %4lf\n", i*n_ctx, std::exp(nll / count), av, av2);
+            }
         }
         fflush(stdout);
 
@@ -615,6 +645,8 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par
         printf("Unexpected negative standard deviation of log(prob)\n");
     }
 
+    llama_batch_free(batch);
+
     return {tokens, ppl, logit_history, prob_history};
 }
 
@@ -1782,13 +1814,24 @@ static void kl_divergence(llama_context * ctx, const gpt_params & params) {
 int main(int argc, char ** argv) {
     gpt_params params;
 
-    params.n_batch = 512;
     if (!gpt_params_parse(argc, argv, params)) {
         return 1;
     }
 
     params.logits_all = true;
-    params.n_batch = std::min(params.n_batch, params.n_ctx);
+
+    const int32_t n_ctx = params.n_ctx;
+
+    const bool ppl = !params.hellaswag && !params.winogrande && !params.multiple_choice && !params.kl_divergence;
+    if (ppl) {
+        int n_seq = std::max(1, params.n_batch / n_ctx);
+        int32_t n_kv = n_seq * n_ctx;
+        params.n_parallel = n_seq;
+        params.n_ctx = n_kv;
+        params.n_batch = std::min(params.n_batch, n_kv);
+    } else {
+        params.n_batch = std::min(params.n_batch, params.n_ctx);
+    }
 
     if (params.ppl_stride > 0) {
         fprintf(stderr, "Will perform strided perplexity calculation -> adjusting context size from %d to %d\n",
@@ -1847,7 +1890,7 @@ int main(int argc, char ** argv) {
     } else if (params.kl_divergence) {
         kl_divergence(ctx, params);
     } else {
-        results = perplexity(ctx, params);
+        results = perplexity(ctx, params, n_ctx);
     }
 
     llama_print_timings(ctx);

examples/server/README.md

@@ -123,10 +123,10 @@ You can consume the endpoints with Postman or NodeJS with axios library. You can
 ### Docker
 
 ```bash
-docker run -p 8080:8080 -v /path/to/models:/models ggerganov/llama.cpp:server -m models/7B/ggml-model.gguf -c 512 --host 0.0.0.0 --port 8080
+docker run -p 8080:8080 -v /path/to/models:/models ghcr.io/ggerganov/llama.cpp:server -m models/7B/ggml-model.gguf -c 512 --host 0.0.0.0 --port 8080
 
 # or, with CUDA:
-docker run -p 8080:8080 -v /path/to/models:/models --gpus all ggerganov/llama.cpp:server-cuda -m models/7B/ggml-model.gguf -c 512 --host 0.0.0.0 --port 8080 --n-gpu-layers 99
+docker run -p 8080:8080 -v /path/to/models:/models --gpus all ghcr.io/ggerganov/llama.cpp:server-cuda -m models/7B/ggml-model.gguf -c 512 --host 0.0.0.0 --port 8080 --n-gpu-layers 99
 ```
 
 ## Testing with CURL
@@ -195,7 +195,11 @@ node index.js
 
     *Options:*
 
-    `prompt`: Provide the prompt for this completion as a string or as an array of strings or numbers representing tokens. Internally, the prompt is compared to the previous completion and only the "unseen" suffix is evaluated. If the prompt is a string or an array with the first element given as a string, a `bos` token is inserted in the front like `main` does.
+    `prompt`: Provide the prompt for this completion as a string or as an array of strings or numbers representing tokens. Internally, if `cache_prompt` is `true`, the prompt is compared to the previous completion and only the "unseen" suffix is evaluated. A `BOS` token is inserted at the start, if all of the following conditions are true:
+
+      - The prompt is a string or an array with the first element given as a string
+      - The model's `tokenizer.ggml.add_bos_token` metadata is `true`
+      - The system prompt is empty
 
     `temperature`: Adjust the randomness of the generated text (default: 0.8).
 
@@ -308,7 +312,7 @@ Notice that each `probs` is an array of length `n_probs`.
 
     `content`: Set the text to tokenize.
 
-    Note that the special `BOS` token is not added in front of the text and also a space character is not inserted automatically as it is for `/completion`.
+    Note that a special `BOS` token is never inserted.
 
 - **POST** `/detokenize`: Convert tokens to text.
 
@@ -552,9 +556,51 @@ Run with bash:
 bash chat.sh
 ```
 
-### API like OAI
+### OAI-like API
 
-The HTTP server supports OAI-like API
+The HTTP server supports OAI-like API: https://github.com/openai/openai-openapi
+
+### API errors
+
+Server returns error in the same format as OAI: https://github.com/openai/openai-openapi
+
+Example of an error:
+
+```json
+{
+    "error": {
+        "code": 401,
+        "message": "Invalid API Key",
+        "type": "authentication_error"
+    }
+}
+```
+
+Apart from error types supported by OAI, we also have custom types that are specific to functionalities of llama.cpp:
+
+**When /metrics or /slots endpoint is disabled**
+
+```json
+{
+    "error": {
+        "code": 501,
+        "message": "This server does not support metrics endpoint.",
+        "type": "not_supported_error"
+    }
+}
+```
+
+**When the server receives invalid grammar via */completions endpoint**
+
+```json
+{
+    "error": {
+        "code": 400,
+        "message": "Failed to parse grammar",
+        "type": "invalid_request_error"
+    }
+}
+```
 
 ### Extending or building alternative Web Front End
 

examples/server/bench/README.md

@@ -0,0 +1,88 @@
+### Server benchmark tools
+
+Benchmark is using [k6](https://k6.io/).
+
+##### Install k6
+
+Follow instruction from: https://k6.io/docs/get-started/installation/
+
+Example for ubuntu:
+```shell
+snap install k6
+```
+
+#### Download a dataset
+
+This dataset was originally proposed in [vLLM benchmarks](https://github.com/vllm-project/vllm/blob/main/benchmarks/README.md).
+
+```shell
+wget https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json
+```
+
+#### Download a model
+Example for PHI-2
+
+```shell
+../../../scripts/hf.sh --repo ggml-org/models --file phi-2/ggml-model-q4_0.gguf
+```
+
+#### Start the server
+The server must answer OAI Chat completion requests on `http://localhost:8080/v1` or according to the environment variable `SERVER_BENCH_URL`.
+
+Example:
+```shell
+server --host localhost --port 8080 \
+  --model ggml-model-q4_0.gguf \
+  --cont-batching \
+  --metrics \
+  --parallel 8 \
+  --batch-size 512 \
+  --ctx-size 4096 \
+  --log-format text \
+  -ngl 33
+```
+
+#### Run the benchmark
+
+For 500 chat completions request with 8 concurrent users during maximum 10 minutes, run:
+```shell
+k6 run script.js --duration 10m --iterations 500 --vus 8
+```
+
+The benchmark values can be overridden with:
+- `SERVER_BENCH_URL` server url prefix for chat completions, default `http://localhost:8080/v1`
+- `SERVER_BENCH_N_PROMPTS` total prompts to randomly select in the benchmark, default `480`
+- `SERVER_BENCH_MODEL_ALIAS` model alias to pass in the completion request, default `my-model`
+- `SERVER_BENCH_MAX_TOKENS` max tokens to predict, default: `512`
+- `SERVER_BENCH_DATASET` path to the benchmark dataset file
+- `SERVER_BENCH_MAX_PROMPT_TOKENS` maximum prompt tokens to filter out in the dataset: default `1024`
+- `SERVER_BENCH_MAX_CONTEXT` maximum context size of the completions request to filter out in the dataset: prompt + predicted tokens, default `2048`
+
+Note: the local tokenizer is just a string space split, real number of tokens will differ.
+
+Or with [k6 options](https://k6.io/docs/using-k6/k6-options/reference/):
+
+```shell
+SERVER_BENCH_N_PROMPTS=500 k6 run script.js --duration 10m --iterations 500 --vus 8
+```
+
+To [debug http request](https://k6.io/docs/using-k6/http-debugging/) use `--http-debug="full"`.
+
+#### Metrics
+
+Following metrics are available computed from the OAI chat completions response `usage`:
+- `llamacpp_tokens_second` Trend of `usage.total_tokens / request duration`
+- `llamacpp_prompt_tokens` Trend of `usage.prompt_tokens`
+- `llamacpp_prompt_tokens_total_counter` Counter of `usage.prompt_tokens`
+- `llamacpp_completion_tokens` Trend of `usage.completion_tokens`
+- `llamacpp_completion_tokens_total_counter` Counter of `usage.completion_tokens`
+- `llamacpp_completions_truncated_rate` Rate of completions truncated, i.e. if `finish_reason === 'length'`
+- `llamacpp_completions_stop_rate` Rate of completions stopped by the model, i.e. if `finish_reason === 'stop'`
+
+The script will fail if too many completions are truncated, see `llamacpp_completions_truncated_rate`.
+
+K6 metrics might be compared against [server metrics](../README.md), with:
+
+```shell
+curl http://localhost:8080/metrics
+```

examples/server/bench/script.js

@@ -0,0 +1,120 @@
+import http from 'k6/http'
+import {check, sleep} from 'k6'
+import {SharedArray} from 'k6/data'
+import {Counter, Rate, Trend} from 'k6/metrics'
+import exec from 'k6/execution';
+
+// Server chat completions prefix
+const server_url = __ENV.SERVER_BENCH_URL ? __ENV.SERVER_BENCH_URL : 'http://localhost:8080/v1'
+
+// Number of total prompts in the dataset - default 10m / 10 seconds/request * number of users
+const n_prompt = __ENV.SERVER_BENCH_N_PROMPTS ? parseInt(__ENV.SERVER_BENCH_N_PROMPTS) : 600 / 10 * 8
+
+// Model name to request
+const model = __ENV.SERVER_BENCH_MODEL_ALIAS ? __ENV.SERVER_BENCH_MODEL_ALIAS : 'my-model'
+
+// Dataset path
+const dataset_path = __ENV.SERVER_BENCH_DATASET ? __ENV.SERVER_BENCH_DATASET : './ShareGPT_V3_unfiltered_cleaned_split.json'
+
+// Max tokens to predict
+const max_tokens = __ENV.SERVER_BENCH_MAX_TOKENS ? parseInt(__ENV.SERVER_BENCH_MAX_TOKENS) : 512
+
+// Max prompt tokens
+const n_prompt_tokens = __ENV.SERVER_BENCH_MAX_PROMPT_TOKENS ? parseInt(__ENV.SERVER_BENCH_MAX_PROMPT_TOKENS) : 1024
+
+// Max slot context
+const n_ctx_slot = __ENV.SERVER_BENCH_MAX_CONTEXT ? parseInt(__ENV.SERVER_BENCH_MAX_CONTEXT) : 2048
+
+export function setup() {
+    console.info(`Benchmark config: server_url=${server_url} n_prompt=${n_prompt} model=${model} dataset_path=${dataset_path} max_tokens=${max_tokens}`)
+}
+
+const data = new SharedArray('conversations', function () {
+    const tokenizer = (message) => message.split(/[\s,'".?]/)
+
+    return JSON.parse(open(dataset_path))
+        // Filter out the conversations with less than 2 turns.
+        .filter(data => data["conversations"].length >= 2)
+        .filter(data => data["conversations"][0]["from"] === "human")
+        .map(data => {
+            return {
+                prompt: data["conversations"][0]["value"],
+                n_prompt_tokens: tokenizer(data["conversations"][0]["value"]).length,
+                n_completion_tokens: tokenizer(data["conversations"][1]["value"]).length,
+            }
+        })
+        // Filter out too short sequences
+        .filter(conv => conv.n_prompt_tokens >= 4 && conv.n_completion_tokens >= 4)
+        // Filter out too long sequences.
+        .filter(conv => conv.n_prompt_tokens <= n_prompt_tokens && conv.n_prompt_tokens + conv.n_completion_tokens <= n_ctx_slot)
+        // Keep only first n prompts
+        .slice(0, n_prompt)
+})
+
+const llamacpp_prompt_tokens = new Trend('llamacpp_prompt_tokens')
+const llamacpp_completion_tokens = new Trend('llamacpp_completion_tokens')
+const llamacpp_tokens_second = new Trend('llamacpp_tokens_second')
+
+const llamacpp_prompt_tokens_total_counter = new Counter('llamacpp_prompt_tokens_total_counter')
+const llamacpp_completion_tokens_total_counter = new Counter('llamacpp_completion_tokens_total_counter')
+
+const llamacpp_completions_truncated_rate = new Rate('llamacpp_completions_truncated_rate')
+const llamacpp_completions_stop_rate = new Rate('llamacpp_completions_stop_rate')
+
+export const options = {
+    thresholds: {
+        llamacpp_completions_truncated_rate: [
+            // more than 80% of truncated input will abort the test
+            {threshold: 'rate < 0.8', abortOnFail: true, delayAbortEval: '1m'},
+        ],
+    },
+    duration: '10m',
+    vus: 8,
+}
+
+export default function () {
+    const conversation = data[exec.scenario.iterationInInstance % data.length]
+    const payload = {
+        "messages": [
+            {
+                "role": "system",
+                "content": "You are ChatGPT, an AI assistant.",
+            },
+            {
+                "role": "user",
+                "content": conversation.prompt,
+            }
+        ],
+        "model": model,
+        "stream": false,
+        "max_tokens": max_tokens
+    }
+
+    const body = JSON.stringify(payload)
+
+    let res = http.post(`${server_url}/chat/completions`, body, {
+        headers: {'Content-Type': 'application/json'},
+        timeout: '300s'
+    })
+
+    check(res, {'success completion': (r) => r.status === 200})
+
+    if (res.status === 200) {
+        const completions = res.json()
+
+        llamacpp_prompt_tokens.add(completions.usage.prompt_tokens)
+        llamacpp_prompt_tokens_total_counter.add(completions.usage.prompt_tokens)
+
+        llamacpp_completion_tokens.add(completions.usage.completion_tokens)
+        llamacpp_completion_tokens_total_counter.add(completions.usage.completion_tokens)
+
+        llamacpp_completions_truncated_rate.add(completions.choices[0].finish_reason === 'length')
+        llamacpp_completions_stop_rate.add(completions.choices[0].finish_reason === 'stop')
+
+        llamacpp_tokens_second.add(completions.usage.total_tokens / res.timings.duration * 1.e3)
+    } else {
+        console.error(`response: ${res.body} request=${payload}`)
+    }
+
+    sleep(0.3)
+}

examples/server/completion.js.hpp

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+  0x20, 0x20, 0x7d, 0x0a, 0x20, 0x20, 0x72, 0x65, 0x74, 0x75, 0x72, 0x6e,
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 };
-unsigned int completion_js_len = 5782;
+unsigned int completion_js_len = 5796;

examples/server/public/completion.js

@@ -96,18 +96,18 @@ export async function* llama(prompt, params = {}, config = {}) {
             }
           }
           if (result.error) {
-            result.error = JSON.parse(result.error);
-            if (result.error.content.includes('slot unavailable')) {
-              // Throw an error to be caught by upstream callers
-              throw new Error('slot unavailable');
-            } else {
-              console.error(`llama.cpp error: ${result.error.content}`);
+            try {
+              result.error = JSON.parse(result.error);
+              if (result.error.message.includes('slot unavailable')) {
+                // Throw an error to be caught by upstream callers
+                throw new Error('slot unavailable');
+              } else {
+                console.error(`llama.cpp error [${result.error.code} - ${result.error.type}]: ${result.error.message}`);
+              }
+            } catch(e) {
+              console.error(`llama.cpp error ${result.error}`)
             }
           }
-          if (result.error) {
-            result.error = JSON.parse(result.error);
-            console.error(`llama.cpp error: ${result.error.content}`);
-          }
         }
       }
     }

examples/server/server.cpp

@@ -341,7 +341,7 @@ struct server_slot {
 };
 
 struct server_metrics {
-    const int64_t t_start = ggml_time_us();
+    int64_t t_start = 0;
 
     uint64_t n_prompt_tokens_processed_total = 0;
     uint64_t t_prompt_processing_total       = 0;
@@ -354,14 +354,18 @@ struct server_metrics {
     uint64_t n_tokens_predicted  = 0;
     uint64_t t_tokens_generation = 0;
 
-    void on_prompt_eval(const server_slot &slot) {
+    void init() {
+        t_start = ggml_time_us();
+    }
+
+    void on_prompt_eval(const server_slot & slot) {
         n_prompt_tokens_processed_total += slot.n_prompt_tokens_processed;
         n_prompt_tokens_processed       += slot.n_prompt_tokens_processed;
         t_prompt_processing             += slot.t_prompt_processing;
         t_prompt_processing_total       += slot.t_prompt_processing;
     }
 
-    void on_prediction(const server_slot &slot) {
+    void on_prediction(const server_slot & slot) {
         n_tokens_predicted_total   += slot.n_decoded;
         n_tokens_predicted         += slot.n_decoded;
         t_tokens_generation        += slot.t_token_generation;
@@ -392,7 +396,7 @@ struct server_queue {
     // callback functions
     std::function<void(server_task       &)> callback_new_task;
     std::function<void(server_task_multi &)> callback_finish_multitask;
-    std::function<void(void)>                callback_run_slots;
+    std::function<void(void)>                callback_update_slots;
 
     // Add a new task to the end of the queue
     int post(server_task task) {
@@ -431,8 +435,8 @@ struct server_queue {
     }
 
     // Register the function to be called when all slots data is ready to be processed
-    void on_run_slots(std::function<void(void)> callback) {
-        callback_run_slots = std::move(callback);
+    void on_update_slots(std::function<void(void)> callback) {
+        callback_update_slots = std::move(callback);
     }
 
     // Call when the state of one slot is changed
@@ -457,7 +461,7 @@ struct server_queue {
      * - Wait until a new task arrives
      * - Process the task (i.e. maybe copy data into slot)
      * - Check if multitask is finished
-     * - Run all slots
+     * - Update all slots
      */
     void start_loop() {
         running = true;
@@ -495,9 +499,9 @@ struct server_queue {
             }
 
             // all tasks in the current loop is processed, slots data is now ready
-            LOG_VERBOSE("callback_run_slots", {});
+            LOG_VERBOSE("callback_update_slots", {});
 
-            callback_run_slots();
+            callback_update_slots();
 
             LOG_VERBOSE("wait for new task", {});
             {
@@ -690,10 +694,11 @@ struct server_context {
         return res > 0;
     }
 
-    void initialize() {
+    void init() {
         const int32_t n_ctx_slot = n_ctx / params.n_parallel;
 
         LOG_INFO("initializing slots", {{"n_slots", params.n_parallel}});
+
         for (int i = 0; i < params.n_parallel; i++) {
             server_slot slot;
 
@@ -735,6 +740,8 @@ struct server_context {
         default_generation_settings_for_props["seed"] = -1;
 
         batch = llama_batch_init(n_ctx, 0, params.n_parallel);
+
+        metrics.init();
     }
 
     std::vector<llama_token> tokenize(const json & json_prompt, bool add_bos) const {
@@ -798,9 +805,10 @@ struct server_context {
         return last_used;
     }
 
-    bool launch_slot_with_data(server_slot & slot, json data) const {
+    bool launch_slot_with_task(server_slot & slot, const server_task & task) {
         slot_params default_params;
         llama_sampling_params default_sparams;
+        auto & data = task.data;
 
         if (data.count("__oaicompat") != 0) {
             slot.oaicompat = true;
@@ -857,10 +865,15 @@ struct server_context {
         {
             const auto & prompt = data.find("prompt");
             if (prompt == data.end()) {
-                slot.prompt = "";
+                send_error(task, "Either \"prompt\" or \"messages\" must be provided", ERROR_TYPE_INVALID_REQUEST);
+                return false;
             } else {
                 slot.prompt = *prompt;
             }
+            if (slot.prompt.is_array() && slot.prompt.size() == 0) {
+                send_error(task, "\"prompt\" cannot be an empty array", ERROR_TYPE_INVALID_REQUEST);
+                return false;
+            }
         }
 
         // penalize user-provided tokens
@@ -919,6 +932,7 @@ struct server_context {
             if (logit_bias != data.end() && logit_bias->is_array()) {
                 const int n_vocab = llama_n_vocab(model);
                 for (const auto & el : *logit_bias) {
+                    // TODO: we may want to throw errors here, in case "el" is incorrect
                     if (el.is_array() && el.size() == 2) {
                         float bias;
                         if (el[1].is_number()) {
@@ -978,6 +992,11 @@ struct server_context {
                 llama_sampling_free(slot.ctx_sampling);
             }
             slot.ctx_sampling = llama_sampling_init(slot.sparams);
+            if (slot.ctx_sampling == nullptr) {
+                // for now, the only error that may happen here is invalid grammar
+                send_error(task, "Failed to parse grammar", ERROR_TYPE_INVALID_REQUEST);
+                return false;
+            }
             llama_set_rng_seed(ctx, slot.params.seed);
         }
 
@@ -1219,15 +1238,23 @@ struct server_context {
         };
     }
 
-    void send_error(const server_task & task, const std::string & error) {
-        LOG_TEE("task %i - error: %s\n", task.id, error.c_str());
+    void send_error(const server_task & task, const std::string & error, const enum error_type type = ERROR_TYPE_SERVER) {
+        send_error(task.id, task.id_multi, error, type);
+    }
+
+    void send_error(const server_slot & slot, const std::string & error, const enum error_type type = ERROR_TYPE_SERVER) {
+        send_error(slot.id_task, slot.id_multi, error, type);
+    }
+
+    void send_error(const int id_task, const int id_multi, const std::string & error, const enum error_type type = ERROR_TYPE_SERVER) {
+        LOG_TEE("task %i - error: %s\n", id_task, error.c_str());
 
         server_task_result res;
-        res.id       = task.id;
-        res.id_multi = task.id_multi;
+        res.id       = id_task;
+        res.id_multi = id_multi;
         res.stop     = false;
         res.error    = true;
-        res.data     = { { "content", error } };
+        res.data     = format_error_response(error, type);
 
         queue_results.send(res);
     }
@@ -1461,9 +1488,8 @@ struct server_context {
                     slot->infill    = task.infill;
                     slot->embedding = task.embedding;
 
-                    if (!launch_slot_with_data(*slot, task.data)) {
-                        // send error result
-                        send_error(task, "internal_error");
+                    if (!launch_slot_with_task(*slot, task)) {
+                        LOG_ERROR("error while launching slot", task.data);
                         break;
                     }
                 } break;
@@ -1580,7 +1606,7 @@ struct server_context {
         queue_results.send(result);
     }
 
-    bool update_slots() {
+    void update_slots() {
         if (system_need_update) {
             system_prompt_update();
         }
@@ -1623,7 +1649,7 @@ struct server_context {
                     kv_cache_clear();
                 }
 
-                return true;
+                return;
             }
         }
 
@@ -1968,8 +1994,7 @@ struct server_context {
 
         if (batch.n_tokens == 0) {
             LOG_VERBOSE("no tokens to decode", {});
-
-            return true;
+            return;
         }
 
         LOG_VERBOSE("decoding batch", {
@@ -2026,7 +2051,13 @@ struct server_context {
                 if (n_batch == 1 || ret < 0) {
                     // if you get here, it means the KV cache is full - try increasing it via the context size
                     LOG_TEE("%s : failed to decode the batch, n_batch = %d, ret = %d\n", __func__, n_batch, ret);
-                    return false;
+                    for (auto & slot : slots) {
+                        slot.state = SLOT_STATE_PROCESSING;
+                        slot.command = SLOT_COMMAND_NONE;
+                        slot.release();
+                        send_error(slot, "Input prompt is too big compared to KV size. Please try increasing KV size.");
+                    }
+                    break; // break loop of n_batch
                 }
 
                 LOG_TEE("%s : failed to find free space in the KV cache, retrying with smaller n_batch = %d\n", __func__, n_batch / 2);
@@ -2035,12 +2066,12 @@ struct server_context {
                 n_batch /= 2;
                 i -= n_batch;
 
-                continue;
+                continue; // continue loop of n_batch
             }
 
             for (auto & slot : slots) {
                 if (slot.state != SLOT_STATE_PROCESSING || slot.i_batch < (int) i || slot.i_batch >= (int) (i + n_tokens)) {
-                    continue;
+                    continue; // continue loop of slots
                 }
 
                 // prompt evaluated for embedding
@@ -2048,7 +2079,7 @@ struct server_context {
                     send_embedding(slot, batch_view);
                     slot.release();
                     slot.i_batch = -1;
-                    continue;
+                    continue; // continue loop of slots
                 }
 
                 completion_token_output result;
@@ -2090,9 +2121,7 @@ struct server_context {
             }
         }
 
-        LOG_VERBOSE("slots updated", {});
-
-        return true;
+        LOG_VERBOSE("run slots completed", {});
     }
 
     json model_meta() const {
@@ -2126,6 +2155,8 @@ static void server_print_usage(const char * argv0, const gpt_params & params, co
     printf("  --yarn-beta-slow N        YaRN: high correction dim or alpha (default: %.1f)\n", params.yarn_beta_slow);
     printf("  --yarn-beta-fast N        YaRN: low correction dim or beta (default: %.1f)\n", params.yarn_beta_fast);
     printf("  --pooling {none,mean,cls} pooling type for embeddings, use model default if unspecified\n");
+    printf("  -dt N, --defrag-thold N\n");
+    printf("                            KV cache defragmentation threshold (default: %.1f, < 0 - disabled)\n", params.defrag_thold);
     printf("  -b N, --batch-size N      batch size for prompt processing (default: %d)\n", params.n_batch);
     printf("  --memory-f32              use f32 instead of f16 for memory key+value (default: disabled)\n");
     printf("                            not recommended: doubles context memory required and no measurable increase in quality\n");
@@ -2190,7 +2221,8 @@ static void server_print_usage(const char * argv0, const gpt_params & params, co
     printf("  -gaw N, --grp-attn-w N    set the group attention width to extend context size through self-extend(default: 512), used together with group attention factor `--grp-attn-n`\n");
     printf("  --chat-template JINJA_TEMPLATE\n");
     printf("                            set custom jinja chat template (default: template taken from model's metadata)\n");
-    printf("                            Note: only commonly used templates are accepted, since we don't have jinja parser\n");
+    printf("                            only commonly used templates are accepted:\n");
+    printf("                            https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template\n");
     printf("\n");
 }
 
@@ -2347,6 +2379,12 @@ static void server_params_parse(int argc, char ** argv, server_params & sparams,
             else if (value == "mean") { params.pooling_type = LLAMA_POOLING_TYPE_MEAN; }
             else if (value == "cls")  { params.pooling_type = LLAMA_POOLING_TYPE_CLS; }
             else { invalid_param = true; break; }
+        } else if (arg == "--defrag-thold" || arg == "-dt") {
+            if (++i >= argc) {
+                invalid_param = true;
+                break;
+            }
+            params.defrag_thold = std::stof(argv[i]);
         } else if (arg == "--threads" || arg == "-t") {
             if (++i >= argc)
             {
@@ -2729,32 +2767,32 @@ int main(int argc, char ** argv) {
 
     svr->set_logger(log_server_request);
 
-    svr->set_exception_handler([](const httplib::Request &, httplib::Response & res, std::exception_ptr ep) {
-        const char fmt[] = "500 Internal Server Error\n%s";
+    auto res_error = [](httplib::Response & res, json error_data) {
+        json final_response {{"error", error_data}};
+        res.set_content(final_response.dump(), "application/json; charset=utf-8");
+        res.status = json_value(error_data, "code", 500);
+    };
 
-        char buf[BUFSIZ];
+    svr->set_exception_handler([&res_error](const httplib::Request &, httplib::Response & res, std::exception_ptr ep) {
+        std::string message;
         try {
             std::rethrow_exception(std::move(ep));
-        } catch (std::exception &e) {
-            snprintf(buf, sizeof(buf), fmt, e.what());
+        } catch (std::exception & e) {
+            message = e.what();
         } catch (...) {
-            snprintf(buf, sizeof(buf), fmt, "Unknown Exception");
+            message = "Unknown Exception";
         }
 
-        res.set_content(buf, "text/plain; charset=utf-8");
-        res.status = 500;
+        json formatted_error = format_error_response(message, ERROR_TYPE_SERVER);
+        LOG_VERBOSE("Got exception", formatted_error);
+        res_error(res, formatted_error);
     });
 
-    svr->set_error_handler([](const httplib::Request &, httplib::Response & res) {
-        if (res.status == 401) {
-            res.set_content("Unauthorized", "text/plain; charset=utf-8");
-        }
-        if (res.status == 400) {
-            res.set_content("Invalid request", "text/plain; charset=utf-8");
-        }
+    svr->set_error_handler([&res_error](const httplib::Request &, httplib::Response & res) {
         if (res.status == 404) {
-            res.set_content("File Not Found", "text/plain; charset=utf-8");
+            res_error(res, format_error_response("File Not Found", ERROR_TYPE_NOT_FOUND));
         }
+        // for other error codes, we skip processing here because it's already done by res_error()
     });
 
     // set timeouts and change hostname and port
@@ -2783,7 +2821,7 @@ int main(int argc, char ** argv) {
         state.store(SERVER_STATE_ERROR);
         return 1;
     } else {
-        ctx_server.initialize();
+        ctx_server.init();
         state.store(SERVER_STATE_READY);
     }
 
@@ -2791,18 +2829,35 @@ int main(int argc, char ** argv) {
 
     const auto model_meta = ctx_server.model_meta();
 
-    if (sparams.chat_template.empty()) { // custom chat template is not supplied
+    // if a custom chat template is not supplied, we will use the one that comes with the model (if any)
+    if (sparams.chat_template.empty()) {
         if (!ctx_server.validate_model_chat_template()) {
             LOG_ERROR("The chat template that comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses", {});
             sparams.chat_template = "chatml";
         }
     }
 
+    // print sample chat example to make it clear which template is used
+    {
+        json chat;
+        chat.push_back({{"role", "system"},    {"content", "You are a helpful assistant"}});
+        chat.push_back({{"role", "user"},      {"content", "Hello"}});
+        chat.push_back({{"role", "assistant"}, {"content", "Hi there"}});
+        chat.push_back({{"role", "user"},      {"content", "How are you?"}});
+
+        const std::string chat_example = format_chat(ctx_server.model, sparams.chat_template, chat);
+
+        LOG_INFO("chat template", {
+            {"chat_example", chat_example},
+            {"built_in", sparams.chat_template.empty()},
+        });
+    }
+
     //
     // Middlewares
     //
 
-    auto middleware_validate_api_key = [&sparams](const httplib::Request & req, httplib::Response & res) {
+    auto middleware_validate_api_key = [&sparams, &res_error](const httplib::Request & req, httplib::Response & res) {
         // TODO: should we apply API key to all endpoints, including "/health" and "/models"?
         static const std::set<std::string> protected_endpoints = {
             "/props",
@@ -2843,8 +2898,7 @@ int main(int argc, char ** argv) {
         // API key is invalid or not provided
         // TODO: make another middleware for CORS related logic
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
-        res.set_content("Unauthorized: Invalid API Key", "text/plain; charset=utf-8");
-        res.status = 401; // Unauthorized
+        res_error(res, format_error_response("Invalid API Key", ERROR_TYPE_AUTHENTICATION));
 
         LOG_WARNING("Unauthorized: Invalid API Key", {});
 
@@ -2907,21 +2961,18 @@ int main(int argc, char ** argv) {
                 }
             case SERVER_STATE_LOADING_MODEL:
                 {
-                    res.set_content(R"({"status": "loading model"})", "application/json");
-                    res.status = 503; // HTTP Service Unavailable
+                    res_error(res, format_error_response("Loading model", ERROR_TYPE_UNAVAILABLE));
                 } break;
             case SERVER_STATE_ERROR:
                 {
-                    res.set_content(R"({"status": "error", "error": "Model failed to load"})", "application/json");
-                    res.status = 500; // HTTP Internal Server Error
+                    res_error(res, format_error_response("Model failed to load", ERROR_TYPE_SERVER));
                 } break;
         }
     };
 
     const auto handle_slots = [&](const httplib::Request &, httplib::Response & res) {
         if (!sparams.slots_endpoint) {
-            res.status = 501;
-            res.set_content("This server does not support slots endpoint.", "text/plain; charset=utf-8");
+            res_error(res, format_error_response("This server does not support slots endpoint.", ERROR_TYPE_NOT_SUPPORTED));
             return;
         }
 
@@ -2945,8 +2996,7 @@ int main(int argc, char ** argv) {
 
     const auto handle_metrics = [&](const httplib::Request &, httplib::Response & res) {
         if (!sparams.metrics_endpoint) {
-            res.status = 501;
-            res.set_content("This server does not support metrics endpoint.", "text/plain; charset=utf-8");
+            res_error(res, format_error_response("This server does not support metrics endpoint.", ERROR_TYPE_NOT_SUPPORTED));
             return;
         }
 
@@ -3057,7 +3107,7 @@ int main(int argc, char ** argv) {
         res.set_content(data.dump(), "application/json; charset=utf-8");
     };
 
-    const auto handle_completions = [&ctx_server](const httplib::Request & req, httplib::Response & res) {
+    const auto handle_completions = [&ctx_server, &res_error](const httplib::Request & req, httplib::Response & res) {
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
 
         json data = json::parse(req.body);
@@ -3072,8 +3122,7 @@ int main(int argc, char ** argv) {
             if (!result.error && result.stop) {
                 res.set_content(result.data.dump(-1, ' ', false, json::error_handler_t::replace), "application/json; charset=utf-8");
             } else {
-                res.status = 500;
-                res.set_content(result.data["content"], "text/plain; charset=utf-8");
+                res_error(res, result.data);
             }
 
             ctx_server.queue_results.remove_waiting_task_id(id_task);
@@ -3153,7 +3202,7 @@ int main(int argc, char ** argv) {
         res.set_content(models.dump(), "application/json; charset=utf-8");
     };
 
-    const auto handle_chat_completions = [&ctx_server, &sparams](const httplib::Request & req, httplib::Response & res) {
+    const auto handle_chat_completions = [&ctx_server, &sparams, &res_error](const httplib::Request & req, httplib::Response & res) {
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
         json data = oaicompat_completion_params_parse(ctx_server.model, json::parse(req.body), sparams.chat_template);
 
@@ -3162,24 +3211,24 @@ int main(int argc, char ** argv) {
         ctx_server.queue_results.add_waiting_task_id(id_task);
         ctx_server.request_completion(id_task, -1, data, false, false);
 
+        const auto completion_id = gen_chatcmplid();
         if (!json_value(data, "stream", false)) {
             server_task_result result = ctx_server.queue_results.recv(id_task);
 
             if (!result.error && result.stop) {
-                json result_oai = format_final_response_oaicompat(data, result.data);
+                json result_oai = format_final_response_oaicompat(data, result.data, completion_id);
 
                 res.set_content(result_oai.dump(-1, ' ', false, json::error_handler_t::replace), "application/json; charset=utf-8");
             } else {
-                res.status = 500;
-                res.set_content(result.data["content"], "text/plain; charset=utf-8");
+                res_error(res, result.data);
             }
             ctx_server.queue_results.remove_waiting_task_id(id_task);
         } else {
-            const auto chunked_content_provider = [id_task, &ctx_server](size_t, httplib::DataSink & sink) {
+            const auto chunked_content_provider = [id_task, &ctx_server, completion_id](size_t, httplib::DataSink & sink) {
                 while (true) {
                     server_task_result result = ctx_server.queue_results.recv(id_task);
                     if (!result.error) {
-                        std::vector<json> result_array = format_partial_response_oaicompat(result.data);
+                        std::vector<json> result_array = format_partial_response_oaicompat(result.data, completion_id);
 
                         for (auto it = result_array.begin(); it != result_array.end(); ++it) {
                             if (!it->empty()) {
@@ -3225,7 +3274,7 @@ int main(int argc, char ** argv) {
         }
     };
 
-    const auto handle_infill = [&ctx_server](const httplib::Request & req, httplib::Response & res) {
+    const auto handle_infill = [&ctx_server, &res_error](const httplib::Request & req, httplib::Response & res) {
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
 
         json data = json::parse(req.body);
@@ -3240,8 +3289,7 @@ int main(int argc, char ** argv) {
             if (!result.error && result.stop) {
                 res.set_content(result.data.dump(-1, ' ', false, json::error_handler_t::replace), "application/json; charset=utf-8");
             } else {
-                res.status = 404;
-                res.set_content(result.data["content"], "text/plain; charset=utf-8");
+                res_error(res, result.data);
             }
 
             ctx_server.queue_results.remove_waiting_task_id(id_task);
@@ -3312,7 +3360,7 @@ int main(int argc, char ** argv) {
         return res.set_content(data.dump(), "application/json; charset=utf-8");
     };
 
-    const auto handle_embeddings = [&params, &ctx_server](const httplib::Request & req, httplib::Response & res) {
+    const auto handle_embeddings = [&params, &ctx_server, &res_error](const httplib::Request & req, httplib::Response & res) {
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
         if (!params.embedding) {
             res.status = 501;
@@ -3341,8 +3389,8 @@ int main(int argc, char ** argv) {
             std::string content = body["content"];
             prompts.push_back(content);
         } else {
-            // TODO @ngxson : should return an error here
-            prompts.push_back("");
+            res_error(res, format_error_response("\"input\" or \"content\" must be provided", ERROR_TYPE_INVALID_REQUEST));
+            return;
         }
 
         // process all prompts
@@ -3358,9 +3406,14 @@ int main(int argc, char ** argv) {
             // get the result
             server_task_result result = ctx_server.queue_results.recv(id_task);
             ctx_server.queue_results.remove_waiting_task_id(id_task);
-
-            // append to the responses
-            responses.push_back(result.data);
+            if (!result.error) {
+                // append to the responses
+                responses.push_back(result.data);
+            } else {
+                // error received, ignore everything else
+                res_error(res, result.data);
+                return;
+            }
         }
 
         // write JSON response
@@ -3454,7 +3507,7 @@ int main(int argc, char ** argv) {
         &server_context::process_single_task, &ctx_server, std::placeholders::_1));
     ctx_server.queue_tasks.on_finish_multitask(std::bind(
         &server_context::on_finish_multitask, &ctx_server, std::placeholders::_1));
-    ctx_server.queue_tasks.on_run_slots(std::bind(
+    ctx_server.queue_tasks.on_update_slots(std::bind(
         &server_context::update_slots, &ctx_server));
     ctx_server.queue_results.on_multitask_update(std::bind(
         &server_queue::update_multitask,

examples/server/tests/features/environment.py

@@ -1,9 +1,10 @@
+import errno
 import os
 import socket
 import subprocess
 import time
 from contextlib import closing
-from signal import SIGKILL
+import signal
 
 
 def before_scenario(context, scenario):
@@ -29,44 +30,71 @@ def after_scenario(context, scenario):
                     for line in f:
                         print(line)
         if not is_server_listening(context.server_fqdn, context.server_port):
-            print("\x1b[33;101mERROR: Server stopped listening\x1b[0m")
+            print("\x1b[33;101mERROR: Server stopped listening\x1b[0m\n")
 
     if not pid_exists(context.server_process.pid):
         assert False, f"Server not running pid={context.server_process.pid} ..."
 
-    print(f"stopping server pid={context.server_process.pid} ...")
-    context.server_process.kill()
+    server_graceful_shutdown(context)
+
     # Wait few for socket to free up
     time.sleep(0.05)
 
     attempts = 0
-    while is_server_listening(context.server_fqdn, context.server_port):
-        print(f"stopping server pid={context.server_process.pid} ...")
-        os.kill(context.server_process.pid, SIGKILL)
+    while pid_exists(context.server_process.pid) or is_server_listening(context.server_fqdn, context.server_port):
+        server_kill(context)
         time.sleep(0.1)
         attempts += 1
         if attempts > 5:
-            print(f"Server dangling exits, killing all {context.server_path} ...")
-            process = subprocess.run(['killall', '-9', context.server_path],
-                                     stderr=subprocess.PIPE,
-                                     universal_newlines=True)
-            print(process)
+            server_kill_hard(context)
+
+
+def server_graceful_shutdown(context):
+    print(f"shutting down server pid={context.server_process.pid} ...\n")
+    if os.name == 'nt':
+        os.kill(context.server_process.pid, signal.CTRL_C_EVENT)
+    else:
+        os.kill(context.server_process.pid, signal.SIGINT)
+
+
+def server_kill(context):
+    print(f"killing server pid={context.server_process.pid} ...\n")
+    context.server_process.kill()
+
+
+def server_kill_hard(context):
+    pid = context.server_process.pid
+    path = context.server_path
+
+    print(f"Server dangling exits, hard killing force {pid}={path}...\n")
+    if os.name == 'nt':
+        process = subprocess.check_output(['taskkill', '/F', '/pid', str(pid)]).decode()
+        print(process)
+    else:
+        os.kill(-pid, signal.SIGKILL)
 
 
 def is_server_listening(server_fqdn, server_port):
     with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as sock:
         result = sock.connect_ex((server_fqdn, server_port))
-        return result == 0
+        _is_server_listening = result == 0
+        if _is_server_listening:
+            print(f"server is listening on {server_fqdn}:{server_port}...\n")
+        return _is_server_listening
 
 
 def pid_exists(pid):
     """Check whether pid exists in the current process table."""
-    import errno
     if pid < 0:
         return False
-    try:
-        os.kill(pid, 0)
-    except OSError as e:
-        return e.errno == errno.EPERM
+    if os.name == 'nt':
+        output = subprocess.check_output(['TASKLIST', '/FI', f'pid eq {pid}']).decode()
+        print(output)
+        return "No tasks are running" not in output
     else:
-        return True
+        try:
+            os.kill(pid, 0)
+        except OSError as e:
+            return e.errno == errno.EPERM
+        else:
+            return True

examples/server/tests/features/server.feature

@@ -47,7 +47,7 @@ Feature: llama.cpp server
     Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
     """
     And   a completion request with no api error
-    Then  64 tokens are predicted matching fun|Annaks|popcorns
+    Then  64 tokens are predicted matching fun|Annaks|popcorns|pictry
     And   the completion is  truncated
     And   109 prompt tokens are processed
 

examples/server/tests/features/steps/steps.py

@@ -18,7 +18,7 @@ from huggingface_hub import hf_hub_download
 from prometheus_client import parser
 
 
-@step(u"a server listening on {server_fqdn}:{server_port}")
+@step("a server listening on {server_fqdn}:{server_port}")
 def step_server_config(context, server_fqdn, server_port):
     context.server_fqdn = server_fqdn
     context.server_port = int(server_port)
@@ -57,24 +57,24 @@ def step_server_config(context, server_fqdn, server_port):
     context.prompts = []
 
 
-@step(u'a model file {hf_file} from HF repo {hf_repo}')
+@step('a model file {hf_file} from HF repo {hf_repo}')
 def step_download_hf_model(context, hf_file, hf_repo):
     context.model_file = hf_hub_download(repo_id=hf_repo, filename=hf_file)
     if context.debug:
         print(f"model file: {context.model_file}\n")
 
 
-@step(u'a model alias {model_alias}')
+@step('a model alias {model_alias}')
 def step_model_alias(context, model_alias):
     context.model_alias = model_alias
 
 
-@step(u'{seed:d} as server seed')
+@step('{seed:d} as server seed')
 def step_seed(context, seed):
     context.server_seed = seed
 
 
-@step(u'{ngl:d} GPU offloaded layers')
+@step('{ngl:d} GPU offloaded layers')
 def step_n_gpu_layer(context, ngl):
     if 'N_GPU_LAYERS' in os.environ:
         new_ngl = int(os.environ['N_GPU_LAYERS'])
@@ -84,37 +84,37 @@ def step_n_gpu_layer(context, ngl):
     context.n_gpu_layer = ngl
 
 
-@step(u'{n_ctx:d} KV cache size')
+@step('{n_ctx:d} KV cache size')
 def step_n_ctx(context, n_ctx):
     context.n_ctx = n_ctx
 
 
-@step(u'{n_slots:d} slots')
+@step('{n_slots:d} slots')
 def step_n_slots(context, n_slots):
     context.n_slots = n_slots
 
 
-@step(u'{n_predict:d} server max tokens to predict')
+@step('{n_predict:d} server max tokens to predict')
 def step_server_n_predict(context, n_predict):
     context.n_server_predict = n_predict
 
 
-@step(u'continuous batching')
+@step('continuous batching')
 def step_server_continuous_batching(context):
     context.server_continuous_batching = True
 
 
-@step(u'embeddings extraction')
+@step('embeddings extraction')
 def step_server_embeddings(context):
     context.server_embeddings = True
 
 
-@step(u'prometheus compatible metrics exposed')
+@step('prometheus compatible metrics exposed')
 def step_server_metrics(context):
     context.server_metrics = True
 
 
-@step(u"the server is starting")
+@step("the server is starting")
 def step_start_server(context):
     start_server_background(context)
     attempts = 0
@@ -131,7 +131,7 @@ def step_start_server(context):
             time.sleep(0.1)
 
 
-@step(u"the server is {expecting_status}")
+@step("the server is {expecting_status}")
 @async_run_until_complete
 async def step_wait_for_the_server_to_be_started(context, expecting_status):
     match expecting_status:
@@ -160,7 +160,7 @@ async def step_wait_for_the_server_to_be_started(context, expecting_status):
             assert False, "unknown status"
 
 
-@step(u'all slots are {expected_slot_status_string}')
+@step('all slots are {expected_slot_status_string}')
 @async_run_until_complete
 async def step_all_slots_status(context, expected_slot_status_string):
     match expected_slot_status_string:
@@ -176,7 +176,7 @@ async def step_all_slots_status(context, expected_slot_status_string):
     await request_slots_status(context, expected_slots)
 
 
-@step(u'a completion request with {api_error} api error')
+@step('a completion request with {api_error} api error')
 @async_run_until_complete
 async def step_request_completion(context, api_error):
     expect_api_error = api_error == 'raised'
@@ -194,133 +194,133 @@ async def step_request_completion(context, api_error):
         assert completion == 401, f"completion must be an 401 status code: {completion}"
 
 
-@step(u'{predicted_n:d} tokens are predicted matching {re_content}')
+@step('{predicted_n:d} tokens are predicted matching {re_content}')
 def step_n_tokens_predicted_with_content(context, predicted_n, re_content):
     context.completion = context.tasks_result.pop()
     assert_n_tokens_predicted(context.completion, predicted_n, re_content)
 
 
-@step(u'{predicted_n:d} tokens are predicted')
+@step('{predicted_n:d} tokens are predicted')
 def step_n_tokens_predicted(context, predicted_n):
     context.completion = context.tasks_result.pop()
     assert_n_tokens_predicted(context.completion, predicted_n)
 
 
-@step(u'the completion is  truncated')
+@step('the completion is  truncated')
 def step_assert_completion_truncated(context):
     step_assert_completion_truncated(context, '')
 
 
-@step(u'the completion is {truncated} truncated')
+@step('the completion is {truncated} truncated')
 def step_assert_completion_truncated(context, truncated):
     truncated = truncated != "not"
     assert context.completion['truncated'] == truncated, f'{context.completion}'
 
 
-@step(u'{n_prompt:d} prompt tokens are processed')
+@step('{n_prompt:d} prompt tokens are processed')
 def step_impl(context, n_prompt):
     assert n_prompt < 0 or n_prompt == context.completion['timings']['prompt_n'], f"n_prompt={context.completion['timings']['prompt_n']}"
 
 
-@step(u'a user prompt {user_prompt}')
+@step('a user prompt {user_prompt}')
 def step_user_prompt(context, user_prompt):
     context.prompts.append(user_prompt)
     context.n_prompts = len(context.prompts)
 
 
-@step(u'a system prompt {system_prompt}')
+@step('a system prompt {system_prompt}')
 def step_system_prompt(context, system_prompt):
     context.system_prompt = system_prompt
 
 
-@step(u'a model {model}')
+@step('a model {model}')
 def step_model(context, model):
     context.model = model
 
 
-@step(u'{max_tokens:d} max tokens to predict')
+@step('{max_tokens:d} max tokens to predict')
 def step_max_tokens(context, max_tokens):
     context.n_predict = max_tokens
 
 
-@step(u'streaming is {enable_streaming}')
+@step('streaming is {enable_streaming}')
 def step_streaming(context, enable_streaming):
     context.enable_streaming = enable_streaming == 'enabled'
 
 
-@step(u'a user api key {user_api_key}')
+@step('a user api key {user_api_key}')
 def step_user_api_key(context, user_api_key):
     context.user_api_key = user_api_key
 
 
-@step(u'no user api key')
+@step('no user api key')
 def step_no_user_api_key(context):
     context.user_api_key = None
 
 
-@step(u'a user api key ')
+@step('a user api key ')
 def step_no_user_api_key_space(context):
     context.user_api_key = None
 
 
-@step(u'a server api key {server_api_key}')
+@step('a server api key {server_api_key}')
 def step_server_api_key(context, server_api_key):
     context.server_api_key = server_api_key
 
 
-@step(u'{n_junk:d} as number of junk')
+@step('{n_junk:d} as number of junk')
 def step_n_junk(context, n_junk):
     context.n_junk = n_junk
 
 
-@step(u'{n_batch:d} as batch size')
+@step('{n_batch:d} as batch size')
 def step_n_batch(context, n_batch):
     context.n_batch = n_batch
 
 
-@step(u'{seed:d} as seed')
+@step('{seed:d} as seed')
 def step_seed(context, seed):
     context.seed = seed
 
 
-@step(u'a prefix prompt')
+@step('a prefix prompt')
 def step_prompt_prefix(context):
-    context.prompt_prefix = context.text
+    context.prompt_prefix = context_text(context)
 
 
-@step(u'a junk suffix prompt')
+@step('a junk suffix prompt')
 def step_prompt_junk_suffix(context):
-    context.prompt_junk_suffix = context.text
+    context.prompt_junk_suffix = context_text(context)
 
 
-@step(u'a suffix prompt')
+@step('a suffix prompt')
 def step_prompt_suffix(context):
-    context.prompt_suffix = context.text
+    context.prompt_suffix = context_text(context)
 
 
-@step(u'{n_ga:d} group attention factor'
-      u' to extend context size through self-extend')
+@step('{n_ga:d} group attention factor'
+      ' to extend context size through self-extend')
 def step_impl(context, n_ga):
     context.n_ga = n_ga
 
 
-@step(u'{n_ga_w:d} group attention width to extend context size through self-extend')
+@step('{n_ga_w:d} group attention width to extend context size through self-extend')
 def step_impl(context, n_ga_w):
     context.n_ga_w = n_ga_w
 
 
-@step(u'a passkey prompt template')
+@step('a passkey prompt template')
 def step_prompt_passkey(context):
-    context.prompt_passkey = context.text
+    context.prompt_passkey = context_text(context)
 
 
-@step(u'{n_prompts:d} fixed prompts')
+@step('{n_prompts:d} fixed prompts')
 def step_fixed_prompts(context, n_prompts):
     context.prompts.extend([str(0)*(context.n_batch if context.n_batch is not None else 512) for i in range(n_prompts)])
     context.n_prompts = n_prompts
 
 
-@step(u'a "{passkey}" passkey challenge prompt with the passkey inserted every {i_pos:d} junk')
+@step('a "{passkey}" passkey challenge prompt with the passkey inserted every {i_pos:d} junk')
 def step_prompt_passkey(context, passkey, i_pos):
     prompt = ""
     for i in range(context.n_junk):
@@ -334,7 +334,7 @@ def step_prompt_passkey(context, passkey, i_pos):
     context.n_prompts = len(context.prompts)
 
 
-@step(u'an OAI compatible chat completions request with {api_error} api error')
+@step('an OAI compatible chat completions request with {api_error} api error')
 @async_run_until_complete
 async def step_oai_chat_completions(context, api_error):
     if context.debug:
@@ -369,19 +369,19 @@ async def step_oai_chat_completions(context, api_error):
         print(f"Completion response: {completion}")
 
 
-@step(u'a prompt')
+@step('a prompt')
 def step_a_prompt(context):
-    context.prompts.append(context.text)
+    context.prompts.append(context_text(context))
     context.n_prompts = len(context.prompts)
 
 
-@step(u'a prompt {prompt}')
+@step('a prompt {prompt}')
 def step_a_prompt_prompt(context, prompt):
     context.prompts.append(prompt)
     context.n_prompts = len(context.prompts)
 
 
-@step(u'concurrent completion requests')
+@step('concurrent completion requests')
 @async_run_until_complete()
 async def step_concurrent_completion_requests(context):
     await concurrent_requests(context,
@@ -397,7 +397,7 @@ async def step_concurrent_completion_requests(context):
                                                                            'user_api_key') else None)
 
 
-@step(u'concurrent OAI completions requests')
+@step('concurrent OAI completions requests')
 @async_run_until_complete
 async def step_oai_chat_completions(context):
     await concurrent_requests(context, oai_chat_completions,
@@ -417,7 +417,7 @@ async def step_oai_chat_completions(context):
                               if hasattr(context, 'user_api_key') else None)
 
 
-@step(u'concurrent OAI completions requests no v1')
+@step('concurrent OAI completions requests no v1')
 @async_run_until_complete
 async def step_oai_chat_completions(context):
     await concurrent_requests(context, oai_chat_completions,
@@ -440,13 +440,13 @@ async def step_oai_chat_completions(context):
                               if hasattr(context, 'user_api_key') else None)
 
 
-@step(u'all prompts are predicted')
+@step('all prompts are predicted')
 @async_run_until_complete
 async def step_all_prompts_are_predicted(context):
     await all_prompts_are_predicted(context)
 
 
-@step(u'all prompts are predicted with {n_expected_predicted:d} tokens')
+@step('all prompts are predicted with {n_expected_predicted:d} tokens')
 @async_run_until_complete
 async def step_all_prompts_are_predicted_with_n_tokens(context, n_expected_predicted):
     await all_prompts_are_predicted(context, n_expected_predicted)
@@ -460,14 +460,14 @@ async def all_prompts_are_predicted(context, expected_predicted_n=None):
     assert len(context.concurrent_tasks) == 0, f"{len(context.concurrent_tasks)} pending requests"
 
 
-@step(u'embeddings are computed for')
+@step('embeddings are computed for')
 @async_run_until_complete
 async def step_compute_embedding(context):
     context.n_prompts = 1
-    context.embeddings = await request_embedding(context.text, base_url=context.base_url)
+    context.embeddings = await request_embedding(context_text(context), base_url=context.base_url)
 
 
-@step(u'all embeddings are the same')
+@step('all embeddings are the same')
 @async_run_until_complete
 async def step_all_embeddings_are_the_same(context):
     n_embedding_requests = await gather_tasks_results(context)
@@ -491,7 +491,8 @@ async def step_all_embeddings_are_the_same(context):
                 print(f"{msg}\n")
             assert np.isclose(similarity, 1.0, rtol=1e-05, atol=1e-08, equal_nan=False), msg
 
-@step(u'embeddings are generated')
+
+@step('embeddings are generated')
 def step_assert_embeddings(context):
     assert context.n_prompts == len(context.embeddings), (f"unexpected response:\n"
                                                              f"context.n_prompts={context.n_prompts}\n"
@@ -500,17 +501,17 @@ def step_assert_embeddings(context):
         assert_embeddings(embedding)
 
 
-@step(u'an OAI compatible embeddings computation request for')
+@step('an OAI compatible embeddings computation request for')
 @async_run_until_complete
 async def step_oai_compute_embeddings(context):
     context.n_prompts = 1
-    context.embeddings = await request_oai_embeddings(context.text,
+    context.embeddings = await request_oai_embeddings(context_text(context),
                                                       base_url=context.base_url,
                                                       user_api_key=context.user_api_key,
                                                       model=context.model)
 
 
-@step(u'an OAI compatible embeddings computation request for multiple inputs')
+@step('an OAI compatible embeddings computation request for multiple inputs')
 @async_run_until_complete
 async def step_oai_compute_embeddings_multiple_inputs(context):
     context.embeddings = await request_oai_embeddings(context.prompts,
@@ -520,7 +521,7 @@ async def step_oai_compute_embeddings_multiple_inputs(context):
     context.prompts.clear()
 
 
-@step(u'concurrent embedding requests')
+@step('concurrent embedding requests')
 @async_run_until_complete()
 async def step_concurrent_embedding_requests(context):
     await concurrent_requests(context,
@@ -529,7 +530,7 @@ async def step_concurrent_embedding_requests(context):
                               base_url=context.base_url)
 
 
-@step(u'concurrent OAI embedding requests')
+@step('concurrent OAI embedding requests')
 @async_run_until_complete()
 async def step_concurrent_oai_embedding_requests(context):
     await concurrent_requests(context,
@@ -540,7 +541,7 @@ async def step_concurrent_oai_embedding_requests(context):
                               model=context.model)
 
 
-@step(u'all embeddings are generated')
+@step('all embeddings are generated')
 @async_run_until_complete()
 async def all_embeddings_are_generated(context):
     n_embedding_requests = await gather_tasks_results(context)
@@ -549,10 +550,10 @@ async def all_embeddings_are_generated(context):
         assert_embeddings(context.tasks_result.pop().pop())
 
 
-@step(u'tokenizing')
+@step('tokenizing')
 @async_run_until_complete
 async def step_tokenize(context):
-    context.tokenized_text = context.text
+    context.tokenized_text = context_text(context)
     async with aiohttp.ClientSession() as session:
         async with session.post(f'{context.base_url}/tokenize',
                                 json={
@@ -563,7 +564,7 @@ async def step_tokenize(context):
             context.tokens = tokenize_json['tokens']
 
 
-@step(u'tokens can be detokenize')
+@step('tokens can be detokenize')
 @async_run_until_complete
 async def step_detokenize(context):
     assert len(context.tokens) > 0
@@ -578,7 +579,7 @@ async def step_detokenize(context):
             assert context.tokenized_text == detokenize_json['content'].strip()
 
 
-@step(u'an OPTIONS request is sent from {origin}')
+@step('an OPTIONS request is sent from {origin}')
 @async_run_until_complete
 async def step_options_request(context, origin):
     async with aiohttp.ClientSession() as session:
@@ -589,12 +590,12 @@ async def step_options_request(context, origin):
             context.options_response = response
 
 
-@step(u'CORS header {cors_header} is set to {cors_header_value}')
+@step('CORS header {cors_header} is set to {cors_header_value}')
 def step_check_options_header_value(context, cors_header, cors_header_value):
     assert context.options_response.headers[cors_header] == cors_header_value
 
 
-@step(u'prometheus metrics are exposed')
+@step('prometheus metrics are exposed')
 @async_run_until_complete
 async def step_prometheus_metrics_exported(context):
     async with aiohttp.ClientSession() as session:
@@ -616,14 +617,14 @@ async def step_prometheus_metrics_exported(context):
             assert metric_exported, "No metrics exported"
 
 
-@step(u'metric {metric_name} is {metric_value:d}')
+@step('metric {metric_name} is {metric_value:d}')
 def step_assert_metric_value(context, metric_name, metric_value):
     if metric_name not in context.metrics:
         assert False, f"no metric {metric_name} in {context.metrics.keys()}"
     assert context.metrics[metric_name].samples[0].value == metric_value, f"metric: {context.metrics[metric_name]}"
 
 
-@step(u'available models')
+@step('available models')
 def step_available_models(context):
     # openai client always expects an api_key
     openai.api_key = context.user_api_key if context.user_api_key is not None else 'nope'
@@ -631,14 +632,14 @@ def step_available_models(context):
     context.models = openai.Model.list().data
 
 
-@step(u'{n_model:d} models are supported')
+@step('{n_model:d} models are supported')
 def step_supported_models(context, n_model):
     if context.debug:
         print("server models available:", context.models)
     assert len(context.models) == n_model
 
 
-@step(u'model {i_model:d} is {param} {preposition} {param_value}')
+@step('model {i_model:d} is {param} {preposition} {param_value}')
 def step_supported_models(context, i_model, param, preposition, param_value):
     assert i_model < len(context.models)
     model = context.models[i_model]
@@ -800,7 +801,7 @@ async def oai_chat_completions(user_prompt,
                 stream=enable_streaming,
                 seed=seed
             )
-        except openai.error.APIError as e:
+        except openai.error.AuthenticationError as e:
             if expect_api_error is not None and expect_api_error:
                 return 401
             else:
@@ -1007,12 +1008,22 @@ async def completions_seed(context):
         else context.server_seed if hasattr(context, 'server_seed') else None
 
 
+def context_text(context):
+    return context.text.replace('\r', '')
+
+
 def start_server_background(context):
-    context.server_path = '../../../build/bin/server'
+    if os.name == 'nt':
+        context.server_path = '../../../build/bin/Release/server.exe'
+    else:
+        context.server_path = '../../../build/bin/server'
     if 'LLAMA_SERVER_BIN_PATH' in os.environ:
         context.server_path = os.environ['LLAMA_SERVER_BIN_PATH']
+    server_listen_addr = context.server_fqdn
+    if os.name == 'nt':
+        server_listen_addr = '0.0.0.0'
     server_args = [
-        '--host', context.server_fqdn,
+        '--host', server_listen_addr,
         '--port', context.server_port,
         '--model', context.model_file
     ]
@@ -1045,7 +1056,16 @@ def start_server_background(context):
     if 'SERVER_LOG_FORMAT_JSON' not in os.environ:
         server_args.extend(['--log-format', "text"])
     print(f"starting server with: {context.server_path} {server_args}\n")
+    flags = 0
+    if 'nt' == os.name:
+        flags |= subprocess.DETACHED_PROCESS
+        flags |= subprocess.CREATE_NEW_PROCESS_GROUP
+        flags |= subprocess.CREATE_NO_WINDOW
+
+    pkwargs = {
+        'creationflags': flags,
+    }
     context.server_process = subprocess.Popen(
         [str(arg) for arg in [context.server_path, *server_args]],
-        close_fds=True)
-    print(f"server pid={context.server_process.pid}")
+        **pkwargs)
+    print(f"server pid={context.server_process.pid}, behave pid={os.getpid()}")

examples/server/utils.hpp

@@ -14,6 +14,17 @@
 
 using json = nlohmann::json;
 
+// https://community.openai.com/t/openai-chat-list-of-error-codes-and-types/357791/11
+enum error_type {
+    ERROR_TYPE_INVALID_REQUEST,
+    ERROR_TYPE_AUTHENTICATION,
+    ERROR_TYPE_SERVER,
+    ERROR_TYPE_NOT_FOUND,
+    ERROR_TYPE_PERMISSION,
+    ERROR_TYPE_UNAVAILABLE, // custom error
+    ERROR_TYPE_NOT_SUPPORTED, // custom error
+};
+
 extern bool server_verbose;
 extern bool server_log_json;
 
@@ -378,7 +389,7 @@ static json oaicompat_completion_params_parse(
     return llama_params;
 }
 
-static json format_final_response_oaicompat(const json & request, json result, bool streaming = false) {
+static json format_final_response_oaicompat(const json & request, json result, const std::string & completion_id, bool streaming = false) {
     bool stopped_word        = result.count("stopped_word") != 0;
     bool stopped_eos         = json_value(result, "stopped_eos", false);
     int num_tokens_predicted = json_value(result, "tokens_predicted", 0);
@@ -412,7 +423,7 @@ static json format_final_response_oaicompat(const json & request, json result, b
             {"prompt_tokens",     num_prompt_tokens},
             {"total_tokens",      num_tokens_predicted + num_prompt_tokens}
         }},
-        {"id", gen_chatcmplid()}
+        {"id", completion_id}
     };
 
     if (server_verbose) {
@@ -427,7 +438,7 @@ static json format_final_response_oaicompat(const json & request, json result, b
 }
 
 // return value is vector as there is one case where we might need to generate two responses
-static std::vector<json> format_partial_response_oaicompat(json result) {
+static std::vector<json> format_partial_response_oaicompat(json result, const std::string & completion_id) {
     if (!result.contains("model") || !result.contains("oaicompat_token_ctr")) {
         return std::vector<json>({result});
     }
@@ -471,7 +482,7 @@ static std::vector<json> format_partial_response_oaicompat(json result) {
                                             {"role", "assistant"}
                                         }}}})},
                             {"created", t},
-                            {"id", gen_chatcmplid()},
+                            {"id", completion_id},
                             {"model", modelname},
                             {"object", "chat.completion.chunk"}};
 
@@ -482,7 +493,7 @@ static std::vector<json> format_partial_response_oaicompat(json result) {
                                                             {"content", content}}}
                                                             }})},
                             {"created", t},
-                            {"id", gen_chatcmplid()},
+                            {"id", completion_id},
                             {"model", modelname},
                             {"object", "chat.completion.chunk"}};
 
@@ -509,7 +520,7 @@ static std::vector<json> format_partial_response_oaicompat(json result) {
     json ret = json {
         {"choices", choices},
         {"created", t},
-        {"id",      gen_chatcmplid()},
+        {"id",      completion_id},
         {"model",   modelname},
         {"object",  "chat.completion.chunk"}
     };
@@ -542,3 +553,43 @@ static json format_detokenized_response(const std::string & content) {
         {"content", content}
     };
 }
+
+static json format_error_response(const std::string & message, const enum error_type type) {
+    std::string type_str;
+    int code = 500;
+    switch (type) {
+        case ERROR_TYPE_INVALID_REQUEST:
+            type_str = "invalid_request_error";
+            code = 400;
+            break;
+        case ERROR_TYPE_AUTHENTICATION:
+            type_str = "authentication_error";
+            code = 401;
+            break;
+        case ERROR_TYPE_NOT_FOUND:
+            type_str = "not_found_error";
+            code = 404;
+            break;
+        case ERROR_TYPE_SERVER:
+            type_str = "server_error";
+            code = 500;
+            break;
+        case ERROR_TYPE_PERMISSION:
+            type_str = "permission_error";
+            code = 403;
+            break;
+        case ERROR_TYPE_NOT_SUPPORTED:
+            type_str = "not_supported_error";
+            code = 501;
+            break;
+        case ERROR_TYPE_UNAVAILABLE:
+            type_str = "unavailable_error";
+            code = 503;
+            break;
+    }
+    return json {
+        {"code", code},
+        {"message", message},
+        {"type", type_str},
+    };
+}

flake.lock

@@ -20,11 +20,11 @@
     },
     "nixpkgs": {
       "locked": {
-        "lastModified": 1709237383,
-        "narHash": "sha256-cy6ArO4k5qTx+l5o+0mL9f5fa86tYUX3ozE1S+Txlds=",
+        "lastModified": 1709703039,
+        "narHash": "sha256-6hqgQ8OK6gsMu1VtcGKBxKQInRLHtzulDo9Z5jxHEFY=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "1536926ef5621b09bba54035ae2bb6d806d72ac8",
+        "rev": "9df3e30ce24fd28c7b3e2de0d986769db5d6225d",
         "type": "github"
       },
       "original": {

ggml-common.h

@@ -17,7 +17,7 @@
 #elif defined(GGML_COMMON_IMPL_CUDA)
 #include <cstdint>
 
-#define GGML_TABLE_BEGIN(type, name, size) static const __device__ __constant__ type name[size] = {
+#define GGML_TABLE_BEGIN(type, name, size) static const __device__ type name[size] = {
 #define GGML_TABLE_END() };
 
 #define GGML_COMMON_IMPL
@@ -644,136 +644,781 @@ GGML_TABLE_BEGIN(uint32_t, iq3s_grid, 512)
     0x0f090307, 0x0f090501, 0x0f090b01, 0x0f0b0505, 0x0f0b0905, 0x0f0d0105, 0x0f0d0703, 0x0f0f0101,
 GGML_TABLE_END()
 
-#define NGRID_IQ2XXS 512
-GGML_TABLE_BEGIN(uint64_t, iq1s_grid, NGRID_IQ2XXS)
-    0xffffffffffff0101, 0xffffffffff01ff00, 0xffffffffff010100, 0xffffffff00000000,
-    0xffffffff01ff00ff, 0xffffffff01ff0001, 0xffffffff0101ffff, 0xffffffff0101ff01,
-    0xffffff00ff000000, 0xffffff000000ff00, 0xffffff00000000ff, 0xffffff0000000100,
-    0xffffff0000010000, 0xffffff0001000000, 0xffffff01ffff00ff, 0xffffff01ff01ff00,
-    0xffffff01ff010100, 0xffffff0100000001, 0xffffff0101ffff00, 0xffffff0101ff0101,
-    0xffffff0101010100, 0xffff00ffff00ff01, 0xffff00ffff0000ff, 0xffff00ff00ff0100,
-    0xffff00ff0100ff00, 0xffff00ff010001ff, 0xffff0000ff0101ff, 0xffff000000ffff00,
-    0xffff000000000000, 0xffff00000001ff01, 0xffff000001000101, 0xffff0000010100ff,
-    0xffff0001ffff0100, 0xffff00010000ff00, 0xffff000100010101, 0xffff000101000000,
-    0xffff01ffffff0000, 0xffff01ffff01ffff, 0xffff01ffff010100, 0xffff01ff00000000,
-    0xffff01ff01ffffff, 0xffff01ff01ff0001, 0xffff01ff0101ffff, 0xffff01ff01010001,
-    0xffff0100ffffff01, 0xffff01000000ffff, 0xffff010000000100, 0xffff010001ff01ff,
-    0xffff010001000000, 0xffff0101ff000000, 0xffff0101000101ff, 0xffff010101ffff01,
-    0xffff01010101ff00, 0xff00ffffff000000, 0xff00ffff00ffff00, 0xff00ffff00000001,
-    0xff00ffff000001ff, 0xff00ffff01010000, 0xff00ff00ffff0000, 0xff00ff00ff00ff00,
-    0xff00ff00ff0000ff, 0xff00ff00ff000100, 0xff00ff00ff010001, 0xff00ff0000ff0001,
-    0xff00ff000000ffff, 0xff00ff0000000000, 0xff00ff000001ff00, 0xff00ff0000010100,
-    0xff00ff0001ff0000, 0xff00ff000100ff00, 0xff00ff0001000100, 0xff00ff01ff000000,
-    0xff00ff0100ff0000, 0xff00ff01000001ff, 0xff00ff0101010001, 0xff0000ff00000000,
-    0xff0000ff0001ff00, 0xff0000ff00010100, 0xff000000ffff0101, 0xff000000ff000000,
-    0xff000000ff01ff00, 0xff00000000ff0000, 0xff0000000000ff00, 0xff000000000000ff,
-    0xff00000000000000, 0xff00000000000001, 0xff00000000000100, 0xff0000000001ffff,
-    0xff00000000010000, 0xff00000001000000, 0xff00000001010100, 0xff000001ff00ff01,
-    0xff000001ff0100ff, 0xff00000100000000, 0xff0000010001ff00, 0xff00000101ff0100,
-    0xff0000010100ff00, 0xff0001ff00ff00ff, 0xff0001ff00000101, 0xff0001ff000100ff,
-    0xff0001ff01000000, 0xff000100ff0001ff, 0xff0001000000ff01, 0xff00010000000000,
-    0xff00010000010001, 0xff00010000010100, 0xff00010001ffff00, 0xff00010001ff0101,
-    0xff00010001010000, 0xff000101ffffffff, 0xff000101ff000101, 0xff00010101ff00ff,
-    0xff00010101000001, 0xff000101010100ff, 0xff01ffffff000101, 0xff01ffffff01ffff,
-    0xff01ffffff01ff01, 0xff01ffffff0101ff, 0xff01ffff00000000, 0xff01ffff01ff0001,
-    0xff01ffff0101ff01, 0xff01ff00ff000000, 0xff01ff0000ff0100, 0xff01ff000000ff01,
-    0xff01ff0000010000, 0xff01ff00010000ff, 0xff01ff01ff01ff00, 0xff01ff0100000101,
-    0xff0100ffffff0000, 0xff0100ffff010000, 0xff0100ff01ff00ff, 0xff0100ff01000100,
-    0xff0100ff010100ff, 0xff010000ffffff01, 0xff01000000000000, 0xff0100000101ff00,
-    0xff010001ffff00ff, 0xff010001ff000100, 0xff01000100ffff00, 0xff01000100010001,
-    0xff01000101ff0001, 0xff010001010001ff, 0xff0101ffffffffff, 0xff0101ffff01ffff,
-    0xff0101ffff010101, 0xff0101ff0000ff00, 0xff0101ff01010001, 0xff010100ff000000,
-    0xff010100ff01ff01, 0xff01010000ff0001, 0xff01010000000100, 0xff01010001000000,
-    0xff0101010100ffff, 0x00ffffff0000ff01, 0x00ffffff000000ff, 0x00ffffff00000100,
-    0x00ffffff00010000, 0x00ffff00ffff0001, 0x00ffff00ff0000ff, 0x00ffff00ff000100,
-    0x00ffff0000000000, 0x00ffff0001000100, 0x00ffff0001010001, 0x00ffff01ff00ff01,
-    0x00ffff0100ff0100, 0x00ffff010000ff00, 0x00ffff01000100ff, 0x00ffff0101ff00ff,
-    0x00ffff010101ff00, 0x00ff00ffffffffff, 0x00ff00ffffff01ff, 0x00ff00ffff000101,
-    0x00ff00ff00000000, 0x00ff00ff000101ff, 0x00ff00ff01010101, 0x00ff0000ff000000,
-    0x00ff0000ff01ffff, 0x00ff000000ff0000, 0x00ff00000000ff00, 0x00ff0000000000ff,
-    0x00ff000000000000, 0x00ff000000000001, 0x00ff000000000100, 0x00ff000000010000,
-    0x00ff000001ffff01, 0x00ff000001000000, 0x00ff0001ff000101, 0x00ff000100ffffff,
-    0x00ff000100000000, 0x00ff0001010001ff, 0x00ff01ffff000000, 0x00ff01ff0001ff00,
-    0x00ff01ff01ff0100, 0x00ff0100ff01ff01, 0x00ff010000ff00ff, 0x00ff010000ff0101,
-    0x00ff010000000000, 0x00ff010000010101, 0x00ff01000100ff00, 0x00ff010001010000,
-    0x00ff0101ffffff00, 0x00ff01010000ff01, 0x00ff010100000100, 0x00ff010101ff0000,
-    0x0000ffffffff0100, 0x0000ffffff00ff00, 0x0000ffffff0000ff, 0x0000ffffff010000,
-    0x0000ffff00000000, 0x0000ffff00010101, 0x0000ffff01ffff01, 0x0000ffff01000100,
-    0x0000ff00ff000000, 0x0000ff00ff01ff00, 0x0000ff00ff0101ff, 0x0000ff0000ff0000,
-    0x0000ff000000ff00, 0x0000ff00000000ff, 0x0000ff0000000000, 0x0000ff0000000001,
-    0x0000ff0000000100, 0x0000ff0000010000, 0x0000ff0001ffffff, 0x0000ff0001ff01ff,
-    0x0000ff0001000000, 0x0000ff000101ffff, 0x0000ff01ffff0101, 0x0000ff01ff010000,
-    0x0000ff0100000000, 0x0000ff0101000101, 0x000000ffffff0001, 0x000000ffff000000,
-    0x000000ff00ff0000, 0x000000ff0000ff00, 0x000000ff000000ff, 0x000000ff00000000,
-    0x000000ff00000001, 0x000000ff00000100, 0x000000ff00010000, 0x000000ff01000000,
-    0x000000ff0101ff00, 0x00000000ffff0000, 0x00000000ff00ff00, 0x00000000ff0000ff,
-    0x00000000ff000000, 0x00000000ff000001, 0x00000000ff000100, 0x00000000ff010000,
-    0x0000000000ffff00, 0x0000000000ff00ff, 0x0000000000ff0000, 0x0000000000ff0001,
+#define NGRID_IQ1S 2048
+#if defined(GGML_COMMON_IMPL_C)
+GGML_TABLE_BEGIN(uint64_t, iq1s_grid, NGRID_IQ1S)
+    0xffffffffffffffff, 0xffffffffffffff01, 0xffffffffffff0000, 0xffffffffffff01ff,
+    0xffffffffffff0101, 0xffffffffff00ff00, 0xffffffffff000000, 0xffffffffff01ffff,
+    0xffffffffff01ff01, 0xffffffffff0101ff, 0xffffffffff010101, 0xffffffff00ff0000,
+    0xffffffff0000ff00, 0xffffffff000000ff, 0xffffffff00000001, 0xffffffff00010000,
+    0xffffffff01ffffff, 0xffffffff01ffff01, 0xffffffff01ff01ff, 0xffffffff01ff0101,
+    0xffffffff01000000, 0xffffffff0101ffff, 0xffffffff0101ff01, 0xffffffff010101ff,
+    0xffffffff01010101, 0xffffff00ffff00ff, 0xffffff00ffff0000, 0xffffff00ff00ff00,
+    0xffffff00ff0000ff, 0xffffff00ff000001, 0xffffff00ff000100, 0xffffff00ff000101,
+    0xffffff00ff010000, 0xffffff0000ffff00, 0xffffff0000ff0001, 0xffffff0000ff0100,
+    0xffffff000000ff01, 0xffffff0000000000, 0xffffff0000000101, 0xffffff000001ff00,
+    0xffffff00000100ff, 0xffffff0000010001, 0xffffff00000101ff, 0xffffff0001ff0000,
+    0xffffff000100ff00, 0xffffff00010000ff, 0xffffff0001000001, 0xffffff0001010000,
+    0xffffff01ffffffff, 0xffffff01ffffff01, 0xffffff01ffff01ff, 0xffffff01ffff0101,
+    0xffffff01ff000000, 0xffffff01ff01ffff, 0xffffff01ff01ff01, 0xffffff01ff0101ff,
+    0xffffff01ff010101, 0xffffff0100ff0000, 0xffffff010000ff00, 0xffffff0100000100,
+    0xffffff01000100ff, 0xffffff0100010100, 0xffffff0101ffffff, 0xffffff0101ffff01,
+    0xffffff0101ff01ff, 0xffffff0101ff0101, 0xffffff010100ff00, 0xffffff0101000000,
+    0xffffff0101000100, 0xffffff010101ffff, 0xffffff010101ff01, 0xffffff01010101ff,
+    0xffffff0101010101, 0xffff00ffff00ff00, 0xffff00ffff0000ff, 0xffff00ffff000001,
+    0xffff00ffff010000, 0xffff00ff00ffff00, 0xffff00ff00ff0100, 0xffff00ff00000000,
+    0xffff00ff00000101, 0xffff00ff000100ff, 0xffff00ff00010000, 0xffff00ff0100ff00,
+    0xffff00ff01000100, 0xffff00ff01010000, 0xffff0000ffffff00, 0xffff0000ffff00ff,
+    0xffff0000ffff0000, 0xffff0000ffff0001, 0xffff0000ff000000, 0xffff0000ff0001ff,
+    0xffff0000ff000101, 0xffff0000ff010100, 0xffff000000ffffff, 0xffff000000ff0000,
+    0xffff000000ff0101, 0xffff00000000ffff, 0xffff00000000ff00, 0xffff0000000000ff,
+    0xffff000000000000, 0xffff000000000001, 0xffff000000000100, 0xffff00000001ffff,
+    0xffff00000001ff01, 0xffff000000010000, 0xffff0000000101ff, 0xffff000000010101,
+    0xffff000001ffff00, 0xffff00000100ff00, 0xffff000001000000, 0xffff0000010001ff,
+    0xffff000001000101, 0xffff00000101ff00, 0xffff0000010100ff, 0xffff000001010000,
+    0xffff000001010001, 0xffff000001010100, 0xffff0001ff0000ff, 0xffff0001ff000100,
+    0xffff000100ffff00, 0xffff000100ff00ff, 0xffff00010000ffff, 0xffff00010000ff01,
+    0xffff000100000000, 0xffff0001000001ff, 0xffff00010001ffff, 0xffff00010001ff00,
+    0xffff000100010001, 0xffff000100010100, 0xffff000101ff0000, 0xffff00010100ff00,
+    0xffff0001010000ff, 0xffff000101000100, 0xffff01ffffffffff, 0xffff01ffffffff01,
+    0xffff01ffffff01ff, 0xffff01ffffff0101, 0xffff01ffff000000, 0xffff01ffff01ffff,
+    0xffff01ffff01ff01, 0xffff01ffff0101ff, 0xffff01ffff010101, 0xffff01ff00ff0000,
+    0xffff01ff0000ff00, 0xffff01ff00000001, 0xffff01ff00010000, 0xffff01ff01ffffff,
+    0xffff01ff01ffff01, 0xffff01ff01ff01ff, 0xffff01ff01ff0101, 0xffff01ff01000000,
+    0xffff01ff0101ffff, 0xffff01ff0101ff01, 0xffff01ff010101ff, 0xffff01ff01010101,
+    0xffff0100ffff0000, 0xffff0100ff00ff00, 0xffff0100ff0000ff, 0xffff0100ff000100,
+    0xffff0100ff0100ff, 0xffff0100ff010000, 0xffff010000ffff00, 0xffff01000000ffff,
+    0xffff01000000ff00, 0xffff010000000000, 0xffff01000001ff00, 0xffff0100000100ff,
+    0xffff010000010100, 0xffff01000100ff00, 0xffff0100010000ff, 0xffff010001000001,
+    0xffff010001000100, 0xffff010001010000, 0xffff0101ffffffff, 0xffff0101ffffff01,
+    0xffff0101ffff01ff, 0xffff0101ffff0101, 0xffff0101ff000000, 0xffff0101ff01ffff,
+    0xffff0101ff01ff01, 0xffff0101ff0101ff, 0xffff0101ff010101, 0xffff010100ff0000,
+    0xffff01010000ff00, 0xffff010100000100, 0xffff01010001ff00, 0xffff010100010000,
+    0xffff010101ffffff, 0xffff010101ffff01, 0xffff010101ff0000, 0xffff010101ff01ff,
+    0xffff010101ff0101, 0xffff010101000000, 0xffff01010101ffff, 0xffff01010101ff01,
+    0xffff0101010101ff, 0xffff010101010101, 0xff00ffffff00ffff, 0xff00ffffff00ff00,
+    0xff00ffffff0000ff, 0xff00ffffff000100, 0xff00ffffff0100ff, 0xff00ffffff010000,
+    0xff00ffff00ffff00, 0xff00ffff00ff00ff, 0xff00ffff0000ffff, 0xff00ffff00000000,
+    0xff00ffff000001ff, 0xff00ffff0001ff00, 0xff00ffff000100ff, 0xff00ffff00010000,
+    0xff00ffff00010100, 0xff00ffff0100ff00, 0xff00ffff010000ff, 0xff00ffff01000001,
+    0xff00ffff0101ff00, 0xff00ffff01010000, 0xff00ff00ffffff00, 0xff00ff00ffff00ff,
+    0xff00ff00ffff0001, 0xff00ff00ffff0100, 0xff00ff00ff00ffff, 0xff00ff00ff00ff01,
+    0xff00ff00ff000000, 0xff00ff00ff0001ff, 0xff00ff00ff01ff00, 0xff00ff00ff0100ff,
+    0xff00ff00ff010100, 0xff00ff0000ff0000, 0xff00ff0000ff0101, 0xff00ff000000ffff,
+    0xff00ff000000ff00, 0xff00ff000000ff01, 0xff00ff00000000ff, 0xff00ff0000000000,
+    0xff00ff0000000001, 0xff00ff0000000100, 0xff00ff000001ffff, 0xff00ff0000010000,
+    0xff00ff0001ff00ff, 0xff00ff000100ff01, 0xff00ff0001000000, 0xff00ff000101ff00,
+    0xff00ff00010100ff, 0xff00ff01ff00ff00, 0xff00ff01ff0000ff, 0xff00ff01ff000001,
+    0xff00ff01ff010000, 0xff00ff0100ffffff, 0xff00ff0100ff0001, 0xff00ff0100ff0100,
+    0xff00ff010000ff01, 0xff00ff0100000000, 0xff00ff01000001ff, 0xff00ff0100000101,
+    0xff00ff01000100ff, 0xff00ff0100010001, 0xff00ff0101ff0000, 0xff00ff010100ff00,
+    0xff00ff01010000ff, 0xff00ff0101000001, 0xff00ff0101010000, 0xff0000ffffffff00,
+    0xff0000ffffff0001, 0xff0000ffffff0100, 0xff0000ffff0000ff, 0xff0000ffff000000,
+    0xff0000ffff0001ff, 0xff0000ffff000100, 0xff0000ffff01ff00, 0xff0000ffff010001,
+    0xff0000ff00ffff00, 0xff0000ff00ff0000, 0xff0000ff00ff0001, 0xff0000ff00ff01ff,
+    0xff0000ff00ff0101, 0xff0000ff0000ff00, 0xff0000ff000000ff, 0xff0000ff00000000,
+    0xff0000ff00000001, 0xff0000ff00000100, 0xff0000ff0001ff01, 0xff0000ff00010000,
+    0xff0000ff000101ff, 0xff0000ff01ff00ff, 0xff0000ff01ff0100, 0xff0000ff0100ffff,
+    0xff0000ff010000ff, 0xff0000ff01000000, 0xff0000ff010001ff, 0xff0000ff01000100,
+    0xff0000ff01000101, 0xff0000ff0101ff00, 0xff0000ff010100ff, 0xff0000ff01010000,
+    0xff0000ff01010100, 0xff000000ffffff01, 0xff000000ffff0000, 0xff000000ffff0101,
+    0xff000000ff00ff00, 0xff000000ff0000ff, 0xff000000ff000000, 0xff000000ff000001,
+    0xff000000ff000100, 0xff000000ff01ffff, 0xff000000ff01ff01, 0xff000000ff010000,
+    0xff000000ff0101ff, 0xff000000ff010101, 0xff00000000ffff00, 0xff00000000ff00ff,
+    0xff00000000ff0000, 0xff00000000ff0001, 0xff0000000000ff00, 0xff0000000000ff01,
+    0xff000000000000ff, 0xff00000000000000, 0xff00000000000001, 0xff00000000000100,
+    0xff00000000000101, 0xff0000000001ff00, 0xff000000000100ff, 0xff00000000010000,
+    0xff00000000010001, 0xff00000000010100, 0xff00000001ffffff, 0xff00000001ffff01,
+    0xff00000001ff00ff, 0xff00000001ff0000, 0xff00000001ff01ff, 0xff00000001ff0101,
+    0xff0000000100ffff, 0xff0000000100ff00, 0xff000000010000ff, 0xff00000001000000,
+    0xff00000001000001, 0xff00000001000100, 0xff00000001000101, 0xff0000000101ffff,
+    0xff0000000101ff01, 0xff00000001010000, 0xff000001ffffff00, 0xff000001ffff00ff,
+    0xff000001ffff0000, 0xff000001ffff0001, 0xff000001ff000000, 0xff000001ff000001,
+    0xff000001ff0001ff, 0xff000001ff000101, 0xff000001ff01ff00, 0xff000001ff010001,
+    0xff00000100ffffff, 0xff00000100ffff01, 0xff00000100ff00ff, 0xff00000100ff0000,
+    0xff00000100ff01ff, 0xff00000100ff0101, 0xff0000010000ff00, 0xff00000100000000,
+    0xff00000100000001, 0xff000001000001ff, 0xff00000100000100, 0xff0000010001ff00,
+    0xff000001000100ff, 0xff00000100010000, 0xff000001000101ff, 0xff00000100010100,
+    0xff00000100010101, 0xff00000101ff0001, 0xff00000101ff0101, 0xff0000010100ff01,
+    0xff00000101000000, 0xff000001010100ff, 0xff00000101010100, 0xff0001ffff00ff00,
+    0xff0001ffff000001, 0xff0001ffff010000, 0xff0001ff00ffff00, 0xff0001ff00ff00ff,
+    0xff0001ff00ff0001, 0xff0001ff00ff0100, 0xff0001ff0000ffff, 0xff0001ff00000000,
+    0xff0001ff000001ff, 0xff0001ff00000101, 0xff0001ff0001ffff, 0xff0001ff0001ff00,
+    0xff0001ff000100ff, 0xff0001ff00010001, 0xff0001ff00010100, 0xff0001ff01ff0000,
+    0xff0001ff0100ff00, 0xff0001ff010000ff, 0xff0001ff01010000, 0xff000100ff00ffff,
+    0xff000100ff00ff01, 0xff000100ff000000, 0xff000100ff000101, 0xff000100ff01ff00,
+    0xff000100ff010000, 0xff00010000ffff01, 0xff00010000ff00ff, 0xff00010000ff0000,
+    0xff00010000ff01ff, 0xff0001000000ff00, 0xff000100000000ff, 0xff00010000000000,
+    0xff00010000000001, 0xff00010000000100, 0xff00010000000101, 0xff0001000001ffff,
+    0xff00010000010000, 0xff00010000010101, 0xff00010001ff0100, 0xff0001000100ff00,
+    0xff0001000100ff01, 0xff00010001000000, 0xff000100010001ff, 0xff0001000101ff00,
+    0xff00010001010001, 0xff00010001010100, 0xff000101ffff0100, 0xff000101ff000001,
+    0xff000101ff0100ff, 0xff000101ff010001, 0xff00010100ff00ff, 0xff00010100ff0001,
+    0xff00010100ff0100, 0xff0001010000ffff, 0xff0001010000ff01, 0xff00010100000000,
+    0xff000101000001ff, 0xff0001010001ff00, 0xff00010100010001, 0xff00010100010100,
+    0xff00010101ff0000, 0xff0001010100ff00, 0xff00010101000001, 0xff00010101000101,
+    0xff01ffffffffffff, 0xff01ffffffffff01, 0xff01ffffffff01ff, 0xff01ffffffff0101,
+    0xff01ffffff000000, 0xff01ffffff01ffff, 0xff01ffffff01ff01, 0xff01ffffff010000,
+    0xff01ffffff0101ff, 0xff01ffffff010101, 0xff01ffff00ff0000, 0xff01ffff0000ff00,
+    0xff01ffff00000100, 0xff01ffff0001ff00, 0xff01ffff00010000, 0xff01ffff01ffffff,
+    0xff01ffff01ffff01, 0xff01ffff01ff01ff, 0xff01ffff01ff0101, 0xff01ffff01000000,
+    0xff01ffff0101ffff, 0xff01ffff0101ff01, 0xff01ffff01010000, 0xff01ffff010101ff,
+    0xff01ffff01010101, 0xff01ff00ffff0000, 0xff01ff00ff00ff00, 0xff01ff00ff0000ff,
+    0xff01ff00ff000100, 0xff01ff00ff010000, 0xff01ff0000ffff01, 0xff01ff0000ff00ff,
+    0xff01ff0000ff0100, 0xff01ff0000000000, 0xff01ff00000001ff, 0xff01ff0000000101,
+    0xff01ff000001ff00, 0xff01ff00000100ff, 0xff01ff0000010000, 0xff01ff0000010001,
+    0xff01ff0001ff0000, 0xff01ff000100ffff, 0xff01ff0001000001, 0xff01ff0001000100,
+    0xff01ff0001010000, 0xff01ff01ffffff00, 0xff01ff01ffff01ff, 0xff01ff01ffff0101,
+    0xff01ff01ff00ff00, 0xff01ff01ff000000, 0xff01ff01ff01ffff, 0xff01ff01ff01ff01,
+    0xff01ff01ff0101ff, 0xff01ff01ff010101, 0xff01ff0100ff0000, 0xff01ff010000ff00,
+    0xff01ff0100000001, 0xff01ff0100000100, 0xff01ff0100010000, 0xff01ff0101ffff00,
+    0xff01ff0101ff01ff, 0xff01ff0101ff0101, 0xff01ff010100ff00, 0xff01ff0101000000,
+    0xff01ff010101ffff, 0xff01ff010101ff01, 0xff01ff01010101ff, 0xff01ff0101010101,
+    0xff0100ffffff0000, 0xff0100ffff0000ff, 0xff0100ffff000001, 0xff0100ffff000100,
+    0xff0100ffff010000, 0xff0100ff00ff00ff, 0xff0100ff00ff0000, 0xff0100ff00ff0001,
+    0xff0100ff00ff0100, 0xff0100ff0000ff01, 0xff0100ff00000000, 0xff0100ff000001ff,
+    0xff0100ff00000101, 0xff0100ff00010001, 0xff0100ff01ff0000, 0xff0100ff0100ff00,
+    0xff0100ff010000ff, 0xff0100ff01000100, 0xff0100ff0101ff00, 0xff0100ff01010000,
+    0xff010000ffff0100, 0xff010000ff000000, 0xff010000ff01ff00, 0xff010000ff010100,
+    0xff01000000ffffff, 0xff01000000ff0000, 0xff01000000ff01ff, 0xff0100000000ff00,
+    0xff010000000000ff, 0xff01000000000000, 0xff01000000000100, 0xff0100000001ff01,
+    0xff01000000010000, 0xff010000000101ff, 0xff01000001ff0100, 0xff0100000100ffff,
+    0xff010000010000ff, 0xff01000001000000, 0xff010000010001ff, 0xff01000001000101,
+    0xff0100000101ff00, 0xff010000010100ff, 0xff01000001010001, 0xff01000001010100,
+    0xff010001ffff0000, 0xff010001ff00ffff, 0xff010001ff00ff01, 0xff010001ff000100,
+    0xff010001ff010000, 0xff01000100ffff00, 0xff01000100ff0100, 0xff01000100000000,
+    0xff0100010001ffff, 0xff0100010001ff00, 0xff01000100010100, 0xff01000101ff00ff,
+    0xff01000101ff0001, 0xff0100010100ffff, 0xff01000101000101, 0xff0101ffffffffff,
+    0xff0101ffffffff01, 0xff0101ffffff01ff, 0xff0101ffffff0101, 0xff0101ffff000000,
+    0xff0101ffff01ffff, 0xff0101ffff01ff01, 0xff0101ffff0101ff, 0xff0101ffff010101,
+    0xff0101ff00ff0000, 0xff0101ff0000ff00, 0xff0101ff000000ff, 0xff0101ff00010000,
+    0xff0101ff01ffffff, 0xff0101ff01ffff01, 0xff0101ff01ff01ff, 0xff0101ff01ff0101,
+    0xff0101ff0101ffff, 0xff0101ff0101ff01, 0xff0101ff010101ff, 0xff0101ff01010101,
+    0xff010100ffff0100, 0xff010100ff00ff00, 0xff010100ff0000ff, 0xff010100ff000100,
+    0xff010100ff010000, 0xff01010000ff0001, 0xff01010000ff0100, 0xff0101000000ff01,
+    0xff01010000000000, 0xff0101000001ff00, 0xff010100000100ff, 0xff01010000010001,
+    0xff01010000010100, 0xff01010001ff0000, 0xff0101000100ffff, 0xff01010001000001,
+    0xff01010001000100, 0xff010100010100ff, 0xff01010001010000, 0xff010101ffffffff,
+    0xff010101ffffff01, 0xff010101ffff01ff, 0xff010101ffff0101, 0xff010101ff01ffff,
+    0xff010101ff01ff01, 0xff010101ff0101ff, 0xff010101ff010101, 0xff01010100ff0000,
+    0xff0101010000ff00, 0xff01010100000001, 0xff01010100000100, 0xff01010100010000,
+    0xff01010101ffffff, 0xff01010101ffff01, 0xff01010101ff01ff, 0xff01010101ff0101,
+    0xff01010101000000, 0xff0101010101ffff, 0xff0101010101ff01, 0xff010101010101ff,
+    0xff01010101010101, 0x00ffffffffff0000, 0x00ffffffff00ff00, 0x00ffffffff000001,
+    0x00ffffffff010000, 0x00ffffff00ff0100, 0x00ffffff0000ff01, 0x00ffffff00000000,
+    0x00ffffff000001ff, 0x00ffffff00000101, 0x00ffffff0001ff00, 0x00ffffff000100ff,
+    0x00ffffff00010001, 0x00ffffff010000ff, 0x00ffffff01000100, 0x00ffffff0101ff00,
+    0x00ffffff01010001, 0x00ffff00ffffffff, 0x00ffff00ffffff00, 0x00ffff00ffff00ff,
+    0x00ffff00ffff0001, 0x00ffff00ffff0100, 0x00ffff00ff00ff01, 0x00ffff00ff000000,
+    0x00ffff00ff000001, 0x00ffff00ff0001ff, 0x00ffff00ff000101, 0x00ffff00ff01ff00,
+    0x00ffff00ff010001, 0x00ffff00ff010100, 0x00ffff0000ff0000, 0x00ffff0000ff01ff,
+    0x00ffff0000ff0101, 0x00ffff000000ff00, 0x00ffff00000000ff, 0x00ffff0000000000,
+    0x00ffff0000000001, 0x00ffff0000000100, 0x00ffff0000000101, 0x00ffff0000010000,
+    0x00ffff00000101ff, 0x00ffff0000010101, 0x00ffff0001ffff00, 0x00ffff0001ff00ff,
+    0x00ffff0001ff0001, 0x00ffff000100ffff, 0x00ffff000100ff01, 0x00ffff0001000000,
+    0x00ffff000101ffff, 0x00ffff000101ff00, 0x00ffff000101ff01, 0x00ffff01ffff0000,
+    0x00ffff01ff00ff00, 0x00ffff01ff0000ff, 0x00ffff01ff000001, 0x00ffff01ff010000,
+    0x00ffff0100ffff00, 0x00ffff010000ff01, 0x00ffff0100000000, 0x00ffff0100000101,
+    0x00ffff01000100ff, 0x00ffff0100010100, 0x00ffff0101ff0100, 0x00ffff01010000ff,
+    0x00ffff0101010000, 0x00ff00ffffffff00, 0x00ff00ffff000000, 0x00ff00ffff000100,
+    0x00ff00ffff010100, 0x00ff00ff00ff0000, 0x00ff00ff00ff01ff, 0x00ff00ff00ff0101,
+    0x00ff00ff0000ff00, 0x00ff00ff000000ff, 0x00ff00ff00000000, 0x00ff00ff00000001,
+    0x00ff00ff0001ff00, 0x00ff00ff0001ff01, 0x00ff00ff00010000, 0x00ff00ff000101ff,
+    0x00ff00ff00010101, 0x00ff00ff01ffff00, 0x00ff00ff01ff0001, 0x00ff00ff01ff0100,
+    0x00ff00ff0100ffff, 0x00ff00ff0100ff01, 0x00ff00ff01000000, 0x00ff00ff0101ffff,
+    0x00ff00ff0101ff00, 0x00ff00ff01010100, 0x00ff0000ffffff00, 0x00ff0000ffffff01,
+    0x00ff0000ffff0000, 0x00ff0000ffff0101, 0x00ff0000ff00ff00, 0x00ff0000ff0000ff,
+    0x00ff0000ff000000, 0x00ff0000ff000001, 0x00ff0000ff000100, 0x00ff0000ff01ffff,
+    0x00ff0000ff010000, 0x00ff0000ff010101, 0x00ff000000ffff00, 0x00ff000000ff00ff,
+    0x00ff000000ff0000, 0x00ff000000ff0001, 0x00ff000000ff0100, 0x00ff00000000ffff,
+    0x00ff00000000ff00, 0x00ff0000000000ff, 0x00ff000000000000, 0x00ff000000000001,
+    0x00ff0000000001ff, 0x00ff000000000100, 0x00ff00000001ff00, 0x00ff0000000100ff,
+    0x00ff000000010000, 0x00ff000000010001, 0x00ff000000010100, 0x00ff000001ffff01,
+    0x00ff000001ff00ff, 0x00ff000001ff0000, 0x00ff000001ff01ff, 0x00ff00000100ff00,
+    0x00ff0000010000ff, 0x00ff000001000000, 0x00ff000001000001, 0x00ff000001000100,
+    0x00ff000001000101, 0x00ff000001010000, 0x00ff0000010101ff, 0x00ff000001010101,
+    0x00ff0001ffffff00, 0x00ff0001ffff0000, 0x00ff0001ffff0100, 0x00ff0001ff0000ff,
+    0x00ff0001ff000000, 0x00ff0001ff0001ff, 0x00ff0001ff000101, 0x00ff0001ff01ff00,
+    0x00ff0001ff0100ff, 0x00ff0001ff010100, 0x00ff000100ffffff, 0x00ff000100ffff01,
+    0x00ff000100ff0000, 0x00ff000100ff01ff, 0x00ff00010000ffff, 0x00ff00010000ff00,
+    0x00ff00010000ff01, 0x00ff000100000000, 0x00ff000100000001, 0x00ff000100000100,
+    0x00ff00010001ff01, 0x00ff000100010000, 0x00ff0001000101ff, 0x00ff000101ffff00,
+    0x00ff000101ff0000, 0x00ff000101ff0101, 0x00ff0001010000ff, 0x00ff000101000000,
+    0x00ff00010101ff00, 0x00ff0001010100ff, 0x00ff000101010001, 0x00ff01ffffff0000,
+    0x00ff01ffff00ff00, 0x00ff01ffff000000, 0x00ff01ffff000101, 0x00ff01ffff010000,
+    0x00ff01ff00ffff01, 0x00ff01ff00ff0100, 0x00ff01ff0000ffff, 0x00ff01ff00000000,
+    0x00ff01ff000001ff, 0x00ff01ff0001ff00, 0x00ff01ff000100ff, 0x00ff01ff00010001,
+    0x00ff01ff00010100, 0x00ff01ff01ff0000, 0x00ff01ff0100ff00, 0x00ff01ff010000ff,
+    0x00ff01ff01000001, 0x00ff01ff01000100, 0x00ff01ff01010000, 0x00ff0100ffffff00,
+    0x00ff0100ffff0000, 0x00ff0100ffff0001, 0x00ff0100ffff0101, 0x00ff0100ff00ffff,
+    0x00ff0100ff0000ff, 0x00ff0100ff000000, 0x00ff0100ff0001ff, 0x00ff0100ff01ff00,
+    0x00ff0100ff0100ff, 0x00ff0100ff010001, 0x00ff010000ffffff, 0x00ff010000ff0000,
+    0x00ff010000ff0101, 0x00ff01000000ff00, 0x00ff01000000ff01, 0x00ff0100000000ff,
+    0x00ff010000000000, 0x00ff010000000001, 0x00ff010000000100, 0x00ff01000001ffff,
+    0x00ff01000001ff01, 0x00ff010000010000, 0x00ff010000010001, 0x00ff010000010101,
+    0x00ff010001ff0001, 0x00ff010001ff0100, 0x00ff01000100ff01, 0x00ff010001000000,
+    0x00ff010001000001, 0x00ff0100010001ff, 0x00ff01000101ff00, 0x00ff0100010100ff,
+    0x00ff010001010001, 0x00ff010001010100, 0x00ff0101ff000001, 0x00ff010100ff00ff,
+    0x00ff010100ff0001, 0x00ff010100ff0100, 0x00ff010100000000, 0x00ff0101000001ff,
+    0x00ff010100000101, 0x00ff0101000100ff, 0x00ff010100010100, 0x00ff0101010000ff,
+    0x00ff010101010000, 0x0000ffffffffff00, 0x0000ffffffff00ff, 0x0000ffffffff0000,
+    0x0000ffffffff0001, 0x0000ffffffff0100, 0x0000ffffff00ff01, 0x0000ffffff000000,
+    0x0000ffffff000101, 0x0000ffffff01ff00, 0x0000ffffff0100ff, 0x0000ffffff010100,
+    0x0000ffff00ffffff, 0x0000ffff00ff0000, 0x0000ffff00ff01ff, 0x0000ffff0000ff00,
+    0x0000ffff000000ff, 0x0000ffff00000000, 0x0000ffff00000001, 0x0000ffff00000100,
+    0x0000ffff00010000, 0x0000ffff000101ff, 0x0000ffff01ff0001, 0x0000ffff01ff0100,
+    0x0000ffff01000000, 0x0000ffff010001ff, 0x0000ffff0101ffff, 0x0000ffff0101ff00,
+    0x0000ffff01010001, 0x0000ffff01010100, 0x0000ff00ffff0000, 0x0000ff00ffff01ff,
+    0x0000ff00ffff0100, 0x0000ff00ffff0101, 0x0000ff00ff00ff00, 0x0000ff00ff0000ff,
+    0x0000ff00ff000000, 0x0000ff00ff000001, 0x0000ff00ff0001ff, 0x0000ff00ff000100,
+    0x0000ff00ff01ffff, 0x0000ff00ff010000, 0x0000ff00ff010001, 0x0000ff00ff0101ff,
+    0x0000ff00ff010101, 0x0000ff0000ffff00, 0x0000ff0000ff00ff, 0x0000ff0000ff0000,
+    0x0000ff0000ff0001, 0x0000ff0000ff0100, 0x0000ff000000ffff, 0x0000ff000000ff00,
+    0x0000ff000000ff01, 0x0000ff00000000ff, 0x0000ff0000000000, 0x0000ff0000000001,
+    0x0000ff00000001ff, 0x0000ff0000000100, 0x0000ff0000000101, 0x0000ff000001ff00,
+    0x0000ff00000100ff, 0x0000ff0000010000, 0x0000ff0000010001, 0x0000ff0000010100,
+    0x0000ff0001ffff01, 0x0000ff0001ff0000, 0x0000ff000100ff00, 0x0000ff00010000ff,
+    0x0000ff0001000000, 0x0000ff0001000001, 0x0000ff0001000100, 0x0000ff000101ffff,
+    0x0000ff0001010000, 0x0000ff0001010101, 0x0000ff01ffffff00, 0x0000ff01ffff0001,
+    0x0000ff01ff00ff01, 0x0000ff01ff000000, 0x0000ff01ff000101, 0x0000ff01ff01ff00,
+    0x0000ff01ff0100ff, 0x0000ff0100ffff01, 0x0000ff0100ff0000, 0x0000ff0100ff0101,
+    0x0000ff010000ff00, 0x0000ff01000000ff, 0x0000ff0100000000, 0x0000ff0100000001,
+    0x0000ff0100000100, 0x0000ff010001ff01, 0x0000ff0100010000, 0x0000ff0101ff0000,
+    0x0000ff010100ffff, 0x0000ff010100ff01, 0x0000ff0101000000, 0x0000ff0101000100,
+    0x0000ff0101000101, 0x0000ff01010100ff, 0x000000ffffff00ff, 0x000000ffffff0000,
+    0x000000ffff00ff00, 0x000000ffff0000ff, 0x000000ffff000000, 0x000000ffff000001,
+    0x000000ffff0001ff, 0x000000ffff000100, 0x000000ffff01ff00, 0x000000ffff010000,
+    0x000000ffff0101ff, 0x000000ffff010101, 0x000000ff00ffff00, 0x000000ff00ff00ff,
+    0x000000ff00ff0000, 0x000000ff00ff0001, 0x000000ff00ff0100, 0x000000ff00ff0101,
+    0x000000ff0000ffff, 0x000000ff0000ff00, 0x000000ff000000ff, 0x000000ff00000000,
+    0x000000ff00000001, 0x000000ff000001ff, 0x000000ff00000100, 0x000000ff00000101,
+    0x000000ff0001ff00, 0x000000ff0001ff01, 0x000000ff000100ff, 0x000000ff00010000,
+    0x000000ff00010001, 0x000000ff00010100, 0x000000ff01ffffff, 0x000000ff01ff01ff,
+    0x000000ff01ff0101, 0x000000ff0100ff00, 0x000000ff010000ff, 0x000000ff01000000,
+    0x000000ff01000001, 0x000000ff01000100, 0x000000ff0101ff00, 0x000000ff010100ff,
+    0x000000ff01010000, 0x000000ff01010101, 0x00000000ffffff00, 0x00000000ffffff01,
+    0x00000000ffff00ff, 0x00000000ffff0000, 0x00000000ffff0001, 0x00000000ffff0100,
+    0x00000000ff00ffff, 0x00000000ff00ff00, 0x00000000ff00ff01, 0x00000000ff0000ff,
+    0x00000000ff000000, 0x00000000ff000001, 0x00000000ff000100, 0x00000000ff000101,
+    0x00000000ff01ff00, 0x00000000ff0100ff, 0x00000000ff010000, 0x00000000ff010001,
+    0x00000000ff010100, 0x0000000000ffffff, 0x0000000000ffff00, 0x0000000000ffff01,
+    0x0000000000ff00ff, 0x0000000000ff0000, 0x0000000000ff0001, 0x0000000000ff01ff,
     0x0000000000ff0100, 0x000000000000ffff, 0x000000000000ff00, 0x000000000000ff01,
-    0x00000000000000ff, 0x0000000000000001, 0x00000000000001ff, 0x0000000000000100,
-    0x0000000000000101, 0x000000000001ff00, 0x00000000000100ff, 0x0000000000010000,
-    0x0000000000010001, 0x0000000000010100, 0x0000000001ff0000, 0x000000000100ff00,
-    0x00000000010000ff, 0x0000000001000000, 0x0000000001000001, 0x0000000001000100,
-    0x0000000001010000, 0x00000001ffff01ff, 0x00000001ff000000, 0x0000000100ff0000,
-    0x000000010000ff00, 0x00000001000000ff, 0x0000000100000000, 0x0000000100000001,
-    0x0000000100000100, 0x0000000100010000, 0x0000000101000000, 0x000001ffff00ff00,
-    0x000001ffff010001, 0x000001ffff0101ff, 0x000001ff00ffff01, 0x000001ff0000ffff,
-    0x000001ff00000000, 0x000001ff010000ff, 0x000001ff01010100, 0x00000100ffff0100,
-    0x00000100ff000000, 0x0000010000ff0000, 0x000001000000ff00, 0x00000100000000ff,
-    0x0000010000000000, 0x0000010000000001, 0x0000010000000100, 0x0000010000010000,
-    0x0000010001000000, 0x000001000101ff01, 0x00000101ffff0001, 0x00000101ff01ffff,
-    0x0000010100000000, 0x0000010101010100, 0x0001ffffff000000, 0x0001ffff00ffffff,
-    0x0001ffff00000100, 0x0001ffff0001ff00, 0x0001ffff01000000, 0x0001ff00ffffff00,
-    0x0001ff00ffff01ff, 0x0001ff00ff010000, 0x0001ff0000000000, 0x0001ff0000010001,
-    0x0001ff0001ff0000, 0x0001ff0001010100, 0x0001ff01ff0000ff, 0x0001ff01ff000001,
-    0x0001ff0100ffffff, 0x0001ff010001ffff, 0x0001ff01000101ff, 0x0001ff010100ff01,
-    0x000100ffff00ffff, 0x000100ffff00ff01, 0x000100ffff000100, 0x000100ff00000000,
-    0x000100ff000101ff, 0x000100ff01ff0101, 0x000100ff0100ffff, 0x000100ff01010101,
-    0x00010000ff000000, 0x00010000ff010100, 0x0001000000ff0000, 0x000100000000ff00,
-    0x00010000000000ff, 0x0001000000000000, 0x0001000000000001, 0x0001000000000100,
-    0x0001000000010000, 0x0001000001ffff01, 0x0001000001000000, 0x0001000100ff0101,
-    0x0001000100000000, 0x00010001010100ff, 0x000101ffffff01ff, 0x000101ffffff0101,
-    0x000101ff00010000, 0x000101ff01ff0000, 0x000101ff0100ff01, 0x00010100ffff0000,
-    0x0001010000000000, 0x000101000001ffff, 0x0001010000010101, 0x00010100010001ff,
-    0x00010101ff00ff00, 0x00010101ff010001, 0x0001010100ffffff, 0x0001010100ff01ff,
-    0x00010101000101ff, 0x0001010101ff0000, 0x000101010100ff01, 0x0001010101000101,
-    0x01ffffffffff0101, 0x01ffffffff01ffff, 0x01ffffffff01ff01, 0x01ffffffff0101ff,
-    0x01ffffffff010101, 0x01ffffff00000000, 0x01ffffff01ff01ff, 0x01ffffff01000101,
-    0x01ffffff0101ff01, 0x01ffffff010100ff, 0x01ffff000000ff00, 0x01ffff0000000001,
-    0x01ffff00000001ff, 0x01ffff0000010000, 0x01ffff0001ff0000, 0x01ffff01ffffffff,
-    0x01ffff01ffff01ff, 0x01ffff01ff000000, 0x01ffff01ff01ffff, 0x01ffff01ff0101ff,
-    0x01ffff010100ffff, 0x01ff00ffffff0000, 0x01ff00ffff010000, 0x01ff00ff00ffff01,
-    0x01ff0000ff0000ff, 0x01ff000000000000, 0x01ff00000001ff01, 0x01ff000001ffffff,
-    0x01ff000001010100, 0x01ff0001ffffff01, 0x01ff0001ff010001, 0x01ff000101ff0100,
-    0x01ff000101000001, 0x01ff0001010100ff, 0x01ff01ffff00ffff, 0x01ff01ff00010001,
-    0x01ff01ff01000000, 0x01ff01ff010101ff, 0x01ff0100ff000001, 0x01ff010000ffff00,
-    0x01ff010000000100, 0x01ff010001ff01ff, 0x01ff01000101ffff, 0x01ff0101ffff00ff,
-    0x01ff0101ffff0101, 0x01ff0101ff0101ff, 0x01ff010100010000, 0x0100ffff00ff00ff,
-    0x0100ffff00ff0001, 0x0100ffff00000100, 0x0100ffff0100ff00, 0x0100ff00ffff0000,
-    0x0100ff00ff00ffff, 0x0100ff00ff00ff01, 0x0100ff00ff000100, 0x0100ff00ff010000,
-    0x0100ff0000000000, 0x0100ff00000100ff, 0x0100ff0001ff0101, 0x0100ff0001010101,
-    0x0100ff0100ff00ff, 0x0100ff0100ff0001, 0x0100ff0100000100, 0x0100ff0100010001,
-    0x0100ff0101000000, 0x010000ffff00ff00, 0x010000ff0000ffff, 0x010000ff00000000,
-    0x010000ff010001ff, 0x010000ff01010001, 0x01000000ffffff00, 0x01000000ffff0101,
-    0x01000000ff000000, 0x01000000ff0100ff, 0x01000000ff010101, 0x0100000000ff0000,
-    0x010000000000ff00, 0x01000000000000ff, 0x0100000000000000, 0x0100000000000001,
-    0x0100000000000100, 0x0100000000010000, 0x0100000001000000, 0x0100000100000000,
-    0x01000001000101ff, 0x0100000101ffff01, 0x010001ffff000101, 0x010001ff00ff0100,
-    0x010001ff0000ff00, 0x010001ff000100ff, 0x010001ff01ffffff, 0x01000100ffff0000,
-    0x01000100ff0001ff, 0x0100010000000000, 0x010001000001ff00, 0x0100010001ff0000,
-    0x01000100010000ff, 0x0100010001000101, 0x01000101ff00ff01, 0x0100010100ff0100,
-    0x010001010000ffff, 0x0100010101010001, 0x0101ffffffff0101, 0x0101ffffff0001ff,
-    0x0101ffffff01ffff, 0x0101ffffff010101, 0x0101ffff00000000, 0x0101ffff0101ffff,
-    0x0101ffff010101ff, 0x0101ff00ff000000, 0x0101ff0000ff0100, 0x0101ff000000ff00,
-    0x0101ff0000010000, 0x0101ff00010000ff, 0x0101ff0001000001, 0x0101ff01ff010101,
-    0x0101ff0100000000, 0x0101ff010101ff00, 0x010100ffffff0000, 0x010100ffff010000,
-    0x010100ff00ff01ff, 0x010100ff000000ff, 0x010100ff00000101, 0x010100ff01ffff00,
-    0x01010000ffffff01, 0x01010000ff000100, 0x01010000ff01ff01, 0x0101000000000000,
-    0x01010000000100ff, 0x010100000101ff01, 0x01010001ffff0000, 0x01010001ff00ffff,
-    0x01010001ff010000, 0x0101000101ffffff, 0x0101000101ff01ff, 0x0101000101010101,
-    0x010101ffff01ffff, 0x010101ff00000000, 0x010101ff0001ff01, 0x010101ff0101ffff,
-    0x010101ff010101ff, 0x01010100ffffffff, 0x01010100ff000001, 0x010101000000ff00,
-    0x0101010001010000, 0x0101010100ff0001, 0x010101010001ff01, 0x010101010101ffff,
+    0x00000000000000ff, 0x0000000000000000, 0x0000000000000001, 0x00000000000001ff,
+    0x0000000000000100, 0x0000000000000101, 0x000000000001ffff, 0x000000000001ff00,
+    0x00000000000100ff, 0x0000000000010000, 0x0000000000010001, 0x00000000000101ff,
+    0x0000000000010100, 0x0000000000010101, 0x0000000001ffff00, 0x0000000001ff00ff,
+    0x0000000001ff0000, 0x0000000001ff0100, 0x0000000001ff0101, 0x000000000100ffff,
+    0x000000000100ff00, 0x00000000010000ff, 0x0000000001000000, 0x0000000001000001,
+    0x00000000010001ff, 0x0000000001000100, 0x000000000101ff00, 0x00000000010100ff,
+    0x0000000001010000, 0x0000000001010001, 0x0000000001010100, 0x00000001ffffffff,
+    0x00000001ffffff00, 0x00000001ffffff01, 0x00000001ffff00ff, 0x00000001ffff0001,
+    0x00000001ffff01ff, 0x00000001ffff0100, 0x00000001ff00ff00, 0x00000001ff0000ff,
+    0x00000001ff000000, 0x00000001ff0001ff, 0x00000001ff000100, 0x00000001ff01ffff,
+    0x00000001ff01ff00, 0x00000001ff01ff01, 0x00000001ff0100ff, 0x00000001ff010000,
+    0x00000001ff010001, 0x00000001ff0101ff, 0x00000001ff010100, 0x0000000100ffff00,
+    0x0000000100ff0000, 0x0000000100ff0001, 0x0000000100ff01ff, 0x0000000100ff0100,
+    0x0000000100ff0101, 0x000000010000ffff, 0x000000010000ff00, 0x000000010000ff01,
+    0x00000001000000ff, 0x0000000100000000, 0x0000000100000001, 0x00000001000001ff,
+    0x0000000100000100, 0x0000000100000101, 0x000000010001ff00, 0x00000001000100ff,
+    0x0000000100010000, 0x0000000100010100, 0x0000000101ffff01, 0x0000000101ff0000,
+    0x0000000101ff0001, 0x0000000101ff01ff, 0x0000000101ff0100, 0x0000000101ff0101,
+    0x000000010100ff00, 0x0000000101000000, 0x0000000101000101, 0x000000010101ff01,
+    0x0000000101010000, 0x0000000101010001, 0x00000001010101ff, 0x0000000101010100,
+    0x000001ffffff00ff, 0x000001ffffff0000, 0x000001ffffff0001, 0x000001ffffff0100,
+    0x000001ffff00ffff, 0x000001ffff000000, 0x000001ffff0001ff, 0x000001ffff01ff00,
+    0x000001ffff010101, 0x000001ff00ff0000, 0x000001ff00ff01ff, 0x000001ff00ff0101,
+    0x000001ff0000ff00, 0x000001ff000000ff, 0x000001ff00000000, 0x000001ff00000001,
+    0x000001ff000001ff, 0x000001ff00000100, 0x000001ff0001ffff, 0x000001ff0001ff01,
+    0x000001ff000100ff, 0x000001ff00010000, 0x000001ff01ffff01, 0x000001ff01ff0100,
+    0x000001ff0100ffff, 0x000001ff0100ff01, 0x000001ff01000000, 0x000001ff010001ff,
+    0x000001ff0101ff00, 0x000001ff01010100, 0x00000100ffffff00, 0x00000100ffffff01,
+    0x00000100ffff0000, 0x00000100ffff0101, 0x00000100ff00ff00, 0x00000100ff0000ff,
+    0x00000100ff000000, 0x00000100ff000001, 0x00000100ff000100, 0x00000100ff010000,
+    0x0000010000ffff00, 0x0000010000ff00ff, 0x0000010000ff0000, 0x0000010000ff0001,
+    0x0000010000ff0100, 0x000001000000ffff, 0x000001000000ff00, 0x000001000000ff01,
+    0x00000100000000ff, 0x0000010000000000, 0x0000010000000001, 0x00000100000001ff,
+    0x0000010000000100, 0x0000010000000101, 0x000001000001ff00, 0x00000100000100ff,
+    0x0000010000010000, 0x0000010000010001, 0x0000010000010100, 0x0000010001ffff00,
+    0x0000010001ff0000, 0x0000010001ff0100, 0x000001000100ff00, 0x00000100010000ff,
+    0x0000010001000000, 0x0000010001000001, 0x00000100010001ff, 0x0000010001000100,
+    0x0000010001010000, 0x00000101ffff00ff, 0x00000101ffff01ff, 0x00000101ff000000,
+    0x00000101ff000101, 0x00000101ff01ffff, 0x00000101ff010000, 0x00000101ff010001,
+    0x00000101ff010100, 0x0000010100ff0000, 0x0000010100ff01ff, 0x0000010100ff0100,
+    0x000001010000ff00, 0x0000010100000000, 0x0000010100000001, 0x00000101000001ff,
+    0x0000010100000100, 0x000001010001ff01, 0x0000010100010000, 0x00000101000101ff,
+    0x0000010100010101, 0x0000010101ffff00, 0x0000010101ff0101, 0x000001010100ff01,
+    0x0000010101000000, 0x0000010101000001, 0x00000101010001ff, 0x0000010101000101,
+    0x000001010101ff00, 0x0001ffffffff0000, 0x0001ffffff0000ff, 0x0001ffffff000001,
+    0x0001ffffff000100, 0x0001ffffff010000, 0x0001ffff00ff00ff, 0x0001ffff0000ffff,
+    0x0001ffff00000000, 0x0001ffff00000001, 0x0001ffff000001ff, 0x0001ffff00000101,
+    0x0001ffff0001ff00, 0x0001ffff000100ff, 0x0001ffff00010001, 0x0001ffff00010100,
+    0x0001ffff01ffff00, 0x0001ffff01000001, 0x0001ffff01010000, 0x0001ff00ffffff00,
+    0x0001ff00ffff00ff, 0x0001ff00ffff0001, 0x0001ff00ffff0100, 0x0001ff00ff00ff01,
+    0x0001ff00ff000000, 0x0001ff00ff01ff00, 0x0001ff00ff01ff01, 0x0001ff00ff010001,
+    0x0001ff00ff010100, 0x0001ff0000ff0000, 0x0001ff0000ff0100, 0x0001ff000000ff00,
+    0x0001ff0000000000, 0x0001ff0000000001, 0x0001ff0000000100, 0x0001ff0000010000,
+    0x0001ff0000010001, 0x0001ff0000010101, 0x0001ff0001ff00ff, 0x0001ff0001ff0101,
+    0x0001ff000100ff01, 0x0001ff0001000000, 0x0001ff000101ff00, 0x0001ff0001010001,
+    0x0001ff0001010100, 0x0001ff01ff00ff00, 0x0001ff01ff000001, 0x0001ff01ff000100,
+    0x0001ff0100ffffff, 0x0001ff0100ffff00, 0x0001ff0100ff0001, 0x0001ff0100000000,
+    0x0001ff0100000001, 0x0001ff01000001ff, 0x0001ff010001ffff, 0x0001ff0101ff0000,
+    0x0001ff010100ff00, 0x0001ff0101000001, 0x0001ff0101010000, 0x000100ffff00ff00,
+    0x000100ffff00ff01, 0x000100ffff000000, 0x000100ffff000001, 0x000100ffff000101,
+    0x000100ffff01ff00, 0x000100ffff010001, 0x000100ffff010100, 0x000100ff00ffffff,
+    0x000100ff00ffff01, 0x000100ff00ff0000, 0x000100ff00ff01ff, 0x000100ff00ff0101,
+    0x000100ff0000ff00, 0x000100ff000000ff, 0x000100ff00000000, 0x000100ff00000001,
+    0x000100ff00000100, 0x000100ff00000101, 0x000100ff0001ffff, 0x000100ff0001ff01,
+    0x000100ff00010000, 0x000100ff01ff00ff, 0x000100ff01ff0000, 0x000100ff01ff0100,
+    0x000100ff0100ffff, 0x000100ff0100ff01, 0x000100ff010000ff, 0x000100ff01000000,
+    0x000100ff01000001, 0x000100ff010001ff, 0x000100ff01000101, 0x000100ff0101ff00,
+    0x000100ff010100ff, 0x000100ff01010100, 0x00010000ffff0000, 0x00010000ffff01ff,
+    0x00010000ffff0101, 0x00010000ff00ff00, 0x00010000ff000000, 0x00010000ff000001,
+    0x00010000ff000100, 0x0001000000ff00ff, 0x0001000000ff0000, 0x0001000000ff0001,
+    0x0001000000ff0100, 0x000100000000ffff, 0x000100000000ff00, 0x00010000000000ff,
+    0x0001000000000000, 0x0001000000000001, 0x0001000000000100, 0x000100000001ff00,
+    0x00010000000100ff, 0x0001000000010000, 0x0001000000010001, 0x0001000000010100,
+    0x0001000001ff0001, 0x0001000001ff0100, 0x0001000001ff0101, 0x000100000100ff00,
+    0x0001000001000000, 0x0001000001000001, 0x0001000001000100, 0x0001000001000101,
+    0x000100000101ff01, 0x0001000001010000, 0x0001000001010001, 0x00010000010101ff,
+    0x00010001ffffff01, 0x00010001ffff0100, 0x00010001ff000000, 0x00010001ff01ffff,
+    0x00010001ff010001, 0x00010001ff0101ff, 0x00010001ff010100, 0x0001000100ffffff,
+    0x0001000100ff0000, 0x0001000100ff01ff, 0x0001000100ff0101, 0x000100010000ff00,
+    0x00010001000000ff, 0x0001000100000000, 0x0001000100000001, 0x00010001000001ff,
+    0x0001000100000101, 0x000100010001ffff, 0x0001000100010000, 0x00010001000101ff,
+    0x0001000101ffffff, 0x0001000101ffff01, 0x0001000101ff0000, 0x0001000101ff0101,
+    0x00010001010000ff, 0x0001000101000001, 0x00010001010001ff, 0x0001000101000100,
+    0x000100010101ffff, 0x00010001010100ff, 0x0001000101010001, 0x0001000101010101,
+    0x000101ffff000001, 0x000101ffff000100, 0x000101ffff010000, 0x000101ff00ffff00,
+    0x000101ff0000ff01, 0x000101ff00000000, 0x000101ff00000101, 0x000101ff0001ff00,
+    0x000101ff00010100, 0x000101ff01ff0000, 0x000101ff0100ff00, 0x000101ff010001ff,
+    0x000101ff01010001, 0x00010100ffffff00, 0x00010100ffff00ff, 0x00010100ff00ffff,
+    0x00010100ff000000, 0x00010100ff01ff00, 0x00010100ff0100ff, 0x00010100ff010001,
+    0x00010100ff010100, 0x0001010000ffffff, 0x0001010000ffff00, 0x0001010000ff0000,
+    0x0001010000ff0001, 0x0001010000ff01ff, 0x000101000000ff00, 0x00010100000000ff,
+    0x0001010000000000, 0x0001010000000001, 0x0001010000000100, 0x000101000001ffff,
+    0x0001010000010000, 0x0001010000010101, 0x0001010001ffff01, 0x0001010001ff00ff,
+    0x0001010001ff0101, 0x0001010001000000, 0x000101000101ff00, 0x00010100010100ff,
+    0x0001010001010000, 0x0001010001010100, 0x00010101ff00ff00, 0x00010101ff000001,
+    0x00010101ff0001ff, 0x0001010100ffff00, 0x0001010100ff00ff, 0x0001010100ff0100,
+    0x000101010000ffff, 0x0001010100000000, 0x00010101000001ff, 0x0001010100000101,
+    0x00010101000100ff, 0x0001010100010000, 0x0001010100010100, 0x0001010101ff0001,
+    0x00010101010000ff, 0x00010101010001ff, 0x0001010101000101, 0x0001010101010001,
+    0x01ffffffffffffff, 0x01ffffffffffff01, 0x01ffffffffff01ff, 0x01ffffffffff0101,
+    0x01ffffffff01ffff, 0x01ffffffff01ff01, 0x01ffffffff0101ff, 0x01ffffffff010101,
+    0x01ffffff00ff0000, 0x01ffffff0000ffff, 0x01ffffff0000ff00, 0x01ffffff000000ff,
+    0x01ffffff00000001, 0x01ffffff00000100, 0x01ffffff00010000, 0x01ffffff01ffffff,
+    0x01ffffff01ffff01, 0x01ffffff01ff01ff, 0x01ffffff01ff0101, 0x01ffffff01000000,
+    0x01ffffff0101ffff, 0x01ffffff0101ff01, 0x01ffffff010101ff, 0x01ffffff01010101,
+    0x01ffff00ffff0000, 0x01ffff00ff00ff00, 0x01ffff00ff0000ff, 0x01ffff00ff000001,
+    0x01ffff00ff000100, 0x01ffff00ff010000, 0x01ffff0000ffff00, 0x01ffff0000ff00ff,
+    0x01ffff0000ff0100, 0x01ffff000000ffff, 0x01ffff000000ff01, 0x01ffff0000000000,
+    0x01ffff0000000001, 0x01ffff00000001ff, 0x01ffff0000000100, 0x01ffff00000100ff,
+    0x01ffff0000010001, 0x01ffff0000010100, 0x01ffff0001ff0000, 0x01ffff0001ff0100,
+    0x01ffff00010000ff, 0x01ffff0001000001, 0x01ffff0001000100, 0x01ffff0001010000,
+    0x01ffff01ffffffff, 0x01ffff01ffffff01, 0x01ffff01ffff01ff, 0x01ffff01ffff0101,
+    0x01ffff01ff000000, 0x01ffff01ff01ffff, 0x01ffff01ff01ff01, 0x01ffff01ff0101ff,
+    0x01ffff01ff010101, 0x01ffff010000ff00, 0x01ffff01000000ff, 0x01ffff0100000100,
+    0x01ffff0100010000, 0x01ffff0101ffffff, 0x01ffff0101ffff01, 0x01ffff0101ff01ff,
+    0x01ffff0101ff0101, 0x01ffff0101000000, 0x01ffff010101ffff, 0x01ffff010101ff01,
+    0x01ffff01010101ff, 0x01ffff0101010101, 0x01ff00ffff0000ff, 0x01ff00ffff000100,
+    0x01ff00ff00ffff00, 0x01ff00ff00ff00ff, 0x01ff00ff0000ff00, 0x01ff00ff00000000,
+    0x01ff00ff00000101, 0x01ff00ff0001ff00, 0x01ff00ff000100ff, 0x01ff00ff00010100,
+    0x01ff00ff010000ff, 0x01ff00ff01000100, 0x01ff0000ffffff00, 0x01ff0000ffff0100,
+    0x01ff0000ff00ff01, 0x01ff0000ff000000, 0x01ff0000ff000101, 0x01ff0000ff010001,
+    0x01ff0000ff010100, 0x01ff000000ffffff, 0x01ff000000ffff00, 0x01ff000000ff0000,
+    0x01ff000000ff01ff, 0x01ff00000000ff00, 0x01ff0000000000ff, 0x01ff000000000000,
+    0x01ff000000000001, 0x01ff000000000100, 0x01ff000000000101, 0x01ff000000010000,
+    0x01ff000000010001, 0x01ff0000000101ff, 0x01ff000000010101, 0x01ff000001ffff00,
+    0x01ff000001ff00ff, 0x01ff000001ff0001, 0x01ff000001ff0100, 0x01ff00000100ffff,
+    0x01ff00000100ff01, 0x01ff000001000000, 0x01ff0000010001ff, 0x01ff000001010001,
+    0x01ff0001ff00ff00, 0x01ff0001ff000001, 0x01ff0001ff000100, 0x01ff0001ff010000,
+    0x01ff000100ffff00, 0x01ff000100ff00ff, 0x01ff000100ff0100, 0x01ff000100ff0101,
+    0x01ff00010000ffff, 0x01ff000100000000, 0x01ff000100000100, 0x01ff000100000101,
+    0x01ff00010001ff00, 0x01ff000100010001, 0x01ff000100010101, 0x01ff000101ff0000,
+    0x01ff00010100ff00, 0x01ff000101000101, 0x01ff0001010100ff, 0x01ff01ffffffffff,
+    0x01ff01ffffffff01, 0x01ff01ffffff01ff, 0x01ff01ffffff0101, 0x01ff01ffff000000,
+    0x01ff01ffff01ffff, 0x01ff01ffff01ff01, 0x01ff01ffff0101ff, 0x01ff01ffff010101,
+    0x01ff01ff00ffff00, 0x01ff01ff00ff0000, 0x01ff01ff0000ff00, 0x01ff01ff000000ff,
+    0x01ff01ff00000100, 0x01ff01ff00010000, 0x01ff01ff00010100, 0x01ff01ff01ffffff,
+    0x01ff01ff01ffff01, 0x01ff01ff01ff01ff, 0x01ff01ff01ff0101, 0x01ff01ff01000000,
+    0x01ff01ff0101ffff, 0x01ff01ff0101ff01, 0x01ff01ff010101ff, 0x01ff01ff01010101,
+    0x01ff0100ffff0000, 0x01ff0100ffff0001, 0x01ff0100ff00ff00, 0x01ff0100ff0000ff,
+    0x01ff0100ff000001, 0x01ff0100ff010000, 0x01ff010000ffff00, 0x01ff010000ff00ff,
+    0x01ff010000ff0001, 0x01ff010000ff0100, 0x01ff01000000ffff, 0x01ff01000000ff01,
+    0x01ff010000000000, 0x01ff010000000101, 0x01ff01000001ff00, 0x01ff0100000100ff,
+    0x01ff010001ff0000, 0x01ff010001000001, 0x01ff010001000100, 0x01ff010001010000,
+    0x01ff0101ffffffff, 0x01ff0101ffffff01, 0x01ff0101ffff01ff, 0x01ff0101ffff0101,
+    0x01ff0101ff000000, 0x01ff0101ff01ffff, 0x01ff0101ff01ff01, 0x01ff0101ff0101ff,
+    0x01ff0101ff010101, 0x01ff010100ff0000, 0x01ff01010000ff00, 0x01ff0101000000ff,
+    0x01ff010100000001, 0x01ff010101ffffff, 0x01ff010101ffff01, 0x01ff010101ff01ff,
+    0x01ff010101ff0101, 0x01ff010101000000, 0x01ff01010101ffff, 0x01ff01010101ff01,
+    0x01ff0101010101ff, 0x01ff010101010101, 0x0100ffffffff0000, 0x0100ffffff00ff00,
+    0x0100ffffff000001, 0x0100ffffff0001ff, 0x0100ffffff000100, 0x0100ffffff010000,
+    0x0100ffff00ffff00, 0x0100ffff00ff0001, 0x0100ffff00ff0100, 0x0100ffff00000000,
+    0x0100ffff000001ff, 0x0100ffff00000101, 0x0100ffff00010100, 0x0100ffff00010101,
+    0x0100ffff01ff0000, 0x0100ffff0100ff00, 0x0100ffff010000ff, 0x0100ffff01000001,
+    0x0100ffff01000100, 0x0100ffff01010000, 0x0100ff00ffffff00, 0x0100ff00ffff00ff,
+    0x0100ff00ffff0001, 0x0100ff00ffff0100, 0x0100ff00ff00ffff, 0x0100ff00ff000000,
+    0x0100ff00ff0001ff, 0x0100ff00ff000101, 0x0100ff00ff01ff00, 0x0100ff00ff0100ff,
+    0x0100ff00ff010001, 0x0100ff00ff010100, 0x0100ff0000ffffff, 0x0100ff0000ff0000,
+    0x0100ff000000ffff, 0x0100ff000000ff00, 0x0100ff00000000ff, 0x0100ff0000000000,
+    0x0100ff0000000001, 0x0100ff0000000100, 0x0100ff000001ff01, 0x0100ff0000010000,
+    0x0100ff0001ff00ff, 0x0100ff0001ff0001, 0x0100ff000100ff01, 0x0100ff0001000000,
+    0x0100ff00010001ff, 0x0100ff000101ff00, 0x0100ff00010100ff, 0x0100ff0001010001,
+    0x0100ff0001010100, 0x0100ff01ffff0000, 0x0100ff01ff00ff00, 0x0100ff01ff0000ff,
+    0x0100ff01ff000100, 0x0100ff01ff010000, 0x0100ff0100ff00ff, 0x0100ff0100ff0001,
+    0x0100ff0100ff0100, 0x0100ff010000ffff, 0x0100ff010000ff01, 0x0100ff0100000000,
+    0x0100ff01000001ff, 0x0100ff0100010001, 0x0100ff0100010100, 0x0100ff0101ff0000,
+    0x0100ff01010000ff, 0x0100ff0101000001, 0x0100ff0101010100, 0x010000ffffffff00,
+    0x010000ffffff00ff, 0x010000ffffff0001, 0x010000ffff00ffff, 0x010000ffff000000,
+    0x010000ffff0001ff, 0x010000ffff010001, 0x010000ff00ffffff, 0x010000ff00ff0101,
+    0x010000ff0000ff00, 0x010000ff000000ff, 0x010000ff00000000, 0x010000ff00000001,
+    0x010000ff000001ff, 0x010000ff00000100, 0x010000ff0001ffff, 0x010000ff0001ff00,
+    0x010000ff0001ff01, 0x010000ff00010000, 0x010000ff01ff00ff, 0x010000ff01ff0001,
+    0x010000ff0100ff01, 0x010000ff010000ff, 0x010000ff01000000, 0x010000ff010001ff,
+    0x010000ff0101ff00, 0x010000ff01010100, 0x01000000ffffffff, 0x01000000ffff0000,
+    0x01000000ffff01ff, 0x01000000ffff0101, 0x01000000ff00ffff, 0x01000000ff00ff00,
+    0x01000000ff0000ff, 0x01000000ff000000, 0x01000000ff000001, 0x01000000ff000100,
+    0x01000000ff01ff00, 0x01000000ff010000, 0x01000000ff010100, 0x01000000ff010101,
+    0x0100000000ffff00, 0x0100000000ff00ff, 0x0100000000ff0000, 0x0100000000ff0001,
+    0x0100000000ff0100, 0x010000000000ffff, 0x010000000000ff00, 0x010000000000ff01,
+    0x01000000000000ff, 0x0100000000000000, 0x0100000000000001, 0x01000000000001ff,
+    0x0100000000000100, 0x0100000000000101, 0x010000000001ff00, 0x01000000000100ff,
+    0x0100000000010000, 0x0100000000010001, 0x0100000000010100, 0x0100000001ffff00,
+    0x0100000001ff0000, 0x0100000001ff01ff, 0x010000000100ff00, 0x010000000100ff01,
+    0x01000000010000ff, 0x0100000001000000, 0x0100000001000001, 0x0100000001000100,
+    0x0100000001000101, 0x010000000101ffff, 0x010000000101ff01, 0x0100000001010000,
+    0x01000000010101ff, 0x0100000001010101, 0x01000001ffffff00, 0x01000001ffff00ff,
+    0x01000001ff00ffff, 0x01000001ff000000, 0x01000001ff000100, 0x01000001ff01ffff,
+    0x01000001ff010001, 0x01000001ff010100, 0x0100000100ff0000, 0x0100000100ff01ff,
+    0x0100000100ff0100, 0x010000010000ff00, 0x010000010000ff01, 0x0100000100000000,
+    0x0100000100000001, 0x0100000100000100, 0x0100000100010000, 0x01000001000101ff,
+    0x0100000101ffff01, 0x0100000101ff00ff, 0x0100000101ff0100, 0x0100000101ff0101,
+    0x010000010100ff01, 0x01000001010000ff, 0x0100000101000000, 0x01000001010100ff,
+    0x0100000101010001, 0x0100000101010100, 0x010001ffffff0000, 0x010001ffff000001,
+    0x010001ffff000100, 0x010001ffff010000, 0x010001ff00ffff00, 0x010001ff00ff0001,
+    0x010001ff0000ffff, 0x010001ff0000ff01, 0x010001ff00000000, 0x010001ff00000001,
+    0x010001ff00000101, 0x010001ff000100ff, 0x010001ff00010000, 0x010001ff01ff0000,
+    0x010001ff0100ff00, 0x010001ff01000001, 0x010001ff01000100, 0x010001ff01010000,
+    0x01000100ffff00ff, 0x01000100ffff0001, 0x01000100ffff0100, 0x01000100ff00ffff,
+    0x01000100ff00ff01, 0x01000100ff000000, 0x01000100ff0001ff, 0x01000100ff000101,
+    0x01000100ff01ffff, 0x01000100ff01ff00, 0x01000100ff0100ff, 0x01000100ff010001,
+    0x0100010000ffffff, 0x0100010000ffff01, 0x0100010000ff0000, 0x0100010000ff01ff,
+    0x0100010000ff0101, 0x010001000000ff00, 0x01000100000000ff, 0x0100010000000000,
+    0x0100010000000001, 0x0100010000000100, 0x010001000001ff01, 0x0100010000010000,
+    0x0100010000010001, 0x0100010000010101, 0x0100010001ffff00, 0x0100010001ff00ff,
+    0x010001000100ffff, 0x010001000100ff01, 0x0100010001000000, 0x0100010001000101,
+    0x010001000101ff00, 0x0100010001010001, 0x01000101ffff0000, 0x01000101ff000000,
+    0x01000101ff010000, 0x0100010100ff00ff, 0x0100010100ff0001, 0x0100010100ff0100,
+    0x010001010000ffff, 0x0100010100000000, 0x01000101000001ff, 0x010001010001ff00,
+    0x0100010101ff0000, 0x010001010100ff00, 0x01000101010000ff, 0x0100010101000000,
+    0x0100010101000001, 0x0101ffffffffffff, 0x0101ffffffffff01, 0x0101ffffffff01ff,
+    0x0101ffffffff0101, 0x0101ffffff000000, 0x0101ffffff01ffff, 0x0101ffffff01ff01,
+    0x0101ffffff0101ff, 0x0101ffffff010101, 0x0101ffff00ff0000, 0x0101ffff0000ff00,
+    0x0101ffff000000ff, 0x0101ffff00000001, 0x0101ffff00000100, 0x0101ffff01ffffff,
+    0x0101ffff01ffff01, 0x0101ffff01ff01ff, 0x0101ffff01ff0101, 0x0101ffff01000000,
+    0x0101ffff0101ffff, 0x0101ffff0101ff01, 0x0101ffff010101ff, 0x0101ffff01010101,
+    0x0101ff00ffff0000, 0x0101ff00ffff0100, 0x0101ff00ff00ff00, 0x0101ff00ff0000ff,
+    0x0101ff00ff000001, 0x0101ff00ff000100, 0x0101ff00ff000101, 0x0101ff0000ff0001,
+    0x0101ff0000ff0100, 0x0101ff000000ff00, 0x0101ff0000000000, 0x0101ff00000001ff,
+    0x0101ff0000000101, 0x0101ff000001ff00, 0x0101ff00000100ff, 0x0101ff0001ff0000,
+    0x0101ff000100ffff, 0x0101ff000100ff01, 0x0101ff0001000001, 0x0101ff0001000100,
+    0x0101ff01ffffff01, 0x0101ff01ffff01ff, 0x0101ff01ffff0101, 0x0101ff01ff00ffff,
+    0x0101ff01ff000100, 0x0101ff01ff01ff01, 0x0101ff01ff0101ff, 0x0101ff01ff010101,
+    0x0101ff0100ff0000, 0x0101ff010000ff00, 0x0101ff0100000001, 0x0101ff0100000100,
+    0x0101ff0100010000, 0x0101ff0101ffffff, 0x0101ff0101ffff01, 0x0101ff0101ff01ff,
+    0x0101ff0101ff0101, 0x0101ff0101000000, 0x0101ff010101ffff, 0x0101ff010101ff01,
+    0x0101ff01010101ff, 0x0101ff0101010101, 0x010100ffff000100, 0x010100ffff010000,
+    0x010100ff00ffff00, 0x010100ff00ff00ff, 0x010100ff0000ffff, 0x010100ff000000ff,
+    0x010100ff00000000, 0x010100ff000001ff, 0x010100ff00000101, 0x010100ff0001ff00,
+    0x010100ff00010000, 0x010100ff00010001, 0x010100ff000101ff, 0x010100ff00010100,
+    0x010100ff01ff0000, 0x01010000ffff0001, 0x01010000ffff0100, 0x01010000ff00ffff,
+    0x01010000ff00ff01, 0x01010000ff000000, 0x01010000ff0001ff, 0x01010000ff010001,
+    0x01010000ff010100, 0x0101000000ffff01, 0x0101000000ff0000, 0x010100000000ff00,
+    0x01010000000000ff, 0x0101000000000000, 0x0101000000000001, 0x0101000000000100,
+    0x0101000000010000, 0x0101000000010101, 0x0101000001ffff00, 0x0101000001ff00ff,
+    0x0101000001ff0000, 0x0101000001ff0001, 0x0101000001ff0100, 0x010100000100ff01,
+    0x0101000001000000, 0x01010000010001ff, 0x01010001ffff0000, 0x01010001ff00ff00,
+    0x01010001ff000001, 0x01010001ff000101, 0x01010001ff01ff00, 0x01010001ff010000,
+    0x0101000100ff00ff, 0x0101000100ff0001, 0x0101000100ff0101, 0x010100010000ff01,
+    0x0101000100000000, 0x0101000100000001, 0x01010001000001ff, 0x010100010001ffff,
+    0x010100010001ff01, 0x0101000101ff0001, 0x010100010100ffff, 0x0101000101000000,
+    0x0101000101000001, 0x0101000101000100, 0x010100010101ff00, 0x01010001010100ff,
+    0x0101000101010001, 0x010101ffffffffff, 0x010101ffffffff01, 0x010101ffffff01ff,
+    0x010101ffffff0101, 0x010101ffff01ffff, 0x010101ffff01ff01, 0x010101ffff0101ff,
+    0x010101ffff010101, 0x010101ff0000ff00, 0x010101ff000000ff, 0x010101ff00000001,
+    0x010101ff00000100, 0x010101ff01ffffff, 0x010101ff01ffff01, 0x010101ff01ff01ff,
+    0x010101ff01ff0101, 0x010101ff01000000, 0x010101ff0101ffff, 0x010101ff0101ff01,
+    0x010101ff010101ff, 0x010101ff01010101, 0x01010100ffff0000, 0x01010100ff0000ff,
+    0x01010100ff000100, 0x01010100ff01ff00, 0x01010100ff010000, 0x0101010000ffff00,
+    0x010101000000ffff, 0x0101010000000000, 0x0101010000000101, 0x010101000001ff00,
+    0x0101010000010001, 0x0101010000010100, 0x010101000100ffff, 0x0101010001000001,
+    0x01010101ffffffff, 0x01010101ffffff01, 0x01010101ffff01ff, 0x01010101ffff0101,
+    0x01010101ff01ffff, 0x01010101ff01ff01, 0x01010101ff0101ff, 0x01010101ff010101,
+    0x010101010000ff00, 0x01010101000000ff, 0x0101010100000001, 0x0101010101ffffff,
+    0x0101010101ffff01, 0x0101010101ff01ff, 0x0101010101ff0101, 0x0101010101000000,
+    0x010101010101ffff, 0x010101010101ff01, 0x01010101010101ff, 0x0101010101010101,
 GGML_TABLE_END()
+#else
+GGML_TABLE_BEGIN(uint32_t, iq1s_grid_gpu, NGRID_IQ1S)
+    0x00000000, 0x00000002, 0x00000101, 0x00000200, 0x00000202, 0x00010001, 0x00010101, 0x00020000,
+    0x00020002, 0x00020200, 0x00020202, 0x01000101, 0x01010001, 0x01010100, 0x01010102, 0x01020101,
+    0x02000000, 0x02000002, 0x02000200, 0x02000202, 0x02010101, 0x02020000, 0x02020002, 0x02020200,
+    0x02020202, 0x00000110, 0x00000111, 0x00010011, 0x00010110, 0x00010112, 0x00010211, 0x00010212,
+    0x00020111, 0x01000011, 0x01000112, 0x01000211, 0x01010012, 0x01010111, 0x01010212, 0x01020011,
+    0x01020110, 0x01020112, 0x01020210, 0x02000111, 0x02010011, 0x02010110, 0x02010112, 0x02020111,
+    0x00000020, 0x00000022, 0x00000220, 0x00000222, 0x00010121, 0x00020020, 0x00020022, 0x00020220,
+    0x00020222, 0x01000121, 0x01010021, 0x01010221, 0x01020120, 0x01020221, 0x02000020, 0x02000022,
+    0x02000220, 0x02000222, 0x02010021, 0x02010121, 0x02010221, 0x02020020, 0x02020022, 0x02020220,
+    0x02020222, 0x00011001, 0x00011100, 0x00011102, 0x00021101, 0x01001001, 0x01001201, 0x01011101,
+    0x01011202, 0x01021100, 0x01021101, 0x02011001, 0x02011201, 0x02021101, 0x00001011, 0x00001110,
+    0x00001111, 0x00001112, 0x00011111, 0x00011210, 0x00011212, 0x00021211, 0x01001010, 0x01001111,
+    0x01001212, 0x01011010, 0x01011011, 0x01011110, 0x01011111, 0x01011112, 0x01011211, 0x01021010,
+    0x01021012, 0x01021111, 0x01021210, 0x01021212, 0x02001011, 0x02011011, 0x02011111, 0x02011210,
+    0x02011212, 0x02021011, 0x02021110, 0x02021111, 0x02021112, 0x02021211, 0x00011120, 0x00011221,
+    0x01001021, 0x01001120, 0x01011020, 0x01011022, 0x01011121, 0x01011220, 0x01021020, 0x01021021,
+    0x01021122, 0x01021221, 0x02001121, 0x02011021, 0x02011120, 0x02011221, 0x00002000, 0x00002002,
+    0x00002200, 0x00002202, 0x00012101, 0x00022000, 0x00022002, 0x00022200, 0x00022202, 0x01002101,
+    0x01012001, 0x01012102, 0x01022101, 0x02002000, 0x02002002, 0x02002200, 0x02002202, 0x02012101,
+    0x02022000, 0x02022002, 0x02022200, 0x02022202, 0x00002111, 0x00012011, 0x00012110, 0x00012211,
+    0x00022110, 0x00022111, 0x01002011, 0x01012010, 0x01012011, 0x01012111, 0x01022011, 0x01022110,
+    0x01022211, 0x02012011, 0x02012110, 0x02012112, 0x02012211, 0x02022111, 0x00002020, 0x00002022,
+    0x00002220, 0x00002222, 0x00012121, 0x00022020, 0x00022022, 0x00022220, 0x00022222, 0x01002121,
+    0x01012021, 0x01012221, 0x01022021, 0x01022121, 0x02002020, 0x02002022, 0x02002121, 0x02002220,
+    0x02002222, 0x02012121, 0x02022020, 0x02022022, 0x02022220, 0x02022222, 0x00110000, 0x00110001,
+    0x00110100, 0x00110201, 0x00120100, 0x00120101, 0x01100001, 0x01100100, 0x01110000, 0x01110101,
+    0x01110200, 0x01120001, 0x01120100, 0x01120101, 0x01120201, 0x02110001, 0x02110100, 0x02110102,
+    0x02120001, 0x02120101, 0x00100011, 0x00100110, 0x00100112, 0x00100211, 0x00110010, 0x00110012,
+    0x00110111, 0x00110210, 0x00120011, 0x00120110, 0x00120211, 0x01100111, 0x01100212, 0x01110010,
+    0x01110011, 0x01110012, 0x01110110, 0x01110111, 0x01110112, 0x01110211, 0x01120010, 0x01120111,
+    0x02100110, 0x02110012, 0x02110111, 0x02120011, 0x02120110, 0x00110021, 0x00110120, 0x00110122,
+    0x00120121, 0x01100020, 0x01100122, 0x01100221, 0x01110022, 0x01110121, 0x01110220, 0x01110222,
+    0x01120120, 0x01120122, 0x02100121, 0x02110021, 0x02110120, 0x02110122, 0x02120121, 0x00101001,
+    0x00101102, 0x00101201, 0x00111100, 0x00111101, 0x00111200, 0x00111201, 0x00121001, 0x00121102,
+    0x01101001, 0x01101101, 0x01101102, 0x01101200, 0x01101202, 0x01111001, 0x01111100, 0x01111101,
+    0x01111102, 0x01111201, 0x01121002, 0x01121101, 0x01121200, 0x02101100, 0x02101201, 0x02111000,
+    0x02111100, 0x02111101, 0x02111200, 0x02111201, 0x02111202, 0x02121001, 0x02121100, 0x02121101,
+    0x02121201, 0x00101012, 0x00101111, 0x00101212, 0x00111011, 0x00111110, 0x00111111, 0x00111112,
+    0x00111211, 0x00121010, 0x00121012, 0x00121111, 0x00121210, 0x00121212, 0x01101011, 0x01101110,
+    0x01101111, 0x01101112, 0x01111011, 0x01111012, 0x01111110, 0x01111111, 0x01111112, 0x01111211,
+    0x01111212, 0x01121011, 0x01121110, 0x01121111, 0x01121112, 0x01121211, 0x02101010, 0x02101012,
+    0x02101110, 0x02101111, 0x02101210, 0x02101212, 0x02111010, 0x02111011, 0x02111110, 0x02111111,
+    0x02111112, 0x02111211, 0x02111212, 0x02121010, 0x02121012, 0x02121111, 0x00101021, 0x00101120,
+    0x00101121, 0x00101122, 0x00111121, 0x00111122, 0x00111220, 0x00111222, 0x00121021, 0x00121122,
+    0x01101020, 0x01101022, 0x01101120, 0x01101121, 0x01101220, 0x01101222, 0x01111021, 0x01111121,
+    0x01111122, 0x01111220, 0x01111221, 0x01121021, 0x01121120, 0x01121121, 0x01121220, 0x01121221,
+    0x01121222, 0x02101122, 0x02101222, 0x02111022, 0x02111121, 0x02121120, 0x02121221, 0x00112001,
+    0x00112102, 0x00122101, 0x01102001, 0x01102100, 0x01102102, 0x01102201, 0x01112000, 0x01112101,
+    0x01112200, 0x01112202, 0x01122000, 0x01122001, 0x01122100, 0x01122102, 0x01122201, 0x02102101,
+    0x02112001, 0x02112100, 0x02122101, 0x00112010, 0x00112012, 0x00112111, 0x00112212, 0x00122011,
+    0x00122111, 0x01102012, 0x01102110, 0x01102111, 0x01102210, 0x01112011, 0x01112110, 0x01112111,
+    0x01112112, 0x01112211, 0x01112212, 0x01122010, 0x01122111, 0x01122212, 0x02102211, 0x02112011,
+    0x02112012, 0x02112111, 0x02112210, 0x02122011, 0x02122112, 0x02122211, 0x00102221, 0x00112122,
+    0x00122120, 0x00122122, 0x01102120, 0x01102122, 0x01102221, 0x01112020, 0x01112022, 0x01112121,
+    0x01112220, 0x01122021, 0x01122122, 0x01122221, 0x02102121, 0x02112021, 0x02112122, 0x02112222,
+    0x00200000, 0x00200002, 0x00200200, 0x00200202, 0x00210101, 0x00220000, 0x00220002, 0x00220101,
+    0x00220200, 0x00220202, 0x01200101, 0x01210001, 0x01210201, 0x01220001, 0x01220101, 0x02200000,
+    0x02200002, 0x02200200, 0x02200202, 0x02210101, 0x02220000, 0x02220002, 0x02220101, 0x02220200,
+    0x02220202, 0x00200111, 0x00210011, 0x00210110, 0x00210211, 0x00220111, 0x01200012, 0x01200110,
+    0x01200211, 0x01210111, 0x01210210, 0x01210212, 0x01220011, 0x01220110, 0x01220111, 0x01220112,
+    0x02200111, 0x02210010, 0x02210112, 0x02210211, 0x02220111, 0x00200021, 0x00200220, 0x00200222,
+    0x00210021, 0x00210121, 0x00220020, 0x00220022, 0x00220220, 0x00220222, 0x01200121, 0x01210021,
+    0x01210122, 0x01210221, 0x01220121, 0x02200021, 0x02200220, 0x02200222, 0x02210021, 0x02210121,
+    0x02220020, 0x02220022, 0x02220220, 0x02220222, 0x00201101, 0x00211100, 0x00211102, 0x00211201,
+    0x00221101, 0x01201100, 0x01201101, 0x01201102, 0x01201201, 0x01211002, 0x01211101, 0x01211200,
+    0x01211202, 0x01221102, 0x02201101, 0x02211001, 0x02211100, 0x02211201, 0x02221001, 0x02221101,
+    0x00201211, 0x00211111, 0x00221011, 0x00221211, 0x01201010, 0x01201111, 0x01201210, 0x01211011,
+    0x01211110, 0x01211111, 0x01211211, 0x01221012, 0x01221111, 0x01221210, 0x02201211, 0x02211010,
+    0x02211110, 0x02211111, 0x02211210, 0x02211212, 0x02221011, 0x02221110, 0x02221112, 0x02221211,
+    0x00201121, 0x00211020, 0x00211022, 0x00211221, 0x00221121, 0x01201021, 0x01201221, 0x01211121,
+    0x01221020, 0x01221021, 0x01221221, 0x02201120, 0x02201122, 0x02211020, 0x02211222, 0x00202000,
+    0x00202002, 0x00202200, 0x00202202, 0x00212101, 0x00222000, 0x00222002, 0x00222200, 0x00222202,
+    0x01202101, 0x01212001, 0x01212100, 0x01222101, 0x02202000, 0x02202002, 0x02202200, 0x02202202,
+    0x02222000, 0x02222002, 0x02222200, 0x02222202, 0x00202211, 0x00212011, 0x00212110, 0x00212211,
+    0x00222111, 0x01202112, 0x01202211, 0x01212012, 0x01212111, 0x01222011, 0x01222110, 0x01222112,
+    0x01222211, 0x02202111, 0x02212010, 0x02212112, 0x02212211, 0x02222110, 0x02222111, 0x00202020,
+    0x00202022, 0x00202220, 0x00202222, 0x00222020, 0x00222022, 0x00222220, 0x00222222, 0x01202121,
+    0x01212021, 0x01212122, 0x01212221, 0x01222121, 0x02202020, 0x02202022, 0x02202220, 0x02202222,
+    0x02212121, 0x02222020, 0x02222022, 0x02222220, 0x02222222, 0x10000101, 0x10010001, 0x10010102,
+    0x10020101, 0x11000201, 0x11010002, 0x11010101, 0x11010200, 0x11010202, 0x11020001, 0x11020100,
+    0x11020102, 0x12010100, 0x12010201, 0x12020001, 0x12020102, 0x10000010, 0x10000011, 0x10000110,
+    0x10000112, 0x10000211, 0x10010012, 0x10010111, 0x10010112, 0x10010210, 0x10010212, 0x10020011,
+    0x10020112, 0x10020211, 0x11000111, 0x11000210, 0x11000212, 0x11010011, 0x11010110, 0x11010111,
+    0x11010112, 0x11010211, 0x11010212, 0x11020111, 0x11020210, 0x11020212, 0x12000011, 0x12000110,
+    0x12000112, 0x12010010, 0x12010012, 0x12010111, 0x12020010, 0x12020011, 0x12020012, 0x10000121,
+    0x10010021, 0x10010120, 0x10010122, 0x10020121, 0x11000021, 0x11010022, 0x11010121, 0x11010222,
+    0x11020120, 0x11020221, 0x12000221, 0x12010120, 0x12020121, 0x10001001, 0x10011101, 0x10011201,
+    0x10021201, 0x11001101, 0x11001200, 0x11001202, 0x11011001, 0x11011100, 0x11011101, 0x11011102,
+    0x11021001, 0x11021002, 0x11021101, 0x11021200, 0x11021202, 0x12001001, 0x12001102, 0x12001201,
+    0x12011000, 0x12011002, 0x12011101, 0x12021000, 0x12021001, 0x12021201, 0x10001011, 0x10001012,
+    0x10001111, 0x10001212, 0x10011011, 0x10011110, 0x10011111, 0x10011112, 0x10011211, 0x10021010,
+    0x10021111, 0x10021212, 0x11001011, 0x11001110, 0x11001111, 0x11001112, 0x11001211, 0x11011010,
+    0x11011011, 0x11011110, 0x11011111, 0x11011112, 0x11011210, 0x11011211, 0x11021011, 0x11021110,
+    0x11021111, 0x11021112, 0x11021211, 0x12001012, 0x12001110, 0x12001111, 0x12001210, 0x12011011,
+    0x12011110, 0x12011111, 0x12011112, 0x12011211, 0x12011212, 0x12021111, 0x12021210, 0x12021212,
+    0x10001021, 0x10001121, 0x10001221, 0x10011120, 0x10011121, 0x10011220, 0x10011222, 0x10021021,
+    0x10021120, 0x10021221, 0x11001020, 0x11001022, 0x11001121, 0x11001220, 0x11011020, 0x11011021,
+    0x11011022, 0x11011121, 0x11011122, 0x11011221, 0x11021022, 0x11021121, 0x11021220, 0x12001021,
+    0x12001121, 0x12001222, 0x12011120, 0x12011121, 0x12021021, 0x12021120, 0x12021122, 0x10002101,
+    0x10012001, 0x10012101, 0x10012202, 0x10022101, 0x11002002, 0x11002201, 0x11012000, 0x11012101,
+    0x11012200, 0x11022001, 0x11022100, 0x11022102, 0x11022201, 0x12002101, 0x12012001, 0x12012100,
+    0x12012102, 0x12012201, 0x12022101, 0x10002011, 0x10002111, 0x10002112, 0x10002212, 0x10012010,
+    0x10012110, 0x10012111, 0x10012210, 0x10022011, 0x10022110, 0x10022112, 0x11002010, 0x11002111,
+    0x11002212, 0x11012011, 0x11012012, 0x11012110, 0x11012111, 0x11012112, 0x11012211, 0x11022010,
+    0x11022012, 0x11022111, 0x11022112, 0x11022212, 0x12002112, 0x12002211, 0x12012012, 0x12012111,
+    0x12012112, 0x12012210, 0x12022011, 0x12022110, 0x12022112, 0x12022211, 0x10012122, 0x11002120,
+    0x11002122, 0x11002221, 0x11012121, 0x11012220, 0x11012222, 0x11022120, 0x11022221, 0x12012120,
+    0x12022121, 0x10100001, 0x10100100, 0x10100101, 0x10100102, 0x10100201, 0x10110002, 0x10110101,
+    0x10110202, 0x10120001, 0x10120100, 0x10120201, 0x11100000, 0x11100101, 0x11100200, 0x11110001,
+    0x11110100, 0x11110101, 0x11110102, 0x11110201, 0x11120101, 0x11120200, 0x12100102, 0x12100201,
+    0x12110101, 0x12110200, 0x12120000, 0x12120001, 0x12120102, 0x12120201, 0x10100111, 0x10100210,
+    0x10100211, 0x10100212, 0x10110011, 0x10110110, 0x10110111, 0x10110112, 0x10110210, 0x10110211,
+    0x10120010, 0x10120111, 0x10120112, 0x10120210, 0x10120212, 0x11100011, 0x11100110, 0x11100111,
+    0x11100112, 0x11100211, 0x11110010, 0x11110011, 0x11110012, 0x11110110, 0x11110111, 0x11110112,
+    0x11110210, 0x11110211, 0x11110212, 0x11120011, 0x11120110, 0x11120111, 0x11120112, 0x11120211,
+    0x12100012, 0x12100111, 0x12110011, 0x12110110, 0x12110111, 0x12110112, 0x12110211, 0x12120010,
+    0x12120111, 0x12120212, 0x10100021, 0x10100122, 0x10110022, 0x10110121, 0x10110222, 0x10120021,
+    0x10120120, 0x11100022, 0x11100121, 0x11100222, 0x11110021, 0x11110120, 0x11110121, 0x11110122,
+    0x11110221, 0x11120022, 0x11120121, 0x12100121, 0x12110020, 0x12110022, 0x12110121, 0x12110221,
+    0x12110222, 0x12120120, 0x10101100, 0x10101101, 0x10111001, 0x10111100, 0x10111101, 0x10111102,
+    0x10111200, 0x10111201, 0x10121001, 0x10121101, 0x10121200, 0x10121202, 0x11101001, 0x11101100,
+    0x11101101, 0x11101102, 0x11101201, 0x11101202, 0x11111000, 0x11111001, 0x11111100, 0x11111101,
+    0x11111102, 0x11111200, 0x11111201, 0x11111202, 0x11121001, 0x11121002, 0x11121100, 0x11121101,
+    0x11121102, 0x11121201, 0x12101000, 0x12101200, 0x12101202, 0x12111001, 0x12111100, 0x12111101,
+    0x12111102, 0x12111201, 0x12121001, 0x12121100, 0x12121101, 0x12121202, 0x10101011, 0x10101012,
+    0x10101110, 0x10101111, 0x10101112, 0x10101211, 0x10111010, 0x10111011, 0x10111012, 0x10111110,
+    0x10111111, 0x10111112, 0x10111211, 0x10111212, 0x10121011, 0x10121110, 0x10121111, 0x10121112,
+    0x10121211, 0x11101010, 0x11101011, 0x11101012, 0x11101110, 0x11101111, 0x11101112, 0x11101210,
+    0x11101211, 0x11111010, 0x11111011, 0x11111012, 0x11111110, 0x11111111, 0x11111112, 0x11111210,
+    0x11111211, 0x11111212, 0x11121010, 0x11121011, 0x11121110, 0x11121111, 0x11121112, 0x11121210,
+    0x11121211, 0x11121212, 0x12101011, 0x12101110, 0x12101111, 0x12101211, 0x12101212, 0x12111010,
+    0x12111011, 0x12111110, 0x12111111, 0x12111112, 0x12111210, 0x12111211, 0x12121011, 0x12121110,
+    0x12121111, 0x12121112, 0x12121211, 0x10101020, 0x10101021, 0x10101022, 0x10101120, 0x10101122,
+    0x10101220, 0x10101221, 0x10111021, 0x10111120, 0x10111121, 0x10111220, 0x10111221, 0x10121020,
+    0x10121021, 0x10121022, 0x10121120, 0x10121121, 0x10121122, 0x10121220, 0x10121221, 0x11101021,
+    0x11101121, 0x11101122, 0x11101220, 0x11101221, 0x11101222, 0x11111020, 0x11111021, 0x11111022,
+    0x11111120, 0x11111121, 0x11111122, 0x11111220, 0x11111221, 0x11111222, 0x11121021, 0x11121120,
+    0x11121121, 0x11121221, 0x12101022, 0x12101121, 0x12101122, 0x12101220, 0x12101221, 0x12101222,
+    0x12111021, 0x12111121, 0x12111222, 0x12121022, 0x12121121, 0x12121122, 0x12121220, 0x12121221,
+    0x10102100, 0x10102101, 0x10102102, 0x10102201, 0x10112000, 0x10112101, 0x10112200, 0x10122001,
+    0x10122202, 0x11102101, 0x11102200, 0x11102202, 0x11112001, 0x11112100, 0x11112101, 0x11112102,
+    0x11112200, 0x11112201, 0x11122000, 0x11122002, 0x11122100, 0x11122101, 0x12102002, 0x12102201,
+    0x12112000, 0x12112002, 0x12112101, 0x12112200, 0x12122001, 0x12122201, 0x10102011, 0x10102012,
+    0x10102111, 0x10102212, 0x10112011, 0x10112110, 0x10112111, 0x10112112, 0x10112211, 0x10122111,
+    0x11102011, 0x11102110, 0x11102111, 0x11102112, 0x11102211, 0x11112010, 0x11112011, 0x11112012,
+    0x11112110, 0x11112111, 0x11112112, 0x11112210, 0x11112211, 0x11112212, 0x11122011, 0x11122110,
+    0x11122111, 0x11122112, 0x11122211, 0x12102011, 0x12102111, 0x12102211, 0x12112011, 0x12112110,
+    0x12112111, 0x12112112, 0x12112210, 0x12112211, 0x12122111, 0x10102120, 0x10102220, 0x10112121,
+    0x10112222, 0x10122020, 0x10122121, 0x10122122, 0x10122221, 0x11102121, 0x11102220, 0x11102221,
+    0x11112021, 0x11112121, 0x11112122, 0x11112220, 0x11112221, 0x11122022, 0x11122121, 0x11122220,
+    0x11122222, 0x12102021, 0x12102222, 0x12112022, 0x12112121, 0x12112122, 0x12112220, 0x12112222,
+    0x12122021, 0x10200101, 0x10210100, 0x10210102, 0x10210201, 0x10220101, 0x11200100, 0x11210000,
+    0x11210101, 0x11210102, 0x11210200, 0x11210202, 0x11220001, 0x11220100, 0x11220102, 0x11220201,
+    0x12200001, 0x12210102, 0x12220101, 0x10200011, 0x10200110, 0x10200112, 0x10200211, 0x10210012,
+    0x10210111, 0x10220011, 0x10220012, 0x10220112, 0x10220211, 0x11200111, 0x11200211, 0x11210011,
+    0x11210111, 0x11210112, 0x11210211, 0x11220111, 0x11220112, 0x11220212, 0x12200110, 0x12200212,
+    0x12210012, 0x12210111, 0x12220011, 0x12220112, 0x12220211, 0x10210021, 0x10210122, 0x10210221,
+    0x11200020, 0x11200021, 0x11200122, 0x11210121, 0x11210122, 0x11210220, 0x11220020, 0x12200121,
+    0x12210021, 0x12210122, 0x12220121, 0x10211001, 0x10211002, 0x10211101, 0x10211102, 0x10211202,
+    0x10221001, 0x10221102, 0x10221201, 0x11201000, 0x11201002, 0x11201101, 0x11201200, 0x11201202,
+    0x11211001, 0x11211100, 0x11211101, 0x11211102, 0x11211201, 0x11211202, 0x11221000, 0x11221002,
+    0x11221101, 0x12201100, 0x12201101, 0x12201201, 0x12211000, 0x12211002, 0x12211100, 0x12211101,
+    0x12211102, 0x12211200, 0x12211202, 0x12221001, 0x12221100, 0x12221201, 0x10201111, 0x10201210,
+    0x10201212, 0x10211011, 0x10211111, 0x10211112, 0x10211211, 0x11201110, 0x11201111, 0x11201112,
+    0x11201211, 0x11211010, 0x11211011, 0x11211110, 0x11211111, 0x11211112, 0x11211211, 0x11221011,
+    0x11221110, 0x11221111, 0x11221112, 0x11221211, 0x12201112, 0x12201211, 0x12201212, 0x12211011,
+    0x12211111, 0x12211112, 0x12211211, 0x12211212, 0x12221012, 0x12221111, 0x12221112, 0x12221210,
+    0x10201022, 0x10201221, 0x10211121, 0x10221020, 0x10221122, 0x10221220, 0x10221221, 0x11201020,
+    0x11201121, 0x11201220, 0x11201222, 0x11211021, 0x11211120, 0x11211121, 0x11211122, 0x11211220,
+    0x11211222, 0x11221020, 0x11221121, 0x11221220, 0x12201020, 0x12201022, 0x12201121, 0x12201222,
+    0x12211120, 0x12211122, 0x12211220, 0x12211221, 0x12221020, 0x12221120, 0x12221122, 0x12221222,
+    0x10212102, 0x10212201, 0x10222101, 0x11202001, 0x11212002, 0x11212101, 0x11212202, 0x11222001,
+    0x11222201, 0x12202101, 0x12212001, 0x12212200, 0x12222102, 0x10202011, 0x10202110, 0x10212010,
+    0x10212111, 0x10222011, 0x10222110, 0x10222112, 0x10222211, 0x11202010, 0x11202011, 0x11202111,
+    0x11202112, 0x11202210, 0x11212011, 0x11212110, 0x11212111, 0x11212112, 0x11212211, 0x11222010,
+    0x11222111, 0x11222212, 0x12202012, 0x12202110, 0x12202212, 0x12212111, 0x12222011, 0x12222110,
+    0x12222111, 0x12222211, 0x10212021, 0x10212122, 0x10212220, 0x11202021, 0x11202120, 0x11202221,
+    0x11212020, 0x11212121, 0x11212220, 0x11212222, 0x11222120, 0x11222121, 0x11222221, 0x12202122,
+    0x12212120, 0x12212220, 0x12212222, 0x12222122, 0x20000000, 0x20000002, 0x20000200, 0x20000202,
+    0x20020000, 0x20020002, 0x20020200, 0x20020202, 0x21000101, 0x21010000, 0x21010001, 0x21010100,
+    0x21010102, 0x21010201, 0x21020101, 0x22000000, 0x22000002, 0x22000200, 0x22000202, 0x22010101,
+    0x22020000, 0x22020002, 0x22020200, 0x22020202, 0x20000111, 0x20010011, 0x20010110, 0x20010112,
+    0x20010211, 0x20020111, 0x21000011, 0x21000110, 0x21000211, 0x21010010, 0x21010012, 0x21010111,
+    0x21010112, 0x21010210, 0x21010211, 0x21020110, 0x21020112, 0x21020211, 0x22000111, 0x22000211,
+    0x22010110, 0x22010112, 0x22010211, 0x22020111, 0x20000020, 0x20000022, 0x20000220, 0x20000222,
+    0x20010121, 0x20020020, 0x20020022, 0x20020220, 0x20020222, 0x21010021, 0x21010120, 0x21010221,
+    0x21020121, 0x22000020, 0x22000022, 0x22000220, 0x22000222, 0x22010121, 0x22020020, 0x22020022,
+    0x22020220, 0x22020222, 0x20011100, 0x20011201, 0x21001001, 0x21001100, 0x21011001, 0x21011101,
+    0x21011202, 0x21021001, 0x21021100, 0x21021201, 0x22011100, 0x22011201, 0x20001011, 0x20001211,
+    0x20011012, 0x20011111, 0x20011212, 0x20021112, 0x20021211, 0x21001010, 0x21001011, 0x21001111,
+    0x21001210, 0x21011011, 0x21011110, 0x21011111, 0x21011112, 0x21011211, 0x21011212, 0x21021111,
+    0x21021112, 0x21021210, 0x21021212, 0x22001011, 0x22001110, 0x22001112, 0x22001211, 0x22011010,
+    0x22011012, 0x22011111, 0x22011210, 0x22021112, 0x20011021, 0x20011122, 0x20011221, 0x20021121,
+    0x21001021, 0x21001120, 0x21001221, 0x21001222, 0x21011020, 0x21011121, 0x21011221, 0x21011222,
+    0x21021021, 0x21021122, 0x21021222, 0x22001121, 0x22011021, 0x22011222, 0x22021120, 0x20002000,
+    0x20002002, 0x20002200, 0x20002202, 0x20012101, 0x20022000, 0x20022002, 0x20022200, 0x20022202,
+    0x21002001, 0x21002101, 0x21012001, 0x21012100, 0x21012201, 0x21022101, 0x21022201, 0x22002000,
+    0x22002002, 0x22002200, 0x22002202, 0x22012101, 0x22022000, 0x22022002, 0x22022200, 0x22022202,
+    0x20002111, 0x20002112, 0x20012011, 0x20012110, 0x20012112, 0x20022111, 0x21002011, 0x21002110,
+    0x21002112, 0x21002211, 0x21012010, 0x21012012, 0x21012111, 0x21012212, 0x21022011, 0x21022110,
+    0x22002111, 0x22012112, 0x22012211, 0x22022111, 0x20002020, 0x20002022, 0x20002220, 0x20002222,
+    0x20012121, 0x20022020, 0x20022022, 0x20022220, 0x20022222, 0x21002121, 0x21012021, 0x21012120,
+    0x21012122, 0x22002020, 0x22002022, 0x22002220, 0x22002222, 0x22012121, 0x22022020, 0x22022022,
+    0x22022220, 0x22022222, 0x20100101, 0x20110001, 0x20110102, 0x20110200, 0x20110201, 0x20120101,
+    0x21100001, 0x21100102, 0x21100201, 0x21110101, 0x21110200, 0x21110202, 0x21120201, 0x21120202,
+    0x22100101, 0x22110001, 0x22110100, 0x22110102, 0x22110201, 0x22120101, 0x20100011, 0x20100110,
+    0x20100112, 0x20100211, 0x20110010, 0x20110111, 0x20110210, 0x20110212, 0x20120011, 0x20120110,
+    0x20120112, 0x20120211, 0x21100010, 0x21100111, 0x21110010, 0x21110011, 0x21110110, 0x21110111,
+    0x21110112, 0x21110211, 0x21120012, 0x21120111, 0x22100110, 0x22100112, 0x22110012, 0x22110111,
+    0x22110210, 0x22120011, 0x22120110, 0x22120112, 0x22120211, 0x20100121, 0x20110021, 0x20110120,
+    0x20110221, 0x20120121, 0x21100120, 0x21100122, 0x21100221, 0x21110020, 0x21110022, 0x21110121,
+    0x21110220, 0x21120122, 0x21120221, 0x22100121, 0x22110120, 0x22110122, 0x22120221, 0x20101001,
+    0x20101100, 0x20101102, 0x20111000, 0x20111101, 0x20111200, 0x20121102, 0x21101000, 0x21101202,
+    0x21111001, 0x21111100, 0x21111101, 0x21111102, 0x21111200, 0x21111201, 0x21121000, 0x21121001,
+    0x21121002, 0x21121101, 0x22101100, 0x22101102, 0x22111002, 0x22111100, 0x22111101, 0x22111200,
+    0x22121001, 0x22121201, 0x20101010, 0x20101111, 0x20101210, 0x20101212, 0x20111010, 0x20111011,
+    0x20111110, 0x20111111, 0x20111112, 0x20111211, 0x20121011, 0x20121111, 0x20121211, 0x20121212,
+    0x21101011, 0x21101110, 0x21101111, 0x21101112, 0x21101211, 0x21111010, 0x21111011, 0x21111012,
+    0x21111110, 0x21111111, 0x21111112, 0x21111210, 0x21111211, 0x21111212, 0x21121011, 0x21121110,
+    0x21121111, 0x21121112, 0x21121211, 0x22101011, 0x22101111, 0x22101210, 0x22111011, 0x22111012,
+    0x22111110, 0x22111111, 0x22111112, 0x22111211, 0x22111212, 0x22121010, 0x22121012, 0x22121111,
+    0x22121210, 0x22121212, 0x20101021, 0x20101120, 0x20111020, 0x20111121, 0x20111221, 0x20121020,
+    0x20121122, 0x20121221, 0x21101121, 0x21101220, 0x21101221, 0x21111021, 0x21111022, 0x21111121,
+    0x21111122, 0x21111221, 0x21121121, 0x21121220, 0x22101022, 0x22101120, 0x22101221, 0x22101222,
+    0x22111022, 0x22111120, 0x22111121, 0x22121120, 0x22121122, 0x22121221, 0x20102101, 0x20112102,
+    0x20112201, 0x20122101, 0x21102001, 0x21102102, 0x21112000, 0x21112002, 0x21112101, 0x21112102,
+    0x21112202, 0x21122100, 0x21122101, 0x22102101, 0x22112001, 0x22112102, 0x22112201, 0x22122101,
+    0x20102110, 0x20102112, 0x20102211, 0x20112010, 0x20112012, 0x20112111, 0x20112210, 0x20112212,
+    0x20122010, 0x20122011, 0x20122110, 0x20122112, 0x21102010, 0x21102012, 0x21102111, 0x21102210,
+    0x21102212, 0x21112011, 0x21112110, 0x21112111, 0x21112112, 0x21112211, 0x21122012, 0x21122111,
+    0x21122112, 0x21122212, 0x22102011, 0x22102110, 0x22112010, 0x22112012, 0x22112111, 0x22112212,
+    0x22122011, 0x22122112, 0x20102121, 0x20112121, 0x20122121, 0x21102120, 0x21102122, 0x21102221,
+    0x21112020, 0x21112121, 0x21112220, 0x21122021, 0x22102121, 0x22112021, 0x22112120, 0x22112121,
+    0x22112122, 0x20200000, 0x20200002, 0x20200200, 0x20200202, 0x20210101, 0x20220000, 0x20220002,
+    0x20220200, 0x20220202, 0x21200101, 0x21210001, 0x21210100, 0x21210102, 0x21210201, 0x22200000,
+    0x22200002, 0x22200200, 0x22200202, 0x22210101, 0x22220000, 0x22220002, 0x22220200, 0x22220202,
+    0x20200111, 0x20200211, 0x20210011, 0x20210110, 0x20210112, 0x20210211, 0x20210212, 0x21200112,
+    0x21200211, 0x21210011, 0x21210111, 0x21210210, 0x21210212, 0x21220011, 0x21220110, 0x22200111,
+    0x22210010, 0x22210012, 0x22210112, 0x22210211, 0x20200022, 0x20200220, 0x20200222, 0x20210020,
+    0x20210221, 0x20220022, 0x20220220, 0x20220222, 0x21200121, 0x21210021, 0x21210122, 0x21210221,
+    0x21220121, 0x22200020, 0x22200022, 0x22200220, 0x22200222, 0x22210121, 0x22220020, 0x22220022,
+    0x22220220, 0x22220222, 0x20211201, 0x20221101, 0x21201001, 0x21201100, 0x21211000, 0x21211100,
+    0x21211101, 0x21211200, 0x21211202, 0x21221001, 0x21221101, 0x21221102, 0x21221200, 0x21221201,
+    0x22201101, 0x20201112, 0x20201211, 0x20211010, 0x20211012, 0x20211111, 0x20211210, 0x20221112,
+    0x20221211, 0x21201012, 0x21201111, 0x21211011, 0x21211110, 0x21211111, 0x21211112, 0x21211211,
+    0x21221111, 0x21221212, 0x22201011, 0x22201110, 0x22201111, 0x22201112, 0x22201211, 0x22211012,
+    0x22211111, 0x22211210, 0x20201121, 0x20211021, 0x20211122, 0x20211222, 0x20221021, 0x20221121,
+    0x21201120, 0x21201122, 0x21201222, 0x21211022, 0x21211121, 0x21211122, 0x21211220, 0x21221020,
+    0x21221022, 0x22201122, 0x22211020, 0x22211121, 0x22211122, 0x22211221, 0x22221021, 0x22221120,
+    0x22221122, 0x20202000, 0x20202002, 0x20202200, 0x20202202, 0x20222000, 0x20222002, 0x20222200,
+    0x20222202, 0x21212001, 0x21212100, 0x21212102, 0x21212201, 0x22202000, 0x22202002, 0x22202200,
+    0x22202202, 0x22212101, 0x22222000, 0x22222002, 0x22222200, 0x22222202, 0x20202111, 0x20212110,
+    0x20212211, 0x20222011, 0x20222111, 0x21202011, 0x21212010, 0x21212111, 0x21212212, 0x21222011,
+    0x21222112, 0x21222211, 0x22212010, 0x22212112, 0x20202020, 0x20202022, 0x20202220, 0x20202222,
+    0x20222020, 0x20222022, 0x20222220, 0x20222222, 0x21212021, 0x21212120, 0x21212122, 0x22202020,
+    0x22202022, 0x22202220, 0x22202222, 0x22212121, 0x22222020, 0x22222022, 0x22222220, 0x22222222,
+GGML_TABLE_END()
+#endif
 
 #endif // GGML_COMMON_IMPL

ggml-cuda.cu

@@ -565,8 +565,8 @@ static_assert(sizeof(block_iq3_s) == sizeof(ggml_fp16_t) + 13*(QK_K/32) + IQ3S_N
 #define QI1_S (QK_K / (4*QR1_S))
 typedef struct {
     half d;
-    uint8_t qs[QK_K/8];
-    uint8_t scales[QK_K/16];
+    uint8_t  qs[QK_K/8];
+    uint16_t qh[QK_K/32];
 } block_iq1_s;
 static_assert(sizeof(block_iq1_s) == sizeof(ggml_fp16_t) + QK_K/8 + QK_K/16, "wrong iq1_s block size/padding");
 
@@ -1722,11 +1722,22 @@ static __global__ void dequantize_block_iq1_s(const void * __restrict__ vx, dst_
     const int il = tid/8; // 0...3
     const int ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
-    const int i8 = 4*ib+il;
-    uint8_t h = x[i].scales[i8/2] >> 4*(i8%2);
-    const int8_t * grid = (const int8_t *)(iq1s_grid + (x[i].qs[i8] | ((h & 8) << 5)));
-    const float d = (float)x[i].d * (2*(h & 7) + 1);
-    for (int j = 0; j < 8; ++j) y[j] = d * grid[j];
+    const float d = (float)x[i].d * (2*((x[i].qh[ib] >> 12) & 0xf) + 1);
+#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
+    int grid32[2]; const int8_t * q = (const int8_t *)grid32;
+    grid32[0] = *((const int *)(iq1s_grid_gpu + (x[i].qs[4*ib+il] | (((x[i].qh[ib] >> 3*il) & 7) << 8))));
+    grid32[1] = __vsub4((grid32[0] >>  4) & 0x0f0f0f0f, 0x01010101);
+    grid32[0] = __vsub4(grid32[0] & 0x0f0f0f0f, 0x01010101);
+    for (int j = 0; j < 8; ++j) {
+        y[j] = d * q[j];
+    }
+#else
+    const uint8_t * grid = (const uint8_t *)(iq1s_grid_gpu + (x[i].qs[4*ib+il] | (((x[i].qh[ib] >> 3*il) & 7) << 8)));
+    for (int j = 0; j < 4; ++j) {
+        y[j+0] = d * ((grid[j] & 0xf) - 1);
+        y[j+4] = d * ((grid[j] >>  4) - 1);
+    }
+#endif
 #else
     assert(false);
 #endif
@@ -4538,44 +4549,33 @@ static __device__ __forceinline__ float vec_dot_iq3_s_q8_1(
 #endif
 }
 
-
 static __device__ __forceinline__ float vec_dot_iq1_s_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
 #if QK_K == 256
     const block_iq1_s * bq1 = (const block_iq1_s *) vbq;
 
     const int ib32 = iqs;
-    int sumi1 = 0, sumi2 = 0, sumi3 = 0, sumi4 = 0;
-    const uint8_t h1 = bq1->scales[2*ib32+0];
-    const uint8_t h2 = bq1->scales[2*ib32+1];
+    int sumi = 0;
 #if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
     const int * q8 = (const int *)bq8_1[ib32].qs;
-    const int * grid1 = (const int *)(iq1s_grid + (bq1->qs[4*ib32+0] | ((h1 & 0x08) << 5)));
-    const int * grid2 = (const int *)(iq1s_grid + (bq1->qs[4*ib32+1] | ((h1 & 0x80) << 1)));
-    const int * grid3 = (const int *)(iq1s_grid + (bq1->qs[4*ib32+2] | ((h2 & 0x08) << 5)));
-    const int * grid4 = (const int *)(iq1s_grid + (bq1->qs[4*ib32+3] | ((h2 & 0x80) << 1)));
-    for (int j = 0; j < 2; ++j) {
-        sumi1 = __dp4a(q8[j+0], grid1[j], sumi1);
-        sumi2 = __dp4a(q8[j+2], grid2[j], sumi2);
-        sumi3 = __dp4a(q8[j+4], grid3[j], sumi3);
-        sumi4 = __dp4a(q8[j+6], grid4[j], sumi4);
+    for (int l = 0; l < 4; ++l) {
+        const int * grid = (const int *)(iq1s_grid_gpu + (bq1->qs[4*ib32+l] | (((bq1->qh[ib32] >> 3*l) & 7) << 8)));
+        int grid0 = __vsub4(grid[0] & 0x0f0f0f0f, 0x01010101);
+        int grid1 = __vsub4((grid[0] >> 4) & 0x0f0f0f0f, 0x01010101);
+        sumi = __dp4a(q8[2*l+1], grid1, __dp4a(q8[2*l+0], grid0, sumi));
     }
 #else
     const int8_t   * q8 = bq8_1[ib32].qs;
-    const int8_t * grid1 = (const int8_t *)(iq1s_grid + (bq1->qs[4*ib32+0] | ((h1 & 0x08) << 5)));
-    const int8_t * grid2 = (const int8_t *)(iq1s_grid + (bq1->qs[4*ib32+1] | ((h1 & 0x80) << 1)));
-    const int8_t * grid3 = (const int8_t *)(iq1s_grid + (bq1->qs[4*ib32+2] | ((h2 & 0x08) << 5)));
-    const int8_t * grid4 = (const int8_t *)(iq1s_grid + (bq1->qs[4*ib32+3] | ((h2 & 0x80) << 1)));
-    for (int j = 0; j < 8; ++j) {
-        sumi1 += q8[j+ 0] * grid1[j];
-        sumi2 += q8[j+ 8] * grid2[j];
-        sumi3 += q8[j+16] * grid3[j];
-        sumi4 += q8[j+24] * grid4[j];
+    for (int l = 0; l < 4; ++l) {
+        const uint8_t * grid = (const uint8_t *)(iq1s_grid_gpu + (bq1->qs[4*ib32+l] | (((bq1->qh[ib32] >> 3*l) & 7) << 8)));
+        for (int j = 0; j < 4; ++j) {
+            sumi += q8[j] * ((grid[j] & 0xf) - 1) + q8[j+4] * ((grid[j] >>  4) - 1);
+        }
+        q8 += 8;
     }
 #endif
     const float d = (float)bq1->d * __low2float(bq8_1[ib32].ds);
-    return d * (sumi1 * (2*(h1 & 7) + 1) + sumi2 * (2*((h1 >> 4) & 7) + 1) +
-                sumi3 * (2*(h2 & 7) + 1) + sumi4 * (2*((h2 >> 4) & 7) + 1));
+    return d * sumi * (2*(bq1->qh[ib32] >> 12) + 1);
 #else
     assert(false);
     return 0.f;

ggml-impl.h

@@ -53,26 +53,30 @@ extern "C" {
 //
 #include <arm_neon.h>
 
+typedef __fp16 ggml_fp16_internal_t;
+
 #define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
 #define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
 
 #define GGML_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
 
 static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
-    __fp16 tmp;
+    ggml_fp16_internal_t tmp;
     memcpy(&tmp, &h, sizeof(ggml_fp16_t));
     return (float)tmp;
 }
 
 static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
     ggml_fp16_t res;
-    __fp16 tmp = f;
+    ggml_fp16_internal_t tmp = f;
     memcpy(&res, &tmp, sizeof(ggml_fp16_t));
     return res;
 }
 
 #else
 
+typedef uint16_t ggml_fp16_internal_t;
+
 #ifdef __wasm_simd128__
 #include <wasm_simd128.h>
 #else

ggml-metal.m

@@ -1642,8 +1642,8 @@ static enum ggml_status ggml_metal_graph_compute(
                         // TODO: make this more general
                         GGML_ASSERT(n_as <= 8);
 
-                        // max size of the src1ids array in the kernel stack
-                        GGML_ASSERT(ne11 <= 512);
+                        // max size of the src1ids array in the kernel shared buffer
+                        GGML_ASSERT(ne11 <= 4096);
 
                         const int64_t  ne20 = src2 ? src2->ne[0] : 0;
                         const int64_t  ne21 = src2 ? src2->ne[1] : 0;
@@ -1741,7 +1741,7 @@ static enum ggml_status ggml_metal_graph_compute(
                                 [encoder setBuffer:id_src_cur offset:offs_src_cur atIndex:19 + j];
                             }
 
-                            [encoder setThreadgroupMemoryLength:8192 atIndex:0];
+                            [encoder setThreadgroupMemoryLength:GGML_PAD(8192 + 2*ne11, 16) atIndex:0];
 
                             [encoder dispatchThreadgroups:MTLSizeMake((ne11 + 31)/32, (ne21 + 63)/64, n_as*ne12*ne13) threadsPerThreadgroup:MTLSizeMake(128, 1, 1)];
                         } else {

ggml-metal.metal

@@ -2595,8 +2595,8 @@ typedef struct {
 
 typedef struct {
     half d;
-    uint8_t qs[QK_K/8];
-    uint8_t scales[QK_K/16];
+    uint8_t  qs[QK_K/8];
+    uint16_t qh[QK_K/32];
 } block_iq1_s;
 
 // Non-linear quants
@@ -4338,48 +4338,53 @@ void kernel_mul_mv_iq1_s_f32_impl(
     device const block_iq1_s * x = (device const block_iq1_s *) src0 + ib_row + offset0;
     device const float       * y = (device const float       *) src1 + r1*ne10 + im*ne00*ne1;
 
-    float yl[16];
+    float yl[32];
     float sumf[N_DST]={0.f}, all_sum;
 
     const int nb32 = nb * (QK_K / 32);
 
-    const int ix = tiisg/2;
-    const int il = tiisg%2;
+    const int ix = tiisg;
 
-    device const float * y4 = y + 32 * ix + 16 * il;
+    device const float * y4 = y + 32 * ix;
 
-    for (int ib32 = ix; ib32 < nb32; ib32 += 16) {
+    for (int ib32 = ix; ib32 < nb32; ib32 += 32) {
 
-        for (int i = 0; i < 16; ++i) {
+        float sumy = 0;
+        for (int i = 0; i < 32; ++i) {
             yl[i] = y4[i];
+            sumy += yl[i];
         }
 
         const int ibl = ib32 / (QK_K / 32);
         const int ib  = ib32 % (QK_K / 32);
 
         device const block_iq1_s * xr = x + ibl;
-        device const uint8_t * qs = xr->qs + 4 * ib + 2 * il;
-        device const uint8_t * sc = xr->scales + 2 * ib + il;
-        device const half    * dh = &xr->d;
+        device const uint8_t  * qs = xr->qs + 4 * ib;
+        device const uint16_t * qh = xr->qh + ib;
+        device const half     * dh = &xr->d;
 
         for (int row = 0; row < N_DST; row++) {
 
-            constant int8_t * grid1 = (constant int8_t *)(iq1s_grid + (qs[0] | ((sc[0] & 0x08) << 5)));
-            constant int8_t * grid2 = (constant int8_t *)(iq1s_grid + (qs[1] | ((sc[0] & 0x80) << 1)));
+            constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((qh[0] << 8) & 0x700)));
+            constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | ((qh[0] << 5) & 0x700)));
+            constant uint8_t * grid3 = (constant uint8_t *)(iq1s_grid_gpu + (qs[2] | ((qh[0] << 2) & 0x700)));
+            constant uint8_t * grid4 = (constant uint8_t *)(iq1s_grid_gpu + (qs[3] | ((qh[0] >> 1) & 0x700)));
 
-            float2 sum = {0};
-            for (int j = 0; j < 8; ++j) {
-                sum[0] += yl[j+ 0] * grid1[j];
-                sum[1] += yl[j+ 8] * grid2[j];
+            float sum = 0;
+            for (int j = 0; j < 4; ++j) {
+                sum += yl[j+ 0] * (grid1[j] & 0xf) + yl[j+ 4] * (grid1[j] >> 4)
+                     + yl[j+ 8] * (grid2[j] & 0xf) + yl[j+12] * (grid2[j] >> 4)
+                     + yl[j+16] * (grid3[j] & 0xf) + yl[j+20] * (grid3[j] >> 4)
+                     + yl[j+24] * (grid4[j] & 0xf) + yl[j+28] * (grid4[j] >> 4);
             }
-            sumf[row] += (float)dh[0] * (sum[0] * (2*(sc[0] & 7) + 1) + sum[1] * (2*((sc[0] >> 4) & 7) + 1));
+            sumf[row] += (float)dh[0] * (sum - sumy) * (2*(qh[0] >> 12) + 1);
 
             dh += nb*sizeof(block_iq1_s)/2;
             qs += nb*sizeof(block_iq1_s);
-            sc += nb*sizeof(block_iq1_s);
+            qh += nb*sizeof(block_iq1_s)/2;
         }
 
-        y4 += 16 * 32;
+        y4 += 32 * 32;
     }
 
     for (int row = 0; row < N_DST; ++row) {
@@ -5066,16 +5071,19 @@ void dequantize_iq2_s(device const block_iq2_s * xb, short il, thread type4x4 &
 template <typename type4x4>
 void dequantize_iq1_s(device const block_iq1_s * xb, short il, thread type4x4 & reg) {
     // il is 0...15 for QK_K = 256 => index of block of 32 is il/2
+    const int ib32 = il/2;
+    il = il%2;
     const float d = xb->d;
-    device const uint8_t * qs = xb->qs + 2*il;
-    device const uint8_t * sc = xb->scales + il;
-    const float dl1 = d * (2*(sc[0] & 7) + 1);
-    const float dl2 = d * (2*((sc[0] >> 4) & 7) + 1);
-    constant int8_t * grid1 = (constant int8_t *)(iq1s_grid + (qs[0] | ((sc[0] & 0x08) << 5)));
-    constant int8_t * grid2 = (constant int8_t *)(iq1s_grid + (qs[1] | ((sc[0] & 0x80) << 1)));
-    for (int i = 0; i < 8; ++i) {
-        reg[i/4+0][i%4] = dl1 * grid1[i];
-        reg[i/4+2][i%4] = dl2 * grid2[i];
+    device const uint8_t  * qs = xb->qs + 4*ib32 + 2*il;
+    device const uint16_t * qh = xb->qh;
+    const float dl = d * (2*(qh[ib32] >> 12) + 1);
+    constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | (((qh[ib32] >> (6*il+0)) & 7) << 8)));
+    constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | (((qh[ib32] >> (6*il+3)) & 7) << 8)));
+    for (int i = 0; i < 4; ++i) {
+        reg[0][i] = dl * (grid1[i] & 0xf) - dl;
+        reg[1][i] = dl * (grid1[i] >>  4) - dl;
+        reg[2][i] = dl * (grid2[i] & 0xf) - dl;
+        reg[3][i] = dl * (grid2[i] >>  4) - dl;
     }
 }
 
@@ -5386,7 +5394,7 @@ template<typename block_q, short nl, void (*dequantize_func)(device const block_
 void kernel_mul_mm_id_impl(
         device const  uchar * src0,
         device const  uchar * src1,
-        thread        short * src1ids,
+        threadgroup   short * src1ids,
         device        float * dst,
         constant    int64_t & ne00,
         constant    int64_t & ne02,
@@ -5589,9 +5597,9 @@ kernel void kernel_mul_mm_id(
     tgpig.z = tgpig.z%(ne12*ne13);
 
     // row indices of src1 for expert id
-    int64_t _ne1 = 0;
-    short src1ids[512];
+    threadgroup short * src1ids = (threadgroup short *)(shared_memory + 8192);
 
+    int64_t _ne1 = 0;
     for (int64_t i1 = 0; i1 < ne1; i1++) {
         if (((device int32_t *) (ids + i1*nbi1))[idx] == id) {
             src1ids[_ne1++] = i1;

ggml-quants.h

@@ -217,8 +217,8 @@ static_assert(sizeof(block_iq3_s) == sizeof(ggml_fp16_t) + 13*(QK_K/32) + IQ3S_N
 
 typedef struct {
     ggml_fp16_t d;
-    uint8_t qs[QK_K/8];
-    uint8_t scales[QK_K/16];
+    uint8_t  qs[QK_K/8];
+    uint16_t qh[QK_K/32];
 } block_iq1_s;
 static_assert(sizeof(block_iq1_s) == sizeof(ggml_fp16_t) + QK_K/8 + QK_K/16, "wrong iq1_s block size/padding");
 
@@ -261,6 +261,7 @@ void quantize_row_q4_K_reference(const float * GGML_RESTRICT x, block_q4_K * GGM
 void quantize_row_q5_K_reference(const float * GGML_RESTRICT x, block_q5_K * GGML_RESTRICT y, int k);
 void quantize_row_q6_K_reference(const float * GGML_RESTRICT x, block_q6_K * GGML_RESTRICT y, int k);
 void quantize_row_q8_K_reference(const float * GGML_RESTRICT x, block_q8_K * GGML_RESTRICT y, int k);
+
 void quantize_row_iq3_xxs_reference(const float * GGML_RESTRICT x, block_iq3_xxs * GGML_RESTRICT y, int k);
 void quantize_row_iq4_nl_reference (const float * GGML_RESTRICT x, block_iq4_nl  * GGML_RESTRICT y, int k);
 void quantize_row_iq4_xs_reference (const float * GGML_RESTRICT x, block_iq4_xs  * GGML_RESTRICT y, int k);
@@ -280,6 +281,7 @@ void quantize_row_q4_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, in
 void quantize_row_q5_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
 void quantize_row_q6_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
 void quantize_row_q8_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
+
 void quantize_row_iq3_xxs(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
 void quantize_row_iq4_nl (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
 void quantize_row_iq4_xs (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
@@ -300,6 +302,7 @@ void dequantize_row_q4_K(const block_q4_K * GGML_RESTRICT x, float * GGML_RESTRI
 void dequantize_row_q5_K(const block_q5_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
 void dequantize_row_q6_K(const block_q6_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
 void dequantize_row_q8_K(const block_q8_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
+
 void dequantize_row_iq2_xxs(const block_iq2_xxs * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
 void dequantize_row_iq2_xs (const block_iq2_xs  * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
 void dequantize_row_iq2_s  (const block_iq2_s   * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
@@ -321,6 +324,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
 void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
 void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
 void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
+
 void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
 void ggml_vec_dot_iq2_xs_q8_K (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
 void ggml_vec_dot_iq2_s_q8_K  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
@@ -330,26 +334,26 @@ void ggml_vec_dot_iq4_nl_q8_0 (int n, float * GGML_RESTRICT s, size_t bs, const
 void ggml_vec_dot_iq4_xs_q8_K (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
 void ggml_vec_dot_iq3_s_q8_K  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
 
-//
 // Quantization utilizing an importance matrix (a.k.a. "Activation aWare Quantization")
-//
-size_t quantize_iq2_xxs(const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_iq2_xs (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_iq2_s  (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_iq3_xxs(const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_iq1_s  (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_iq4_nl (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_iq4_xs (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_iq3_s  (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_q2_K   (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_q3_K   (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_q4_K   (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_q5_K   (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_q6_K   (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_q4_0   (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_q4_1   (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_q5_0   (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
-size_t quantize_q5_1   (const float * src, void * dst, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
+size_t quantize_iq2_xxs(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_iq2_xs (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_iq2_s  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_iq3_xxs(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_iq1_s  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_iq4_nl (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_iq4_xs (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_iq3_s  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+
+size_t quantize_q2_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_q3_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_q4_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_q5_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_q6_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_q4_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_q4_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_q5_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_q5_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_q8_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
 
 void iq2xs_init_impl(enum ggml_type type);
 void iq2xs_free_impl(enum ggml_type type);

ggml-sycl.cpp

@@ -3494,6 +3494,31 @@ typedef struct dpct_type_block_iq3_xxs {
 } block_iq3_xxs;
 static_assert(sizeof(block_iq3_xxs) == sizeof(ggml_fp16_t) + 3*(QK_K/8), "wrong iq3_xxs block size/padding");
 
+#define QR3_XS 8
+#define QI3_XS (QK_K / (4*QR3_XS))
+#if QK_K == 64
+#define IQ3S_N_SCALE 2
+#else
+#define IQ3S_N_SCALE QK_K/64
+#endif
+typedef struct {
+    sycl::half d;
+    uint8_t qs[QK_K/4];
+    uint8_t qh[QK_K/32];
+    uint8_t signs[QK_K/8];
+    uint8_t scales[IQ3S_N_SCALE];
+} block_iq3_s;
+static_assert(sizeof(block_iq3_s) == sizeof(ggml_fp16_t) + 13*(QK_K/32) + IQ3S_N_SCALE, "wrong iq3_s block size/padding");
+
+#define QR1_S 8
+#define QI1_S (QK_K / (4*QR1_S))
+typedef struct {
+    sycl::half d;
+    uint8_t qs[QK_K/8];
+    uint8_t scales[QK_K/16];
+} block_iq1_s;
+static_assert(sizeof(block_iq1_s) == sizeof(ggml_fp16_t) + QK_K/8 + QK_K/16, "wrong iq1_s block size/padding");
+
 #define WARP_SIZE 32
 #define MATRIX_ROW_PADDING 512 // last row of quant. matrices is a multiple of this to avoid out-of-bounds memory accesses
 
@@ -4833,6 +4858,62 @@ static void dequantize_block_iq3_xxs(const void * __restrict__ vx, dst_t * __res
 
 }
 
+template<typename dst_t>
+static void dequantize_block_iq3_s(const void * __restrict__ vx, dst_t * __restrict__ yy,
+                                     const sycl::nd_item<3> &item_ct1,
+                                     const uint32_t *iq3s_grid,
+                                     const uint8_t *ksigns_iq2xs,
+                                     const uint8_t *kmask_iq2xs) {
+
+    const int i = item_ct1.get_group(2);
+    const block_iq3_s * x = (const block_iq3_s  *) vx;
+
+    const int tid = item_ct1.get_local_id(2);
+#if QK_K == 256
+    const int il = tid/8; // 0...3
+    const int ib = tid%8; // 0...7
+    dst_t * y = yy + i*QK_K + 32*ib + 8*il;
+    const uint8_t  * qs = x[i].qs + 8*ib;
+    const uint8_t  * grid1 = (const uint8_t *)(iq3s_grid + qs[2*il+0]);
+    const uint8_t  * grid2 = (const uint8_t *)(iq3s_grid + qs[2*il+1]);
+    const float d = (float)x[i].d * (1 + 2*((x[i].scales[ib/2] >> 4*(ib%2)) & 0xf));
+    const uint8_t signs = x[i].signs[4*ib + il];
+    for (int j = 0; j < 4; ++j) {
+        y[j+0] = d * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f);
+        y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f);
+    }
+#else
+    assert(false);
+#endif
+
+}
+
+template<typename dst_t>
+static void dequantize_block_iq1_s(const void * __restrict__ vx, dst_t * __restrict__ yy,
+                                     const sycl::nd_item<3> &item_ct1,
+                                     const uint64_t *iq1s_grid,
+                                     const uint8_t *ksigns_iq2xs,
+                                     const uint8_t *kmask_iq2xs) {
+
+    const int i = item_ct1.get_group(2);
+    const block_iq1_s * x = (const block_iq1_s  *) vx;
+
+    const int tid = item_ct1.get_local_id(2);
+#if QK_K == 256
+    const int il = tid/8; // 0...3
+    const int ib = tid%8; // 0...7
+    dst_t * y = yy + i*QK_K + 32*ib + 8*il;
+    const int i8 = 4*ib+il;
+    uint8_t h = x[i].scales[i8/2] >> 4*(i8%2);
+    const int8_t * grid = (const int8_t *)(iq1s_grid + (x[i].qs[i8] | ((h & 8) << 5)));
+    const float d = (float)x[i].d * (2*(h & 7) + 1);
+    for (int j = 0; j < 8; ++j) y[j] = d * grid[j];
+#else
+    assert(false);
+#endif
+
+}
+
 /*
 DPCT1110:4: The total declared local variable size in device function
 dequantize_mul_mat_vec_q2_k exceeds 128 bytes and may cause high register
@@ -7679,6 +7760,76 @@ vec_dot_iq3_xxs_q8_1(const void *__restrict__ vbq,
 #endif
 }
 
+static __dpct_inline__ float
+vec_dot_iq3_s_q8_1(const void *__restrict__ vbq,
+                     const block_q8_1 *__restrict__ bq8_1, const int &iqs,
+                     const uint32_t *iq3s_grid, const uint64_t *ksigns64) {
+#if DPCT_COMPATIBILITY_TEMP >=                                                 \
+    MIN_CC_DP4A // lowest compute capability for integer intrinsics
+#if QK_K == 256
+    const block_iq3_s * bq2 = (const block_iq3_s *) vbq;
+
+    const int ib32 = iqs;
+    const uint8_t  * qs = bq2->qs + 8*ib32;
+    const int8_t   * q8 = bq8_1[ib32].qs;
+    int sumi = 0;
+    for (int l = 0; l < 4; ++l) {
+        const uint32_t * grid1 = iq3s_grid + (qs[2*l+0] | ((bq2->qh[ib32] << (8 - 2*l)) & 256));
+        const uint32_t * grid2 = iq3s_grid + (qs[2*l+1] | ((bq2->qh[ib32] << (7 - 2*l)) & 256));
+        uint32_t signs0 = dpct::vectorized_binary<sycl::uchar4>(
+            ((bq2->signs[4*ib32+l] & 0xf) * 0x01010101) & 0x08040201, 0x08040201, std::equal_to<>());
+        uint32_t signs1 = dpct::vectorized_binary<sycl::uchar4>(
+            ((bq2->signs[4*ib32+l] >>  4) * 0x01010101) & 0x08040201, 0x08040201, std::equal_to<>());
+        const int grid_l = dpct::vectorized_binary<sycl::uchar4>(
+            grid1[0] ^ signs0, signs0, std::minus<>());
+        const int grid_h = dpct::vectorized_binary<sycl::uchar4>(
+            grid2[0] ^ signs1, signs1, std::minus<>());
+        sumi = dpct::dp4a(grid_l, *((int *)q8 + 0), sumi);
+        sumi = dpct::dp4a(grid_h, *((int *)q8 + 1), sumi);
+        q8 += 8;
+    }
+    const float d = (float)bq2->d * (1 + 2*((bq2->scales[ib32/2] >> 4*(ib32%2)) & 0xf)) * bq8_1[ib32].ds[0];
+    return d * sumi;
+#else
+    assert(false);
+    return 0.f;
+#endif
+#else
+    assert(false);
+    return 0.f;
+#endif
+}
+
+static __dpct_inline__ float
+vec_dot_iq1_s_q8_1(const void *__restrict__ vbq,
+                     const block_q8_1 *__restrict__ bq8_1, const int &iqs,
+                     const uint64_t *iq1s_grid, const uint64_t *ksigns64) {
+#if QK_K == 256
+    const block_iq1_s * bq1 = (const block_iq1_s *) vbq;
+
+    const int ib32 = iqs;
+    int sumi1 = 0, sumi2 = 0, sumi3 = 0, sumi4 = 0;
+    const uint8_t h1 = bq1->scales[2*ib32+0];
+    const uint8_t h2 = bq1->scales[2*ib32+1];
+    const int * q8 = (const int *)bq8_1[ib32].qs;
+    const int * grid1 = (const int *)(iq1s_grid + (bq1->qs[4*ib32+0] | ((h1 & 0x08) << 5)));
+    const int * grid2 = (const int *)(iq1s_grid + (bq1->qs[4*ib32+1] | ((h1 & 0x80) << 1)));
+    const int * grid3 = (const int *)(iq1s_grid + (bq1->qs[4*ib32+2] | ((h2 & 0x08) << 5)));
+    const int * grid4 = (const int *)(iq1s_grid + (bq1->qs[4*ib32+3] | ((h2 & 0x80) << 1)));
+    for (int j = 0; j < 2; ++j) {
+        sumi1 = dpct::dp4a(q8[j+0], grid1[j], sumi1);
+        sumi2 = dpct::dp4a(q8[j+2], grid2[j], sumi2);
+        sumi3 = dpct::dp4a(q8[j+4], grid3[j], sumi3);
+        sumi4 = dpct::dp4a(q8[j+6], grid4[j], sumi4);
+    }
+    const float d = (float)bq1->d  * bq8_1[ib32].ds[0];
+    return d * (sumi1 * (2*(h1 & 7) + 1) + sumi2 * (2*((h1 >> 4) & 7) + 1) +
+                sumi3 * (2*(h2 & 7) + 1) + sumi4 * (2*((h2 >> 4) & 7) + 1));
+#else
+    assert(false);
+    return 0.f;
+#endif
+}
 
 template <int qk, int qr, int qi, bool need_sum, typename block_q_t, int mmq_x,
           int mmq_y, int nwarps, load_tiles_sycl_t load_tiles, int vdr,
@@ -8444,6 +8595,98 @@ static void mul_mat_vec_q_iq3_xxs_q8_1(const void * __restrict__ vx, const void
     }
 }
 
+template <int qk, int qi, typename block_q_t, int vdr>
+static void mul_mat_vec_q_iq3_s_q8_1(const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst, const int ncols, const int nrows,
+                          const sycl::nd_item<3> &item_ct1,
+                          const uint32_t *iq3s_grid_ptr, const uint64_t *ksigns64_ptr ) {
+    const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) +
+                    item_ct1.get_local_id(1);
+
+    if (row >= nrows) {
+        return;
+    }
+
+    const int blocks_per_row = ncols / qk;
+    const int blocks_per_warp = vdr * WARP_SIZE / qi;
+
+// partial sum for each thread
+    float tmp = 0.0f;
+
+    const block_q_t  * x = (const block_q_t  *) vx;
+    const block_q8_1 * y = (const block_q8_1 *) vy;
+
+    for (int i = item_ct1.get_local_id(2) / (qi / vdr); i < blocks_per_row;
+         i += blocks_per_warp) {
+        const int ibx = row*blocks_per_row + i; // x block index
+
+        const int iby = i * (qk/QK8_1); // y block index that aligns with ibx
+
+        const int iqs =
+            vdr *
+            (item_ct1.get_local_id(2) %
+             (qi / vdr)); // x block quant index when casting the quants to int
+
+        tmp += vec_dot_iq3_s_q8_1(&x[ibx], &y[iby], iqs, iq3s_grid_ptr, ksigns64_ptr);
+    }
+
+    // sum up partial sums and write back result
+#pragma unroll
+    for (int mask = 16; mask > 0; mask >>= 1) {
+        tmp +=
+            dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
+    }
+
+    if (item_ct1.get_local_id(2) == 0) {
+        dst[row] = tmp;
+    }
+}
+
+template <int qk, int qi, typename block_q_t, int vdr>
+static void mul_mat_vec_q_iq1_s_q8_1(const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst, const int ncols, const int nrows,
+                          const sycl::nd_item<3> &item_ct1,
+                          const uint64_t *iq1s_grid_ptr, const uint64_t *ksigns64_ptr ) {
+    const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) +
+                    item_ct1.get_local_id(1);
+
+    if (row >= nrows) {
+        return;
+    }
+
+    const int blocks_per_row = ncols / qk;
+    const int blocks_per_warp = vdr * WARP_SIZE / qi;
+
+// partial sum for each thread
+    float tmp = 0.0f;
+
+    const block_q_t  * x = (const block_q_t  *) vx;
+    const block_q8_1 * y = (const block_q8_1 *) vy;
+
+    for (int i = item_ct1.get_local_id(2) / (qi / vdr); i < blocks_per_row;
+         i += blocks_per_warp) {
+        const int ibx = row*blocks_per_row + i; // x block index
+
+        const int iby = i * (qk/QK8_1); // y block index that aligns with ibx
+
+        const int iqs =
+            vdr *
+            (item_ct1.get_local_id(2) %
+             (qi / vdr)); // x block quant index when casting the quants to int
+
+        tmp += vec_dot_iq1_s_q8_1(&x[ibx], &y[iby], iqs, iq1s_grid_ptr, ksigns64_ptr);
+    }
+
+    // sum up partial sums and write back result
+#pragma unroll
+    for (int mask = 16; mask > 0; mask >>= 1) {
+        tmp +=
+            dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
+    }
+
+    if (item_ct1.get_local_id(2) == 0) {
+        dst[row] = tmp;
+    }
+}
+
 template <int qk, int qr, dequantize_kernel_t dequantize_kernel>
 static void dequantize_mul_mat_vec(const void * __restrict__ vx, const dfloat * __restrict__ y, float * __restrict__ dst, const int ncols, const int nrows,
                                    const sycl::nd_item<3> &item_ct1) {
@@ -10129,6 +10372,64 @@ static void dequantize_row_iq3_xxs_sycl(const void *vx, dst_t *y, const int k,
     }
 }
 
+template <typename dst_t>
+static void dequantize_row_iq3_s_sycl(const void *vx, dst_t *y, const int k,
+                                        dpct::queue_ptr stream) {
+    const int nb = k / QK_K;
+    {
+        iq3s_grid.init(*stream);
+        ksigns_iq2xs.init(*stream);
+        kmask_iq2xs.init(*stream);
+
+        dpct::has_capability_or_fail(stream->get_device(),
+                                     {sycl::aspect::fp16});
+
+        stream->submit([&](sycl::handler &cgh) {
+            auto iq3s_grid_ptr_ct1 = iq3s_grid.get_ptr();
+            auto ksigns_iq2xs_ptr_ct1 = ksigns_iq2xs.get_ptr();
+            auto kmask_iq2xs_ptr_ct1 = kmask_iq2xs.get_ptr();
+
+            cgh.parallel_for(sycl::nd_range<3>(sycl::range<3>(1, 1, nb) *
+                                                   sycl::range<3>(1, 1, 32),
+                                               sycl::range<3>(1, 1, 32)),
+                             [=](sycl::nd_item<3> item_ct1) {
+                                 dequantize_block_iq3_s(
+                                     vx, y, item_ct1, iq3s_grid_ptr_ct1,
+                                     ksigns_iq2xs_ptr_ct1, kmask_iq2xs_ptr_ct1);
+                             });
+        });
+    }
+}
+
+template <typename dst_t>
+static void dequantize_row_iq1_s_sycl(const void *vx, dst_t *y, const int k,
+                                        dpct::queue_ptr stream) {
+    const int nb = k / QK_K;
+    {
+        iq1s_grid.init(*stream);
+        ksigns_iq2xs.init(*stream);
+        kmask_iq2xs.init(*stream);
+
+        dpct::has_capability_or_fail(stream->get_device(),
+                                     {sycl::aspect::fp16});
+
+        stream->submit([&](sycl::handler &cgh) {
+            auto iq1s_grid_ptr_ct1 = iq1s_grid.get_ptr();
+            auto ksigns_iq2xs_ptr_ct1 = ksigns_iq2xs.get_ptr();
+            auto kmask_iq2xs_ptr_ct1 = kmask_iq2xs.get_ptr();
+
+            cgh.parallel_for(sycl::nd_range<3>(sycl::range<3>(1, 1, nb) *
+                                                   sycl::range<3>(1, 1, 32),
+                                               sycl::range<3>(1, 1, 32)),
+                             [=](sycl::nd_item<3> item_ct1) {
+                                 dequantize_block_iq1_s(
+                                     vx, y, item_ct1, iq1s_grid_ptr_ct1,
+                                     ksigns_iq2xs_ptr_ct1, kmask_iq2xs_ptr_ct1);
+                             });
+        });
+    }
+}
+
 template <typename src_t, typename dst_t>
 static void convert_unary_sycl(const void *__restrict__ vx,
                                dst_t *__restrict__ y, const int k,
@@ -10179,6 +10480,10 @@ static to_fp16_sycl_t ggml_get_to_fp16_sycl(ggml_type type) try {
             return dequantize_row_iq2_xs_sycl;
         case GGML_TYPE_IQ3_XXS:
             return dequantize_row_iq3_xxs_sycl;
+        case GGML_TYPE_IQ3_S:
+            return dequantize_row_iq3_s_sycl;
+        case GGML_TYPE_IQ1_S:
+            return dequantize_row_iq1_s_sycl;
         case GGML_TYPE_F32:
             return convert_unary_sycl<float>;
         default:
@@ -10219,6 +10524,10 @@ static to_fp32_sycl_t ggml_get_to_fp32_sycl(ggml_type type) {
             return dequantize_row_iq2_xs_sycl;
         case GGML_TYPE_IQ3_XXS:
             return dequantize_row_iq3_xxs_sycl;
+        case GGML_TYPE_IQ3_S:
+            return dequantize_row_iq3_s_sycl;
+        case GGML_TYPE_IQ1_S:
+            return dequantize_row_iq1_s_sycl;
         case GGML_TYPE_F16:
             return convert_unary_sycl<sycl::half>;
         default:
@@ -10808,6 +11117,61 @@ static void mul_mat_vec_iq3_xxs_q8_1_sycl(const void *vx, const void *vy,
     }
 }
 
+static void mul_mat_vec_iq3_s_q8_1_sycl(const void *vx, const void *vy,
+                                          float *dst, const int ncols,
+                                          const int nrows,
+                                          dpct::queue_ptr stream) {
+    GGML_ASSERT(ncols % QK_K == 0);
+    const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y;
+    const sycl::range<3> block_nums(1, 1, block_num_y);
+    const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
+    {
+        iq3s_grid.init(*stream);
+        ksigns64.init(*stream);
+
+        stream->submit([&](sycl::handler &cgh) {
+            auto iq3s_grid_ptr_ct1 = iq3s_grid.get_ptr();
+            auto ksigns64_ptr_ct1 = ksigns64.get_ptr();
+
+            cgh.parallel_for(
+                sycl::nd_range<3>(block_nums * block_dims, block_dims),
+                [=](sycl::nd_item<3> item_ct1)
+                    [[intel::reqd_sub_group_size(32)]] {
+                        mul_mat_vec_q_iq3_s_q8_1<QK_K, QI3_XS, block_iq3_s, 1>(
+                            vx, vy, dst, ncols, nrows, item_ct1,
+                            iq3s_grid_ptr_ct1, ksigns64_ptr_ct1);
+                    });
+        });
+    }
+}
+
+static void mul_mat_vec_iq1_s_q8_1_sycl(const void *vx, const void *vy,
+                                          float *dst, const int ncols,
+                                          const int nrows,
+                                          dpct::queue_ptr stream) {
+    GGML_ASSERT(ncols % QK_K == 0);
+    const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y;
+    const sycl::range<3> block_nums(1, 1, block_num_y);
+    const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
+    {
+        iq1s_grid.init(*stream);
+        ksigns64.init(*stream);
+
+        stream->submit([&](sycl::handler &cgh) {
+            auto iq1s_grid_ptr_ct1 = iq1s_grid.get_ptr();
+            auto ksigns64_ptr_ct1 = ksigns64.get_ptr();
+
+            cgh.parallel_for(
+                sycl::nd_range<3>(block_nums * block_dims, block_dims),
+                [=](sycl::nd_item<3> item_ct1)
+                    [[intel::reqd_sub_group_size(32)]] {
+                        mul_mat_vec_q_iq1_s_q8_1<QK_K, QI1_S, block_iq1_s, 1>(
+                            vx, vy, dst, ncols, nrows, item_ct1,
+                            iq1s_grid_ptr_ct1, ksigns64_ptr_ct1);
+                    });
+        });
+    }
+}
 
 static void ggml_mul_mat_q4_0_q8_1_sycl(const void *vx, const void *vy,
                                         float *dst, const int ncols_x,
@@ -13556,8 +13920,11 @@ static int64_t get_row_rounding(ggml_type type, const std::array<float, GGML_SYC
         case GGML_TYPE_Q5_K:
         case GGML_TYPE_IQ2_XXS:
         case GGML_TYPE_IQ2_XS:
+        case GGML_TYPE_IQ1_S:
         case GGML_TYPE_IQ3_XXS:
             return max_compute_capability >= VER_GEN9 ? 128 : 64;
+        case GGML_TYPE_IQ3_S:
+            return max_compute_capability >= VER_GEN9 ? 128 : 64;
         case GGML_TYPE_Q6_K:
             return 64;
         default:
@@ -13618,6 +13985,12 @@ inline void ggml_sycl_op_mul_mat_vec_q(
         case GGML_TYPE_IQ3_XXS:
             mul_mat_vec_iq3_xxs_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
             break;
+        case GGML_TYPE_IQ3_S:
+            mul_mat_vec_iq3_s_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            break;
+        case GGML_TYPE_IQ1_S:
+            mul_mat_vec_iq1_s_q8_1_sycl(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stream);
+            break;
         default:
             GGML_ASSERT(false);
             break;
@@ -16963,9 +17336,8 @@ GGML_CALL static bool ggml_backend_sycl_supports_op(ggml_backend_t backend, cons
                     return false;
                 }
                 ggml_type a_type = a->type;
-                if (a_type == GGML_TYPE_IQ2_XXS || a_type == GGML_TYPE_IQ2_XS || a_type == GGML_TYPE_IQ3_XXS ||
-                    a_type == GGML_TYPE_IQ1_S   || a_type == GGML_TYPE_IQ4_NL || a_type == GGML_TYPE_IQ3_S   ||
-                    a_type == GGML_TYPE_IQ2_S   || a_type == GGML_TYPE_IQ4_XS) {
+                if (a_type == GGML_TYPE_IQ4_NL || a_type == GGML_TYPE_IQ2_S ||
+                    a_type == GGML_TYPE_IQ4_XS) {
                     return false;
                 }
                 return true;

ggml-vulkan.cpp

@@ -4102,45 +4102,7 @@ static void ggml_vk_test_transfer(ggml_backend_vk_context * ctx, size_t ne, bool
 }
 
 static void ggml_vk_quantize_data(const float * from, void * to, size_t ne, ggml_type quant) {
-    std::vector<int64_t> hist_cur(1 << 4, 0);
-
-    switch(quant) {
-    case GGML_TYPE_F32:
-        memcpy(to, from, sizeof(float) * ne);
-        break;
-    case GGML_TYPE_Q4_0:
-        ggml_quantize_q4_0(from, to, ne, ne, hist_cur.data());
-        break;
-    case GGML_TYPE_Q4_1:
-        ggml_quantize_q4_1(from, to, ne, ne, hist_cur.data());
-        break;
-    case GGML_TYPE_Q5_0:
-        ggml_quantize_q5_0(from, to, ne, ne, hist_cur.data());
-        break;
-    case GGML_TYPE_Q5_1:
-        ggml_quantize_q5_1(from, to, ne, ne, hist_cur.data());
-        break;
-    case GGML_TYPE_Q8_0:
-        ggml_quantize_q8_0(from, to, ne, ne, hist_cur.data());
-        break;
-    case GGML_TYPE_Q2_K:
-        ggml_quantize_q2_K(from, to, ne, ne, hist_cur.data());
-        break;
-    case GGML_TYPE_Q3_K:
-        ggml_quantize_q3_K(from, to, ne, ne, hist_cur.data());
-        break;
-    case GGML_TYPE_Q4_K:
-        ggml_quantize_q4_K(from, to, ne, ne, hist_cur.data());
-        break;
-    case GGML_TYPE_Q5_K:
-        ggml_quantize_q5_K(from, to, ne, ne, hist_cur.data());
-        break;
-    case GGML_TYPE_Q6_K:
-        ggml_quantize_q6_K(from, to, ne, ne, hist_cur.data());
-        break;
-    default:
-        GGML_ASSERT(false);
-    }
+    ggml_quantize_chunk(quant, from, to, 0, 1, ne, nullptr);
 }
 
 static void ggml_vk_test_dequant(ggml_backend_vk_context * ctx, size_t ne, ggml_type quant) {

ggml.c

@@ -857,7 +857,7 @@ inline static float vaddvq_f32(float32x4_t v) {
     #define GGML_F16x8              float16x8_t
     #define GGML_F16x8_ZERO         vdupq_n_f16(0.0f)
     #define GGML_F16x8_SET1(x)      vdupq_n_f16(x)
-    #define GGML_F16x8_LOAD(x)      vld1q_f16((const __fp16 *)(x))
+    #define GGML_F16x8_LOAD(x)      vld1q_f16((const ggml_fp16_internal_t *)(x))
     #define GGML_F16x8_STORE        vst1q_f16
     #define GGML_F16x8_FMA(a, b, c) vfmaq_f16(a, b, c)
     #define GGML_F16x8_ADD          vaddq_f16
@@ -900,7 +900,7 @@ inline static float vaddvq_f32(float32x4_t v) {
     #define GGML_F32Cx4              float32x4_t
     #define GGML_F32Cx4_ZERO         vdupq_n_f32(0.0f)
     #define GGML_F32Cx4_SET1(x)      vdupq_n_f32(x)
-    #define GGML_F32Cx4_LOAD(x)      vcvt_f32_f16(vld1_f16((const __fp16 *)(x)))
+    #define GGML_F32Cx4_LOAD(x)      vcvt_f32_f16(vld1_f16((const ggml_fp16_internal_t *)(x)))
     #define GGML_F32Cx4_STORE(x, y)  vst1_f16(x, vcvt_f16_f32(y))
     #define GGML_F32Cx4_FMA(a, b, c) vfmaq_f32(a, b, c)
     #define GGML_F32Cx4_ADD          vaddq_f32
@@ -20159,133 +20159,6 @@ void ggml_quantize_free(void) {
     ggml_critical_section_end();
 }
 
-size_t ggml_quantize_q4_0(const float * src, void * dst, int n, int k, int64_t * hist) {
-    assert(k % QK4_0 == 0);
-    const int nb = k / QK4_0;
-
-    for (int b = 0; b < n; b += k) {
-        block_q4_0 * restrict y = (block_q4_0 *) dst + b/QK4_0;
-
-        quantize_row_q4_0_reference(src + b, y, k);
-
-        for (int i = 0; i < nb; i++) {
-            for (int j = 0; j < QK4_0; j += 2) {
-                const uint8_t vi0 = y[i].qs[j/2] & 0x0F;
-                const uint8_t vi1 = y[i].qs[j/2] >> 4;
-
-                hist[vi0]++;
-                hist[vi1]++;
-            }
-        }
-    }
-
-    return (n/QK4_0*sizeof(block_q4_0));
-}
-
-size_t ggml_quantize_q4_1(const float * src, void * dst, int n, int k, int64_t * hist) {
-    assert(k % QK4_1 == 0);
-    const int nb = k / QK4_1;
-
-    for (int b = 0; b < n; b += k) {
-        block_q4_1 * restrict y = (block_q4_1 *) dst + b/QK4_1;
-
-        quantize_row_q4_1_reference(src + b, y, k);
-
-        for (int i = 0; i < nb; i++) {
-            for (int j = 0; j < QK4_1; j += 2) {
-                const uint8_t vi0 = y[i].qs[j/2] & 0x0F;
-                const uint8_t vi1 = y[i].qs[j/2] >> 4;
-
-                hist[vi0]++;
-                hist[vi1]++;
-            }
-        }
-    }
-
-    return (n/QK4_1*sizeof(block_q4_1));
-}
-
-size_t ggml_quantize_q5_0(const float * src, void * dst, int n, int k, int64_t * hist) {
-    assert(k % QK5_0 == 0);
-    const int nb = k / QK5_0;
-
-    for (int b = 0; b < n; b += k) {
-        block_q5_0 * restrict y = (block_q5_0 *)dst + b/QK5_0;
-
-        quantize_row_q5_0_reference(src + b, y, k);
-
-        for (int i = 0; i < nb; i++) {
-            uint32_t qh;
-            memcpy(&qh, &y[i].qh, sizeof(qh));
-
-            for (int j = 0; j < QK5_0; j += 2) {
-                const uint8_t vh0 = ((qh & (1u << (j/2 + 0 ))) >> (j/2 + 0 )) << 4;
-                const uint8_t vh1 = ((qh & (1u << (j/2 + 16))) >> (j/2 + 12));
-
-                // cast to 16 bins
-                const uint8_t vi0 = ((y[i].qs[j/2] & 0x0F) | vh0) / 2;
-                const uint8_t vi1 = ((y[i].qs[j/2] >>   4) | vh1) / 2;
-
-                hist[vi0]++;
-                hist[vi1]++;
-            }
-        }
-    }
-
-    return (n/QK5_0*sizeof(block_q5_0));
-}
-
-size_t ggml_quantize_q5_1(const float * src, void * dst, int n, int k, int64_t * hist) {
-    assert(k % QK5_1 == 0);
-    const int nb = k / QK5_1;
-
-    for (int b = 0; b < n; b += k) {
-        block_q5_1 * restrict y = (block_q5_1 *)dst + b/QK5_1;
-
-        quantize_row_q5_1_reference(src + b, y, k);
-
-        for (int i = 0; i < nb; i++) {
-            uint32_t qh;
-            memcpy(&qh, &y[i].qh, sizeof(qh));
-
-            for (int j = 0; j < QK5_1; j += 2) {
-                const uint8_t vh0 = ((qh & (1u << (j/2 + 0 ))) >> (j/2 + 0 )) << 4;
-                const uint8_t vh1 = ((qh & (1u << (j/2 + 16))) >> (j/2 + 12));
-
-                // cast to 16 bins
-                const uint8_t vi0 = ((y[i].qs[j/2] & 0x0F) | vh0) / 2;
-                const uint8_t vi1 = ((y[i].qs[j/2] >>   4) | vh1) / 2;
-
-                hist[vi0]++;
-                hist[vi1]++;
-            }
-        }
-    }
-
-    return (n/QK5_1*sizeof(block_q5_1));
-}
-
-size_t ggml_quantize_q8_0(const float * src, void * dst, int n, int k, int64_t * hist) {
-    assert(k % QK8_0 == 0);
-    const int nb = k / QK8_0;
-
-    for (int b = 0; b < n; b += k) {
-        block_q8_0 * restrict y = (block_q8_0 *)dst + b/QK8_0;
-
-        quantize_row_q8_0_reference(src + b, y, k);
-
-        for (int i = 0; i < nb; i++) {
-            for (int j = 0; j < QK8_0; ++j) {
-                const int8_t vi = y[i].qs[j];
-
-                hist[vi/16 + 8]++;
-            }
-        }
-    }
-
-    return (n/QK8_0*sizeof(block_q8_0));
-}
-
 bool ggml_quantize_requires_imatrix(enum ggml_type type) {
     return
         type == GGML_TYPE_IQ2_XXS ||
@@ -20293,177 +20166,52 @@ bool ggml_quantize_requires_imatrix(enum ggml_type type) {
         type == GGML_TYPE_IQ1_S;
 }
 
-size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst, int start,
-        int nrows, int n_per_row, int64_t * hist, const float * imatrix) {
+size_t ggml_quantize_chunk(
+        enum ggml_type   type,
+           const float * src,
+                  void * dst,
+                   int   start,
+                   int   nrows,
+                   int   n_per_row,
+           const float * imatrix) {
+    const int n = nrows * n_per_row;
+
+    if (ggml_quantize_requires_imatrix(type)) {
+        GGML_ASSERT(imatrix != NULL);
+    }
+
+    GGML_ASSERT(start % type_traits[type].blck_size == 0);
+    GGML_ASSERT(start % n_per_row == 0);
+
     ggml_quantize_init(type); // this is noop if already initialized
+
+    const size_t start_row = start / n_per_row;
+    const size_t row_size  = ggml_row_size(type, n_per_row);
+
     size_t result = 0;
-    int n = nrows * n_per_row;
+
     switch (type) {
-        case GGML_TYPE_Q4_0:
-            {
-                GGML_ASSERT(start % QK4_0 == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_q4_0(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_Q4_1:
-            {
-                GGML_ASSERT(start % QK4_1 == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_q4_1(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_Q5_0:
-            {
-                GGML_ASSERT(start % QK5_0 == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_q5_0(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_Q5_1:
-            {
-                GGML_ASSERT(start % QK5_1 == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_q5_1(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_Q8_0:
-            {
-                GGML_ASSERT(start % QK8_0 == 0);
-                block_q8_0 * block = (block_q8_0*)dst + start / QK8_0;
-                result = ggml_quantize_q8_0(src + start, block, n, n, hist);
-            } break;
-        case GGML_TYPE_Q2_K:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_q2_K(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_Q3_K:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_q3_K(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_Q4_K:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_q4_K(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_Q5_K:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_q5_K(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_Q6_K:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_q6_K(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_IQ2_XXS:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                GGML_ASSERT(imatrix);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_iq2_xxs(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_IQ2_XS:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                GGML_ASSERT(imatrix);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_iq2_xs(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_IQ3_XXS:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_iq3_xxs(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_IQ3_S:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_iq3_s(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_IQ2_S:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_iq2_s(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_IQ1_S:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_iq1_s(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-        case GGML_TYPE_IQ4_NL:
+        case GGML_TYPE_Q4_0:    result = quantize_q4_0(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q4_1:    result = quantize_q4_1(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q5_0:    result = quantize_q5_0(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q5_1:    result = quantize_q5_1(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q8_0:    result = quantize_q8_0(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q2_K:    result = quantize_q2_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q3_K:    result = quantize_q3_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q4_K:    result = quantize_q4_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q5_K:    result = quantize_q5_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_Q6_K:    result = quantize_q6_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_IQ2_XXS: result = quantize_iq2_xxs(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_IQ2_XS:  result = quantize_iq2_xs (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_IQ3_XXS: result = quantize_iq3_xxs(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_IQ3_S:   result = quantize_iq3_s  (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_IQ2_S:   result = quantize_iq2_s  (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_IQ1_S:   result = quantize_iq1_s  (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_IQ4_NL:  result = quantize_iq4_nl (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
 #if QK_K == 64
-        case GGML_TYPE_IQ4_XS:
-#endif
-            {
-                GGML_ASSERT(start % QK4_NL == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_iq4_nl(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
-#if QK_K != 64
-        case GGML_TYPE_IQ4_XS:
-            {
-                GGML_ASSERT(start % QK_K == 0);
-                GGML_ASSERT(start % n_per_row == 0);
-                size_t start_row = start / n_per_row;
-                size_t row_size = ggml_row_size(type, n_per_row);
-                result = quantize_iq4_xs(src + start, (char *)dst + start_row * row_size, nrows, n_per_row, hist, imatrix);
-                GGML_ASSERT(result == row_size * nrows);
-            } break;
+        case GGML_TYPE_IQ4_XS:  result = quantize_iq4_nl (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+#else
+        case GGML_TYPE_IQ4_XS:  result = quantize_iq4_xs (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
 #endif
         case GGML_TYPE_F16:
             {
@@ -20480,6 +20228,9 @@ size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst, i
         default:
             assert(false);
     }
+
+    GGML_ASSERT(result == nrows * row_size);
+
     return result;
 }
 

ggml.h

@@ -2194,25 +2194,18 @@ extern "C" {
     GGML_API void ggml_quantize_init(enum ggml_type type);
     GGML_API void ggml_quantize_free(void);
 
-    // TODO: these would probably get removed in favor of the more general ggml_quantize_chunk
-    GGML_API size_t ggml_quantize_q4_0(const float * src, void * dst, int n, int k, int64_t * hist);
-    GGML_API size_t ggml_quantize_q4_1(const float * src, void * dst, int n, int k, int64_t * hist);
-    GGML_API size_t ggml_quantize_q5_0(const float * src, void * dst, int n, int k, int64_t * hist);
-    GGML_API size_t ggml_quantize_q5_1(const float * src, void * dst, int n, int k, int64_t * hist);
-    GGML_API size_t ggml_quantize_q8_0(const float * src, void * dst, int n, int k, int64_t * hist);
-
-    GGML_API size_t ggml_quantize_q2_K(const float * src, void * dst, int n, int k, int64_t * hist);
-    GGML_API size_t ggml_quantize_q3_K(const float * src, void * dst, int n, int k, int64_t * hist);
-    GGML_API size_t ggml_quantize_q4_K(const float * src, void * dst, int n, int k, int64_t * hist);
-    GGML_API size_t ggml_quantize_q5_K(const float * src, void * dst, int n, int k, int64_t * hist);
-    GGML_API size_t ggml_quantize_q6_K(const float * src, void * dst, int n, int k, int64_t * hist);
-
     // some quantization type cannot be used without an importance matrix
     GGML_API bool ggml_quantize_requires_imatrix(enum ggml_type type);
 
     // calls ggml_quantize_init internally (i.e. can allocate memory)
-    GGML_API size_t ggml_quantize_chunk(enum ggml_type type, const float * src, void * dst,
-            int start, int nrows, int n_per_row, int64_t * hist, const float * imatrix);
+    GGML_API size_t ggml_quantize_chunk(
+            enum ggml_type   type,
+               const float * src,
+                      void * dst,
+                       int   start,
+                       int   nrows,
+                       int   n_per_row,
+               const float * imatrix);
 
     //
     // gguf

llama.cpp

@@ -1744,6 +1744,7 @@ struct llama_cparams {
     float defrag_thold;
 
     bool embeddings;
+    bool causal_attn;
     bool offload_kqv;
 
     enum llama_pooling_type pooling_type;
@@ -3702,7 +3703,7 @@ static void llm_load_vocab(
 
             for (int i = 0; i < n_merges; i++) {
                 const std::string word = gguf_get_arr_str(ctx, merges_keyidx, i);
-                GGML_ASSERT(codepoints_from_utf8(word).size() > 0);
+                GGML_ASSERT(unicode_cpts_from_utf8(word).size() > 0);
 
                 std::string first;
                 std::string second;
@@ -3747,7 +3748,7 @@ static void llm_load_vocab(
 
     for (uint32_t i = 0; i < n_vocab; i++) {
         std::string word = gguf_get_arr_str(ctx, token_idx, i);
-        GGML_ASSERT(codepoints_from_utf8(word).size() > 0);
+        GGML_ASSERT(unicode_cpts_from_utf8(word).size() > 0);
 
         vocab.token_to_id[word] = i;
 
@@ -3939,6 +3940,7 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
     LLAMA_LOG_INFO("%s: n_ff             = %u\n",     __func__, hparams.n_ff);
     LLAMA_LOG_INFO("%s: n_expert         = %u\n",     __func__, hparams.n_expert);
     LLAMA_LOG_INFO("%s: n_expert_used    = %u\n",     __func__, hparams.n_expert_used);
+    LLAMA_LOG_INFO("%s: causal attm      = %d\n",     __func__, hparams.causal_attn);
     LLAMA_LOG_INFO("%s: pooling type     = %d\n",     __func__, hparams.pooling_type);
     LLAMA_LOG_INFO("%s: rope type        = %d\n",     __func__, hparams.rope_type);
     LLAMA_LOG_INFO("%s: rope scaling     = %s\n",     __func__, rope_scaling_type);
@@ -8532,7 +8534,13 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
         ggml_backend_tensor_set(lctx.inp_pos, batch.pos, 0, n_tokens*ggml_element_size(lctx.inp_pos));
     }
 
-    if (hparams.causal_attn) {
+    GGML_ASSERT(
+        (hparams.causal_attn || !cparams.causal_attn) &&
+        "non-causal attention with generative models is not supported"
+    );
+
+    // NOTE: hparams.causal_attn indicates the model is capable of generation and uses the kv cache.
+    if (cparams.causal_attn) {
         const int64_t n_kv     = kv_self.n;
         const int64_t n_tokens = batch.n_tokens;
 
@@ -8560,8 +8568,9 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
             }
         }
     } else {
-        // non-causal attention attends only the tokens within the batch (i.e. the KV cache is not used)
+        // when using kv cache, the mask needs to match the kv cache size
         const int64_t n_tokens = batch.n_tokens;
+        const int64_t n_stride = hparams.causal_attn ? kv_self.n : n_tokens;
 
         assert(ggml_backend_buffer_is_host(lctx.inp_KQ_mask->buffer));
 
@@ -8580,7 +8589,11 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
                         }
                     }
 
-                    data[h*(n_tokens*n_tokens) + j*n_tokens + i] = f;
+                    data[h*(n_tokens*n_tokens) + j*n_stride + i] = f;
+                }
+
+                for (int i = n_tokens; i < n_stride; ++i) {
+                    data[h*(n_tokens*n_tokens) + j*n_stride + i] = -INFINITY;
                 }
             }
         }
@@ -8925,17 +8938,29 @@ static int llama_decode_internal(
 
         if (batch.logits) {
             logits_out.resize(n_vocab * n_tokens);
+            int32_t i_first = -1;
             for (uint32_t i = 0; i < n_tokens; i++) {
-                if (batch.logits[i] == 0) {
-                    continue;
+                if (batch.logits[i] && i_first == -1) {
+                    i_first = (int32_t) i;
+                }
+                if (batch.logits[i] == 0 || i == n_tokens - 1) {
+                    if (i_first != -1) {
+                        int i_last = batch.logits[i] == 0 ? i : i + 1;
+                        // extract logits for the range [i_first, i_last)
+                        // group the requests to minimize the number of calls to the backend
+                        ggml_backend_tensor_get_async(backend_res, res,
+                            logits_out.data() + (n_vocab*i_first),
+                            (n_vocab*i_first)*sizeof(float),
+                            (i_last - i_first)*n_vocab*sizeof(float));
+                        i_first = -1;
+                    }
                 }
-                ggml_backend_tensor_get_async(backend_res, res, logits_out.data() + (n_vocab*i), (n_vocab*i)*sizeof(float), n_vocab*sizeof(float));
 #ifndef NDEBUG
-                logits_valid[i] = true;
+                logits_valid[i] = batch.logits[i] != 0;
 #endif
             }
         } else if (lctx.logits_all) {
-            logits_out.resize(n_vocab * n_tokens);
+            logits_out.resize(n_vocab*n_tokens);
             ggml_backend_tensor_get_async(backend_res, res, logits_out.data(), 0, n_vocab*n_tokens*sizeof(float));
 #ifndef NDEBUG
             std::fill(logits_valid.begin(), logits_valid.end(), true);
@@ -9315,7 +9340,7 @@ static uint8_t llama_token_to_byte(const llama_vocab& vocab, llama_token id) {
         }
         case LLAMA_VOCAB_TYPE_BPE: {
             GGML_ASSERT(false);
-            return unicode_to_bytes_bpe(token_data.text);
+            return unicode_utf8_to_byte(token_data.text);
         }
         case LLAMA_VOCAB_TYPE_WPM: {
             GGML_ASSERT(false);
@@ -9340,7 +9365,7 @@ static llama_token llama_byte_to_token(const llama_vocab & vocab, uint8_t ch) {
         }
         case LLAMA_VOCAB_TYPE_WPM:
         case LLAMA_VOCAB_TYPE_BPE: {
-            return vocab.token_to_id.at(bytes_to_unicode_bpe(ch));
+            return vocab.token_to_id.at(unicode_byte_to_utf8(ch));
         }
         default:
             GGML_ASSERT(false);
@@ -9680,9 +9705,9 @@ private:
         bpe_words.reserve(text.size());
         bpe_encoded_words.reserve(text.size());
 
-        auto cps = codepoints_from_utf8(text);
-        for (size_t i = 0; i < cps.size(); ++i)
-            text_utf.emplace_back(codepoint_to_utf8(cps[i]));
+        const auto cpts = unicode_cpts_from_utf8(text);
+        for (size_t i = 0; i < cpts.size(); ++i)
+            text_utf.emplace_back(unicode_cpt_to_utf8(cpts[i]));
 
         for (int i = 0; i < (int)text_utf.size(); i++) {
             const std::string & utf_char = text_utf[i];
@@ -9732,40 +9757,40 @@ private:
             }
 
             if (!split_condition && !collecting) {
-                if (codepoint_type(utf_char) == CODEPOINT_TYPE_LETTER || (!token.size() && utf_char == " " && codepoint_type(utf_char_next) == CODEPOINT_TYPE_LETTER)) {
+                if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER)) {
                     collecting_letter = true;
                     collecting = true;
                 }
-                else if (codepoint_type(utf_char) == CODEPOINT_TYPE_DIGIT || (!token.size() && utf_char == " " && codepoint_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) {
+                else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) {
                     collecting_numeric = true;
                     collecting = true;
                 }
                 else if (
-                    ((codepoint_type(utf_char) != CODEPOINT_TYPE_LETTER && codepoint_type(utf_char) != CODEPOINT_TYPE_DIGIT) && (codepoint_type(utf_char) != CODEPOINT_TYPE_WHITESPACE)) ||
-                    (!token.size() && utf_char == " " && codepoint_type(utf_char_next) != CODEPOINT_TYPE_LETTER && codepoint_type(utf_char_next) != CODEPOINT_TYPE_DIGIT && codepoint_type(utf_char_next) != CODEPOINT_TYPE_WHITESPACE)
+                    ((unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) && (unicode_cpt_type(utf_char) != CODEPOINT_TYPE_WHITESPACE)) ||
+                    (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_DIGIT && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_WHITESPACE)
                     ) {
                     collecting_special = true;
                     collecting = true;
                 }
-                else if (codepoint_type(utf_char) == CODEPOINT_TYPE_WHITESPACE && codepoint_type(utf_char_next) == CODEPOINT_TYPE_WHITESPACE) {
+                else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_WHITESPACE) {
                     collecting_whitespace_lookahead = true;
                     collecting = true;
                 }
-                else if (codepoint_type(utf_char) == CODEPOINT_TYPE_WHITESPACE) {
+                else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE) {
                     split_condition = true;
                 }
             }
             else if (!split_condition && collecting) {
-                if (collecting_letter && codepoint_type(utf_char) != CODEPOINT_TYPE_LETTER) {
+                if (collecting_letter && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER) {
                     split_condition = true;
                 }
-                else if (collecting_numeric && codepoint_type(utf_char) != CODEPOINT_TYPE_DIGIT) {
+                else if (collecting_numeric && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) {
                     split_condition = true;
                 }
-                else if (collecting_special && (codepoint_type(utf_char) == CODEPOINT_TYPE_LETTER || codepoint_type(utf_char) == CODEPOINT_TYPE_DIGIT || codepoint_type(utf_char) == CODEPOINT_TYPE_WHITESPACE)) {
+                else if (collecting_special && (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE)) {
                     split_condition = true;
                 }
-                else if (collecting_whitespace_lookahead && (codepoint_type(utf_char_next) == CODEPOINT_TYPE_LETTER || codepoint_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) {
+                else if (collecting_whitespace_lookahead && (unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) {
                     split_condition = true;
                 }
             }
@@ -9794,7 +9819,7 @@ private:
         for (std::string & word : bpe_words) {
             std::string encoded_token = "";
             for (char & c : word) {
-                encoded_token += bytes_to_unicode_bpe(c);
+                encoded_token += unicode_byte_to_utf8(c);
             }
             bpe_encoded_words.emplace_back(encoded_token);
         }
@@ -9868,25 +9893,13 @@ struct llm_tokenizer_wpm {
     }
 
     std::vector<std::string> preprocess(const std::string & text) {
-        // normalalization form D
-        std::vector<uint32_t> codepoints = codepoints_from_utf8(text);
-        std::vector<uint32_t> nfd_codepoints;
-        for (uint32_t code : codepoints) {
-            auto it = nfd_map.equal_range(code);
-            if (it.first != it.second) {
-                for (auto jt = it.first; jt != it.second; jt++) {
-                    nfd_codepoints.push_back(jt->second);
-                }
-            } else {
-                nfd_codepoints.push_back(code);
-            }
-        }
+        std::vector<uint32_t> cpts_nfd = unicode_cpts_normalize_nfd(unicode_cpts_from_utf8(text));
 
         // strip accents, strip control, uniformize whitespace,
         // to lowercase, pad chinese characters, pad punctuation
         std::string new_str = "";
-        for (uint32_t code : nfd_codepoints) {
-            int type = codepoint_type(code);
+        for (uint32_t code : cpts_nfd) {
+            int type = unicode_cpt_type(code);
             if (type == CODEPOINT_TYPE_ACCENT_MARK || type == CODEPOINT_TYPE_CONTROL) {
                 continue;
             }
@@ -9894,7 +9907,7 @@ struct llm_tokenizer_wpm {
             if (type == CODEPOINT_TYPE_WHITESPACE) {
                 code = ' ';
             }
-            std::string s = codepoint_to_utf8(code);
+            std::string s = unicode_cpt_to_utf8(code);
             if (type == CODEPOINT_TYPE_PUNCTUATION || is_ascii_punct(code) || is_chinese_char(code)) {
                 new_str += " ";
                 new_str += s;
@@ -9914,8 +9927,7 @@ struct llm_tokenizer_wpm {
                 if (r > l) words.push_back(new_str.substr(l, (r - l)));
                 l = r + 1;
                 r = l;
-            }
-            else {
+            } else {
                 r += 1;
             }
         }
@@ -9939,17 +9951,17 @@ struct llm_tokenizer_wpm {
         return code < 256 && ispunct(code);
     }
 
-    bool is_chinese_char(uint32_t codepoint) {
-        if ((codepoint >= 0x4E00  && codepoint <= 0x9FFF)  ||
-            (codepoint >= 0x3400  && codepoint <= 0x4DBF)  ||
-            (codepoint >= 0x20000 && codepoint <= 0x2A6DF) ||
-            (codepoint >= 0x2A700 && codepoint <= 0x2B73F) ||
-            (codepoint >= 0x2B740 && codepoint <= 0x2B81F) ||
-            (codepoint >= 0x2B920 && codepoint <= 0x2CEAF) || // this should be 0x2B820 but in hf rust code it is 0x2B920
-            (codepoint >= 0xF900  && codepoint <= 0xFAFF)  ||
-            (codepoint >= 0x2F800 && codepoint <= 0x2FA1F) ||
-            (codepoint >= 0x3000  && codepoint <= 0x303F)  ||
-            (codepoint >= 0xFF00  && codepoint <= 0xFFEF)) {
+    bool is_chinese_char(uint32_t cpt) {
+        if ((cpt >= 0x4E00  && cpt <= 0x9FFF)  ||
+            (cpt >= 0x3400  && cpt <= 0x4DBF)  ||
+            (cpt >= 0x20000 && cpt <= 0x2A6DF) ||
+            (cpt >= 0x2A700 && cpt <= 0x2B73F) ||
+            (cpt >= 0x2B740 && cpt <= 0x2B81F) ||
+            (cpt >= 0x2B920 && cpt <= 0x2CEAF) || // this should be 0x2B820 but in hf rust code it is 0x2B920
+            (cpt >= 0xF900  && cpt <= 0xFAFF)  ||
+            (cpt >= 0x2F800 && cpt <= 0x2FA1F) ||
+            (cpt >= 0x3000  && cpt <= 0x303F)  ||
+            (cpt >= 0xFF00  && cpt <= 0xFFEF)) {
             return true; // NOLINT
         }
         return false;
@@ -11611,7 +11623,7 @@ static void llama_tensor_dequantize_internal(
     workers.clear();
 }
 
-static ggml_type get_k_quant_type(quantize_state_internal & qs, ggml_type new_type, const ggml_tensor * tensor, llama_ftype ftype) {
+static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type new_type, const ggml_tensor * tensor, llama_ftype ftype) {
     const std::string name = ggml_get_name(tensor);
 
     // TODO: avoid hardcoded tensor names - use the TN_* constants
@@ -11890,17 +11902,16 @@ static ggml_type get_k_quant_type(quantize_state_internal & qs, ggml_type new_ty
     return new_type;
 }
 
-static int32_t llama_tensor_quantize_internal(enum ggml_type new_type, const float * f32_data, void * new_data, const int chunk_size, int nrows, int n_per_row, int64_t * hist_cur, const float * imatrix, std::vector<std::thread> & workers, const int nthread) {
+static int32_t llama_tensor_quantize_internal(enum ggml_type new_type, const float * f32_data, void * new_data, const int chunk_size, int nrows, int n_per_row, const float * imatrix, std::vector<std::thread> & workers, const int nthread) {
     std::mutex mutex;
     int counter = 0;
     size_t new_size = 0;
     if (nthread < 2) {
         // single-thread
-        return ggml_quantize_chunk(new_type, f32_data, new_data, 0, nrows, n_per_row, hist_cur, imatrix);
+        return ggml_quantize_chunk(new_type, f32_data, new_data, 0, nrows, n_per_row, imatrix);
     }
-    auto compute = [&mutex, &counter, &hist_cur, &new_size, new_type, f32_data, new_data, chunk_size,
+    auto compute = [&mutex, &counter, &new_size, new_type, f32_data, new_data, chunk_size,
             nrows, n_per_row, imatrix]() {
-        std::array<int64_t, 1 << 4> local_hist = {};
         const int nrows_per_chunk = chunk_size / n_per_row;
         size_t local_size = 0;
         while (true) {
@@ -11908,17 +11919,13 @@ static int32_t llama_tensor_quantize_internal(enum ggml_type new_type, const flo
             int first_row = counter; counter += nrows_per_chunk;
             if (first_row >= nrows) {
                 if (local_size > 0) {
-                    for (int j=0; j<int(local_hist.size()); ++j) {
-                        hist_cur[j] += local_hist[j];
-                    }
                     new_size += local_size;
                 }
                 break;
             }
             lock.unlock();
             const int this_nrow = std::min(nrows - first_row, nrows_per_chunk);
-            local_size += ggml_quantize_chunk(new_type, f32_data, new_data,
-                    first_row * n_per_row, this_nrow, n_per_row, local_hist.data(), imatrix);
+            local_size += ggml_quantize_chunk(new_type, f32_data, new_data, first_row * n_per_row, this_nrow, n_per_row, imatrix);
         }
     };
     for (int it = 0; it < nthread - 1; ++it) {
@@ -11931,40 +11938,40 @@ static int32_t llama_tensor_quantize_internal(enum ggml_type new_type, const flo
 }
 
 static void llama_model_quantize_internal(const std::string & fname_inp, const std::string & fname_out, const llama_model_quantize_params * params) {
-    ggml_type quantized_type;
+    ggml_type default_type;
     llama_ftype ftype = params->ftype;
 
     switch (params->ftype) {
-        case LLAMA_FTYPE_MOSTLY_Q4_0: quantized_type = GGML_TYPE_Q4_0; break;
-        case LLAMA_FTYPE_MOSTLY_Q4_1: quantized_type = GGML_TYPE_Q4_1; break;
-        case LLAMA_FTYPE_MOSTLY_Q5_0: quantized_type = GGML_TYPE_Q5_0; break;
-        case LLAMA_FTYPE_MOSTLY_Q5_1: quantized_type = GGML_TYPE_Q5_1; break;
-        case LLAMA_FTYPE_MOSTLY_Q8_0: quantized_type = GGML_TYPE_Q8_0; break;
-        case LLAMA_FTYPE_MOSTLY_F16:  quantized_type = GGML_TYPE_F16;  break;
-        case LLAMA_FTYPE_ALL_F32:     quantized_type = GGML_TYPE_F32;  break;
+        case LLAMA_FTYPE_MOSTLY_Q4_0: default_type = GGML_TYPE_Q4_0; break;
+        case LLAMA_FTYPE_MOSTLY_Q4_1: default_type = GGML_TYPE_Q4_1; break;
+        case LLAMA_FTYPE_MOSTLY_Q5_0: default_type = GGML_TYPE_Q5_0; break;
+        case LLAMA_FTYPE_MOSTLY_Q5_1: default_type = GGML_TYPE_Q5_1; break;
+        case LLAMA_FTYPE_MOSTLY_Q8_0: default_type = GGML_TYPE_Q8_0; break;
+        case LLAMA_FTYPE_MOSTLY_F16:  default_type = GGML_TYPE_F16;  break;
+        case LLAMA_FTYPE_ALL_F32:     default_type = GGML_TYPE_F32;  break;
 
         // K-quants
         case LLAMA_FTYPE_MOSTLY_Q2_K_S:
-        case LLAMA_FTYPE_MOSTLY_Q2_K:    quantized_type = GGML_TYPE_Q2_K;    break;
-        case LLAMA_FTYPE_MOSTLY_IQ3_XS:  quantized_type = GGML_TYPE_IQ3_S;   break;
+        case LLAMA_FTYPE_MOSTLY_Q2_K:    default_type = GGML_TYPE_Q2_K;    break;
+        case LLAMA_FTYPE_MOSTLY_IQ3_XS:  default_type = GGML_TYPE_IQ3_S;   break;
         case LLAMA_FTYPE_MOSTLY_Q3_K_S:
         case LLAMA_FTYPE_MOSTLY_Q3_K_M:
-        case LLAMA_FTYPE_MOSTLY_Q3_K_L:  quantized_type = GGML_TYPE_Q3_K;    break;
+        case LLAMA_FTYPE_MOSTLY_Q3_K_L:  default_type = GGML_TYPE_Q3_K;    break;
         case LLAMA_FTYPE_MOSTLY_Q4_K_S:
-        case LLAMA_FTYPE_MOSTLY_Q4_K_M:  quantized_type = GGML_TYPE_Q4_K;    break;
+        case LLAMA_FTYPE_MOSTLY_Q4_K_M:  default_type = GGML_TYPE_Q4_K;    break;
         case LLAMA_FTYPE_MOSTLY_Q5_K_S:
-        case LLAMA_FTYPE_MOSTLY_Q5_K_M:  quantized_type = GGML_TYPE_Q5_K;    break;
-        case LLAMA_FTYPE_MOSTLY_Q6_K:    quantized_type = GGML_TYPE_Q6_K;    break;
-        case LLAMA_FTYPE_MOSTLY_IQ2_XXS: quantized_type = GGML_TYPE_IQ2_XXS; break;
-        case LLAMA_FTYPE_MOSTLY_IQ2_XS:  quantized_type = GGML_TYPE_IQ2_XS;  break;
-        case LLAMA_FTYPE_MOSTLY_IQ2_S:   quantized_type = GGML_TYPE_IQ2_XS;  break;
-        case LLAMA_FTYPE_MOSTLY_IQ2_M:   quantized_type = GGML_TYPE_IQ2_S;   break;
-        case LLAMA_FTYPE_MOSTLY_IQ3_XXS: quantized_type = GGML_TYPE_IQ3_XXS; break;
-        case LLAMA_FTYPE_MOSTLY_IQ1_S:   quantized_type = GGML_TYPE_IQ1_S;   break;
-        case LLAMA_FTYPE_MOSTLY_IQ4_NL:  quantized_type = GGML_TYPE_IQ4_NL;  break;
-        case LLAMA_FTYPE_MOSTLY_IQ4_XS:  quantized_type = GGML_TYPE_IQ4_XS;  break;
-        case LLAMA_FTYPE_MOSTLY_IQ3_S:   quantized_type = GGML_TYPE_IQ3_S;   break;
-        case LLAMA_FTYPE_MOSTLY_IQ3_M:   quantized_type = GGML_TYPE_IQ3_S;   break;
+        case LLAMA_FTYPE_MOSTLY_Q5_K_M:  default_type = GGML_TYPE_Q5_K;    break;
+        case LLAMA_FTYPE_MOSTLY_Q6_K:    default_type = GGML_TYPE_Q6_K;    break;
+        case LLAMA_FTYPE_MOSTLY_IQ2_XXS: default_type = GGML_TYPE_IQ2_XXS; break;
+        case LLAMA_FTYPE_MOSTLY_IQ2_XS:  default_type = GGML_TYPE_IQ2_XS;  break;
+        case LLAMA_FTYPE_MOSTLY_IQ2_S:   default_type = GGML_TYPE_IQ2_XS;  break;
+        case LLAMA_FTYPE_MOSTLY_IQ2_M:   default_type = GGML_TYPE_IQ2_S;   break;
+        case LLAMA_FTYPE_MOSTLY_IQ3_XXS: default_type = GGML_TYPE_IQ3_XXS; break;
+        case LLAMA_FTYPE_MOSTLY_IQ1_S:   default_type = GGML_TYPE_IQ1_S;   break;
+        case LLAMA_FTYPE_MOSTLY_IQ4_NL:  default_type = GGML_TYPE_IQ4_NL;  break;
+        case LLAMA_FTYPE_MOSTLY_IQ4_XS:  default_type = GGML_TYPE_IQ4_XS;  break;
+        case LLAMA_FTYPE_MOSTLY_IQ3_S:   default_type = GGML_TYPE_IQ3_S;   break;
+        case LLAMA_FTYPE_MOSTLY_IQ3_M:   default_type = GGML_TYPE_IQ3_S;   break;
 
         default: throw std::runtime_error(format("invalid output file type %d\n", ftype));
     }
@@ -12041,7 +12048,6 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
 
     size_t total_size_org = 0;
     size_t total_size_new = 0;
-    std::vector<int64_t> hist_all(1 << 4, 0);
 
     std::vector<std::thread> workers;
     workers.reserve(nthread);
@@ -12106,23 +12112,26 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
         // do not quantize Mamba's small yet 2D weights
         // NOTE: can't use LLM_TN here because the layer number is not known
         quantize &= name.find("ssm_conv1d.weight") == std::string::npos;
-        quantize &= name.find("ssm_x.weight") == std::string::npos;
-        quantize &= name.find("ssm_dt.weight") == std::string::npos;
+        quantize &= name.find("ssm_x.weight")      == std::string::npos;
+        quantize &= name.find("ssm_dt.weight")     == std::string::npos;
 
         enum ggml_type new_type;
         void * new_data;
         size_t new_size;
 
         if (quantize) {
-            new_type = quantized_type;
-            if (!params->pure) {
-                new_type = get_k_quant_type(qs, new_type, tensor, ftype);
+            new_type = default_type;
+
+            // get more optimal quantization type based on the tensor shape, layer, etc.
+            if (!params->pure && ggml_is_quantized(default_type)) {
+                new_type = llama_tensor_get_type(qs, new_type, tensor, ftype);
             }
 
             // If we've decided to quantize to the same type the tensor is already
             // in then there's nothing to do.
             quantize = tensor->type != new_type;
         }
+
         if (!quantize) {
             new_type = tensor->type;
             new_data = tensor->data;
@@ -12168,14 +12177,13 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
                 f32_data = (float *) f32_conv_buf.data();
             }
 
-            LLAMA_LOG_INFO("quantizing to %s .. ", ggml_type_name(new_type));
+            LLAMA_LOG_INFO("converting to %s .. ", ggml_type_name(new_type));
             fflush(stdout);
 
             if (work.size() < nelements * 4) {
                 work.resize(nelements * 4); // upper bound on size
             }
             new_data = work.data();
-            std::array<int64_t, 1 << 4> hist_cur = {};
 
             const int n_per_row = tensor->ne[0];
             const int nrows = nelements / n_per_row;
@@ -12185,22 +12193,9 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
 
             const int nchunk = (nelements + chunk_size - 1)/chunk_size;
             const int nthread_use = nthread > 1 ? std::max(1, std::min(nthread, nchunk)) : 1;
-            new_size = llama_tensor_quantize_internal(new_type, f32_data, new_data, chunk_size, nrows, n_per_row, hist_cur.data(), imatrix, workers, nthread_use);
+            new_size = llama_tensor_quantize_internal(new_type, f32_data, new_data, chunk_size, nrows, n_per_row, imatrix, workers, nthread_use);
 
-            LLAMA_LOG_INFO("size = %8.2f MiB -> %8.2f MiB", ggml_nbytes(tensor)/1024.0/1024.0, new_size/1024.0/1024.0);
-            int64_t tot_count = 0;
-            for (size_t i = 0; i < hist_cur.size(); i++) {
-                hist_all[i] += hist_cur[i];
-                tot_count += hist_cur[i];
-            }
-
-            if (tot_count > 0) {
-                LLAMA_LOG_INFO(" | hist: ");
-                for (size_t i = 0; i < hist_cur.size(); i++) {
-                    LLAMA_LOG_INFO("%5.3f ", hist_cur[i] / float(nelements));
-                }
-            }
-            LLAMA_LOG_INFO("\n");
+            LLAMA_LOG_INFO("size = %8.2f MiB -> %8.2f MiB\n", ggml_nbytes(tensor)/1024.0/1024.0, new_size/1024.0/1024.0);
         }
         total_size_org += ggml_nbytes(tensor);
         total_size_new += new_size;
@@ -12229,24 +12224,8 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
     LLAMA_LOG_INFO("%s: model size  = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);
     LLAMA_LOG_INFO("%s: quant size  = %8.2f MB\n", __func__, total_size_new/1024.0/1024.0);
 
-    // print histogram for all tensors
-    {
-        int64_t sum_all = 0;
-        for (size_t i = 0; i < hist_all.size(); i++) {
-            sum_all += hist_all[i];
-        }
-
-        if (sum_all > 0) {
-            LLAMA_LOG_INFO("%s: hist: ", __func__);
-            for (size_t i = 0; i < hist_all.size(); i++) {
-                LLAMA_LOG_INFO("%5.3f ", hist_all[i] / float(sum_all));
-            }
-            LLAMA_LOG_INFO("\n");
-        }
-    }
-
     if (qs.n_fallback > 0) {
-        LLAMA_LOG_WARN("%s: WARNING: %d of %d tensor(s) incompatible with k-quants and required fallback quantization\n",
+        LLAMA_LOG_WARN("%s: WARNING: %d of %d tensor(s) required fallback quantization\n",
                 __func__, qs.n_fallback, qs.n_k_quantized + qs.n_fallback);
     }
 }
@@ -12757,6 +12736,8 @@ struct llama_context * llama_new_context_with_model(
         cparams.yarn_ext_factor = rope_scaling_type == LLAMA_ROPE_SCALING_TYPE_YARN ? 1.0f : 0.0f;
     }
 
+    cparams.causal_attn = hparams.causal_attn;
+
     if (cparams.pooling_type == LLAMA_POOLING_TYPE_UNSPECIFIED) {
         if (hparams.pooling_type == LLAMA_POOLING_TYPE_UNSPECIFIED) {
             cparams.pooling_type = LLAMA_POOLING_TYPE_NONE;
@@ -13791,6 +13772,10 @@ void llama_set_abort_callback(struct llama_context * ctx, bool (*abort_callback)
     ctx->abort_callback_data = abort_callback_data;
 }
 
+void llama_set_causal_attn(struct llama_context * ctx, bool causal_attn) {
+    ctx->cparams.causal_attn = causal_attn;
+}
+
 struct llama_batch llama_batch_get_one(
              llama_token * tokens,
                  int32_t   n_tokens,
@@ -13955,9 +13940,9 @@ int32_t llama_tokenize(
 
 static std::string llama_decode_text(const std::string & text) {
     std::string decoded_text;
-    auto unicode_sequences = codepoints_from_utf8(text);
-    for (auto& unicode_sequence : unicode_sequences) {
-        decoded_text += unicode_to_bytes_bpe(codepoint_to_utf8(unicode_sequence));
+    auto unicode_sequences = unicode_cpts_from_utf8(text);
+    for (auto & unicode_sequence : unicode_sequences) {
+        decoded_text += unicode_utf8_to_byte(unicode_cpt_to_utf8(unicode_sequence));
     }
 
     return decoded_text;
@@ -13982,7 +13967,7 @@ int32_t llama_token_to_piece(const struct llama_model * model, llama_token token
             } else if (llama_is_user_defined_token(model->vocab, token)) {
                 std::string result = model->vocab.id_to_token[token].text;
                 if (length < (int) result.length()) {
-                    return -result.length();
+                    return -(int) result.length();
                 }
                 memcpy(buf, result.c_str(), result.length());
                 return result.length();
@@ -14017,7 +14002,7 @@ int32_t llama_token_to_piece(const struct llama_model * model, llama_token token
             } else if (llama_is_user_defined_token(model->vocab, token)) {
                 std::string result = model->vocab.id_to_token[token].text;
                 if (length < (int) result.length()) {
-                    return -result.length();
+                    return -(int) result.length();
                 }
                 memcpy(buf, result.c_str(), result.length());
                 return result.length();

llama.h

@@ -278,7 +278,7 @@ extern "C" {
         bool allow_requantize;       // allow quantizing non-f32/f16 tensors
         bool quantize_output_tensor; // quantize output.weight
         bool only_copy;              // only copy tensors - ftype, allow_requantize and quantize_output_tensor are ignored
-        bool pure;                   // disable k-quant mixtures and quantize all tensors to the same type
+        bool pure;                   // quantize all tensors to the default type
         void * imatrix;              // pointer to importance matrix data
     } llama_model_quantize_params;
 
@@ -643,6 +643,10 @@ extern "C" {
     // n_threads_batch is the number of threads used for prompt and batch processing (multiple tokens)
     LLAMA_API void llama_set_n_threads(struct llama_context * ctx, uint32_t n_threads, uint32_t n_threads_batch);
 
+    // Set whether to use causal attention or not
+    // If set to true, the model will only attend to the past tokens
+    LLAMA_API void llama_set_causal_attn(struct llama_context * ctx, bool causal_attn);
+
     // Set abort callback
     LLAMA_API void llama_set_abort_callback(struct llama_context * ctx, ggml_abort_callback abort_callback, void * abort_callback_data);
 

scripts/sync-ggml.last

@@ -1 +1 @@
-8695910a39102609073d0e099aa7c97d6bcb3bf9
+43a6d4af1971ee2912ff7bc2404011ff327b6a60

tests/test-backend-ops.cpp

@@ -53,7 +53,6 @@ static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float m
     } else if (ggml_is_quantized(tensor->type) || tensor->type == GGML_TYPE_F16) {
         GGML_ASSERT(size % ggml_blck_size(tensor->type) == 0);
         std::vector<uint8_t> dataq(ggml_row_size(tensor->type, size));
-        int64_t hist[16];
         std::vector<float> imatrix(tensor->ne[0], 1.0f); // dummy importance matrix
         const float * im = imatrix.data();
         if (!ggml_quantize_requires_imatrix(tensor->type)) {
@@ -63,7 +62,7 @@ static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float m
                 im = nullptr;
             }
         }
-        ggml_quantize_chunk(tensor->type, data.data(), dataq.data(), 0, size/tensor->ne[0], tensor->ne[0], hist, im);
+        ggml_quantize_chunk(tensor->type, data.data(), dataq.data(), 0, size/tensor->ne[0], tensor->ne[0], im);
         ggml_backend_tensor_set(tensor, dataq.data(), 0, dataq.size());
     } else if (tensor->type == GGML_TYPE_I8 || tensor->type == GGML_TYPE_I16 || tensor->type == GGML_TYPE_I32) {
         // This is going to create some weird integers though.

tests/test-tokenizer-1-bpe.cpp

@@ -64,7 +64,7 @@ int main(int argc, char **argv) {
     for (int i = 0; i < n_vocab; ++i) {
         std::string str = llama_detokenize_bpe(ctx, std::vector<int>(1, i));
         try {
-            auto cps = codepoints_from_utf8(str);
+            auto cps = unicode_cpts_from_utf8(str);
             std::vector<llama_token> tokens = llama_tokenize(ctx, str, false);
             std::string check = llama_detokenize_bpe(ctx, tokens);
             if (check != str) {
@@ -97,7 +97,7 @@ int main(int argc, char **argv) {
                         continue;
                     }
 
-                    std::string str = codepoint_to_utf8(cp);
+                    std::string str = unicode_cpt_to_utf8(cp);
                     std::vector<llama_token> tokens = llama_tokenize(ctx, str, false);
                     std::string check = llama_detokenize_bpe(ctx, tokens);
                     if (cp != 9601 && str != check) {

tests/test-tokenizer-1-llama.cpp

@@ -85,7 +85,7 @@ int main(int argc, char **argv) {
                         continue;
                     }
 
-                    std::string str = codepoint_to_utf8(cp);
+                    std::string str = unicode_cpt_to_utf8(cp);
                     std::vector<llama_token> tokens = llama_tokenize(ctx, str, false);
                     std::string check = llama_detokenize_spm(ctx, tokens);
                     if (cp != 9601 && str != check) {

unicode.h

@@ -1,784 +1,26 @@
-#pragma once
+#pragma once
 
-#include <cassert>
-#include <map>
-#include <stdexcept>
+#include <cstdint>
 #include <string>
-#include <unordered_map>
 #include <vector>
 
-static const std::vector<std::pair<uint32_t, uint32_t>> digit_ranges = {
-{0x30, 0x39}, {0xB2, 0xB3}, {0xB9, 0xB9}, {0x660, 0x669}, {0x6F0, 0x6F9}, {0x7C0, 0x7C9}, {0x966, 0x96F}, {0x9E6, 0x9EF}, {0xA66, 0xA6F}, {0xAE6, 0xAEF}, {0xB66, 0xB6F}, {0xBE6, 0xBEF}, {0xC66, 0xC6F},
-{0xCE6, 0xCEF}, {0xD66, 0xD6F}, {0xDE6, 0xDEF}, {0xE50, 0xE59}, {0xED0, 0xED9}, {0xF20, 0xF29}, {0x1040, 0x1049}, {0x1090, 0x1099}, {0x1369, 0x1371}, {0x17E0, 0x17E9}, {0x1810, 0x1819}, {0x1946, 0x194F},
-{0x19D0, 0x19DA}, {0x1A80, 0x1A89}, {0x1A90, 0x1A99}, {0x1B50, 0x1B59}, {0x1BB0, 0x1BB9}, {0x1C40, 0x1C49}, {0x1C50, 0x1C59}, {0x2070, 0x2070}, {0x2074, 0x2079}, {0x2080, 0x2089}, {0x2460, 0x2468},
-{0x2474, 0x247C}, {0x2488, 0x2490}, {0x24EA, 0x24EA}, {0x24F5, 0x24FD}, {0x24FF, 0x24FF}, {0x2776, 0x277E}, {0x2780, 0x2788}, {0x278A, 0x2792}, {0xA620, 0xA629}, {0xA8D0, 0xA8D9}, {0xA900, 0xA909},
-{0xA9D0, 0xA9D9}, {0xA9F0, 0xA9F9}, {0xAA50, 0xAA59}, {0xABF0, 0xABF9}, {0xFF10, 0xFF19}, {0x104A0, 0x104A9}, {0x10A40, 0x10A43}, {0x10D30, 0x10D39}, {0x10E60, 0x10E68}, {0x11052, 0x1105A},
-{0x11066, 0x1106F}, {0x110F0, 0x110F9}, {0x11136, 0x1113F}, {0x111D0, 0x111D9}, {0x112F0, 0x112F9}, {0x11450, 0x11459}, {0x114D0, 0x114D9}, {0x11650, 0x11659}, {0x116C0, 0x116C9}, {0x11730, 0x11739},
-{0x118E0, 0x118E9}, {0x11950, 0x11959}, {0x11C50, 0x11C59}, {0x11D50, 0x11D59}, {0x11DA0, 0x11DA9}, {0x16A60, 0x16A69}, {0x16B50, 0x16B59}, {0x1D7CE, 0x1D7FF}, {0x1E140, 0x1E149}, {0x1E2F0, 0x1E2F9},
-{0x1E950, 0x1E959}, {0x1F100, 0x1F10A}, {0x1FBF0, 0x1FBF9},
-};
-
-static const std::vector<std::pair<uint32_t, uint32_t>> letter_ranges = {
-{0x41, 0x5A}, {0x61, 0x7A}, {0xAA, 0xAA}, {0xB5, 0xB5}, {0xBA, 0xBA}, {0xC0, 0xD6}, {0xD8, 0xF6}, {0xF8, 0x2C1}, {0x2C6, 0x2D1}, {0x2E0, 0x2E4}, {0x2EC, 0x2EC}, {0x2EE, 0x2EE}, {0x370, 0x374},
-{0x376, 0x377}, {0x37A, 0x37D}, {0x37F, 0x37F}, {0x386, 0x386}, {0x388, 0x38A}, {0x38C, 0x38C}, {0x38E, 0x3A1}, {0x3A3, 0x3F5}, {0x3F7, 0x481}, {0x48A, 0x52F}, {0x531, 0x556}, {0x559, 0x559},
-{0x560, 0x588}, {0x5D0, 0x5EA}, {0x5EF, 0x5F2}, {0x620, 0x64A}, {0x66E, 0x66F}, {0x671, 0x6D3}, {0x6D5, 0x6D5}, {0x6E5, 0x6E6}, {0x6EE, 0x6EF}, {0x6FA, 0x6FC}, {0x6FF, 0x6FF}, {0x710, 0x710},
-{0x712, 0x72F}, {0x74D, 0x7A5}, {0x7B1, 0x7B1}, {0x7CA, 0x7EA}, {0x7F4, 0x7F5}, {0x7FA, 0x7FA}, {0x800, 0x815}, {0x81A, 0x81A}, {0x824, 0x824}, {0x828, 0x828}, {0x840, 0x858}, {0x860, 0x86A},
-{0x8A0, 0x8B4}, {0x8B6, 0x8C7}, {0x904, 0x939}, {0x93D, 0x93D}, {0x950, 0x950}, {0x958, 0x961}, {0x971, 0x980}, {0x985, 0x98C}, {0x98F, 0x990}, {0x993, 0x9A8}, {0x9AA, 0x9B0}, {0x9B2, 0x9B2},
-{0x9B6, 0x9B9}, {0x9BD, 0x9BD}, {0x9CE, 0x9CE}, {0x9DC, 0x9DD}, {0x9DF, 0x9E1}, {0x9F0, 0x9F1}, {0x9FC, 0x9FC}, {0xA05, 0xA0A}, {0xA0F, 0xA10}, {0xA13, 0xA28}, {0xA2A, 0xA30}, {0xA32, 0xA33},
-{0xA35, 0xA36}, {0xA38, 0xA39}, {0xA59, 0xA5C}, {0xA5E, 0xA5E}, {0xA72, 0xA74}, {0xA85, 0xA8D}, {0xA8F, 0xA91}, {0xA93, 0xAA8}, {0xAAA, 0xAB0}, {0xAB2, 0xAB3}, {0xAB5, 0xAB9}, {0xABD, 0xABD},
-{0xAD0, 0xAD0}, {0xAE0, 0xAE1}, {0xAF9, 0xAF9}, {0xB05, 0xB0C}, {0xB0F, 0xB10}, {0xB13, 0xB28}, {0xB2A, 0xB30}, {0xB32, 0xB33}, {0xB35, 0xB39}, {0xB3D, 0xB3D}, {0xB5C, 0xB5D}, {0xB5F, 0xB61},
-{0xB71, 0xB71}, {0xB83, 0xB83}, {0xB85, 0xB8A}, {0xB8E, 0xB90}, {0xB92, 0xB95}, {0xB99, 0xB9A}, {0xB9C, 0xB9C}, {0xB9E, 0xB9F}, {0xBA3, 0xBA4}, {0xBA8, 0xBAA}, {0xBAE, 0xBB9}, {0xBD0, 0xBD0},
-{0xC05, 0xC0C}, {0xC0E, 0xC10}, {0xC12, 0xC28}, {0xC2A, 0xC39}, {0xC3D, 0xC3D}, {0xC58, 0xC5A}, {0xC60, 0xC61}, {0xC80, 0xC80}, {0xC85, 0xC8C}, {0xC8E, 0xC90}, {0xC92, 0xCA8}, {0xCAA, 0xCB3},
-{0xCB5, 0xCB9}, {0xCBD, 0xCBD}, {0xCDE, 0xCDE}, {0xCE0, 0xCE1}, {0xCF1, 0xCF2}, {0xD04, 0xD0C}, {0xD0E, 0xD10}, {0xD12, 0xD3A}, {0xD3D, 0xD3D}, {0xD4E, 0xD4E}, {0xD54, 0xD56}, {0xD5F, 0xD61},
-{0xD7A, 0xD7F}, {0xD85, 0xD96}, {0xD9A, 0xDB1}, {0xDB3, 0xDBB}, {0xDBD, 0xDBD}, {0xDC0, 0xDC6}, {0xE01, 0xE30}, {0xE32, 0xE33}, {0xE40, 0xE46}, {0xE81, 0xE82}, {0xE84, 0xE84}, {0xE86, 0xE8A},
-{0xE8C, 0xEA3}, {0xEA5, 0xEA5}, {0xEA7, 0xEB0}, {0xEB2, 0xEB3}, {0xEBD, 0xEBD}, {0xEC0, 0xEC4}, {0xEC6, 0xEC6}, {0xEDC, 0xEDF}, {0xF00, 0xF00}, {0xF40, 0xF47}, {0xF49, 0xF6C}, {0xF88, 0xF8C},
-{0x1000, 0x102A}, {0x103F, 0x103F}, {0x1050, 0x1055}, {0x105A, 0x105D}, {0x1061, 0x1061}, {0x1065, 0x1066}, {0x106E, 0x1070}, {0x1075, 0x1081}, {0x108E, 0x108E}, {0x10A0, 0x10C5}, {0x10C7, 0x10C7},
-{0x10CD, 0x10CD}, {0x10D0, 0x10FA}, {0x10FC, 0x1248}, {0x124A, 0x124D}, {0x1250, 0x1256}, {0x1258, 0x1258}, {0x125A, 0x125D}, {0x1260, 0x1288}, {0x128A, 0x128D}, {0x1290, 0x12B0}, {0x12B2, 0x12B5},
-{0x12B8, 0x12BE}, {0x12C0, 0x12C0}, {0x12C2, 0x12C5}, {0x12C8, 0x12D6}, {0x12D8, 0x1310}, {0x1312, 0x1315}, {0x1318, 0x135A}, {0x1380, 0x138F}, {0x13A0, 0x13F5}, {0x13F8, 0x13FD}, {0x1401, 0x166C},
-{0x166F, 0x167F}, {0x1681, 0x169A}, {0x16A0, 0x16EA}, {0x16F1, 0x16F8}, {0x1700, 0x170C}, {0x170E, 0x1711}, {0x1720, 0x1731}, {0x1740, 0x1751}, {0x1760, 0x176C}, {0x176E, 0x1770}, {0x1780, 0x17B3},
-{0x17D7, 0x17D7}, {0x17DC, 0x17DC}, {0x1820, 0x1878}, {0x1880, 0x1884}, {0x1887, 0x18A8}, {0x18AA, 0x18AA}, {0x18B0, 0x18F5}, {0x1900, 0x191E}, {0x1950, 0x196D}, {0x1970, 0x1974}, {0x1980, 0x19AB},
-{0x19B0, 0x19C9}, {0x1A00, 0x1A16}, {0x1A20, 0x1A54}, {0x1AA7, 0x1AA7}, {0x1B05, 0x1B33}, {0x1B45, 0x1B4B}, {0x1B83, 0x1BA0}, {0x1BAE, 0x1BAF}, {0x1BBA, 0x1BE5}, {0x1C00, 0x1C23}, {0x1C4D, 0x1C4F},
-{0x1C5A, 0x1C7D}, {0x1C80, 0x1C88}, {0x1C90, 0x1CBA}, {0x1CBD, 0x1CBF}, {0x1CE9, 0x1CEC}, {0x1CEE, 0x1CF3}, {0x1CF5, 0x1CF6}, {0x1CFA, 0x1CFA}, {0x1D00, 0x1DBF}, {0x1E00, 0x1F15}, {0x1F18, 0x1F1D},
-{0x1F20, 0x1F45}, {0x1F48, 0x1F4D}, {0x1F50, 0x1F57}, {0x1F59, 0x1F59}, {0x1F5B, 0x1F5B}, {0x1F5D, 0x1F5D}, {0x1F5F, 0x1F7D}, {0x1F80, 0x1FB4}, {0x1FB6, 0x1FBC}, {0x1FBE, 0x1FBE}, {0x1FC2, 0x1FC4},
-{0x1FC6, 0x1FCC}, {0x1FD0, 0x1FD3}, {0x1FD6, 0x1FDB}, {0x1FE0, 0x1FEC}, {0x1FF2, 0x1FF4}, {0x1FF6, 0x1FFC}, {0x2071, 0x2071}, {0x207F, 0x207F}, {0x2090, 0x209C}, {0x2102, 0x2102}, {0x2107, 0x2107},
-{0x210A, 0x2113}, {0x2115, 0x2115}, {0x2119, 0x211D}, {0x2124, 0x2124}, {0x2126, 0x2126}, {0x2128, 0x2128}, {0x212A, 0x212D}, {0x212F, 0x2139}, {0x213C, 0x213F}, {0x2145, 0x2149}, {0x214E, 0x214E},
-{0x2183, 0x2184}, {0x2C00, 0x2C2E}, {0x2C30, 0x2C5E}, {0x2C60, 0x2CE4}, {0x2CEB, 0x2CEE}, {0x2CF2, 0x2CF3}, {0x2D00, 0x2D25}, {0x2D27, 0x2D27}, {0x2D2D, 0x2D2D}, {0x2D30, 0x2D67}, {0x2D6F, 0x2D6F},
-{0x2D80, 0x2D96}, {0x2DA0, 0x2DA6}, {0x2DA8, 0x2DAE}, {0x2DB0, 0x2DB6}, {0x2DB8, 0x2DBE}, {0x2DC0, 0x2DC6}, {0x2DC8, 0x2DCE}, {0x2DD0, 0x2DD6}, {0x2DD8, 0x2DDE}, {0x2E2F, 0x2E2F}, {0x3005, 0x3006},
-{0x3031, 0x3035}, {0x303B, 0x303C}, {0x3041, 0x3096}, {0x309D, 0x309F}, {0x30A1, 0x30FA}, {0x30FC, 0x30FF}, {0x3105, 0x312F}, {0x3131, 0x318E}, {0x31A0, 0x31BF}, {0x31F0, 0x31FF}, {0x3400, 0x4DBF},
-{0x4E00, 0x9FFC}, {0xA000, 0xA48C}, {0xA4D0, 0xA4FD}, {0xA500, 0xA60C}, {0xA610, 0xA61F}, {0xA62A, 0xA62B}, {0xA640, 0xA66E}, {0xA67F, 0xA69D}, {0xA6A0, 0xA6E5}, {0xA717, 0xA71F}, {0xA722, 0xA788},
-{0xA78B, 0xA7BF}, {0xA7C2, 0xA7CA}, {0xA7F5, 0xA801}, {0xA803, 0xA805}, {0xA807, 0xA80A}, {0xA80C, 0xA822}, {0xA840, 0xA873}, {0xA882, 0xA8B3}, {0xA8F2, 0xA8F7}, {0xA8FB, 0xA8FB}, {0xA8FD, 0xA8FE},
-{0xA90A, 0xA925}, {0xA930, 0xA946}, {0xA960, 0xA97C}, {0xA984, 0xA9B2}, {0xA9CF, 0xA9CF}, {0xA9E0, 0xA9E4}, {0xA9E6, 0xA9EF}, {0xA9FA, 0xA9FE}, {0xAA00, 0xAA28}, {0xAA40, 0xAA42}, {0xAA44, 0xAA4B},
-{0xAA60, 0xAA76}, {0xAA7A, 0xAA7A}, {0xAA7E, 0xAAAF}, {0xAAB1, 0xAAB1}, {0xAAB5, 0xAAB6}, {0xAAB9, 0xAABD}, {0xAAC0, 0xAAC0}, {0xAAC2, 0xAAC2}, {0xAADB, 0xAADD}, {0xAAE0, 0xAAEA}, {0xAAF2, 0xAAF4},
-{0xAB01, 0xAB06}, {0xAB09, 0xAB0E}, {0xAB11, 0xAB16}, {0xAB20, 0xAB26}, {0xAB28, 0xAB2E}, {0xAB30, 0xAB5A}, {0xAB5C, 0xAB69}, {0xAB70, 0xABE2}, {0xAC00, 0xD7A3}, {0xD7B0, 0xD7C6}, {0xD7CB, 0xD7FB},
-{0xF900, 0xFA6D}, {0xFA70, 0xFAD9}, {0xFB00, 0xFB06}, {0xFB13, 0xFB17}, {0xFB1D, 0xFB1D}, {0xFB1F, 0xFB28}, {0xFB2A, 0xFB36}, {0xFB38, 0xFB3C}, {0xFB3E, 0xFB3E}, {0xFB40, 0xFB41}, {0xFB43, 0xFB44},
-{0xFB46, 0xFBB1}, {0xFBD3, 0xFD3D}, {0xFD50, 0xFD8F}, {0xFD92, 0xFDC7}, {0xFDF0, 0xFDFB}, {0xFE70, 0xFE74}, {0xFE76, 0xFEFC}, {0xFF21, 0xFF3A}, {0xFF41, 0xFF5A}, {0xFF66, 0xFFBE}, {0xFFC2, 0xFFC7},
-{0xFFCA, 0xFFCF}, {0xFFD2, 0xFFD7}, {0xFFDA, 0xFFDC}, {0x10000, 0x1000B}, {0x1000D, 0x10026}, {0x10028, 0x1003A}, {0x1003C, 0x1003D}, {0x1003F, 0x1004D}, {0x10050, 0x1005D}, {0x10080, 0x100FA},
-{0x10280, 0x1029C}, {0x102A0, 0x102D0}, {0x10300, 0x1031F}, {0x1032D, 0x10340}, {0x10342, 0x10349}, {0x10350, 0x10375}, {0x10380, 0x1039D}, {0x103A0, 0x103C3}, {0x103C8, 0x103CF}, {0x10400, 0x1049D},
-{0x104B0, 0x104D3}, {0x104D8, 0x104FB}, {0x10500, 0x10527}, {0x10530, 0x10563}, {0x10600, 0x10736}, {0x10740, 0x10755}, {0x10760, 0x10767}, {0x10800, 0x10805}, {0x10808, 0x10808}, {0x1080A, 0x10835},
-{0x10837, 0x10838}, {0x1083C, 0x1083C}, {0x1083F, 0x10855}, {0x10860, 0x10876}, {0x10880, 0x1089E}, {0x108E0, 0x108F2}, {0x108F4, 0x108F5}, {0x10900, 0x10915}, {0x10920, 0x10939}, {0x10980, 0x109B7},
-{0x109BE, 0x109BF}, {0x10A00, 0x10A00}, {0x10A10, 0x10A13}, {0x10A15, 0x10A17}, {0x10A19, 0x10A35}, {0x10A60, 0x10A7C}, {0x10A80, 0x10A9C}, {0x10AC0, 0x10AC7}, {0x10AC9, 0x10AE4}, {0x10B00, 0x10B35},
-{0x10B40, 0x10B55}, {0x10B60, 0x10B72}, {0x10B80, 0x10B91}, {0x10C00, 0x10C48}, {0x10C80, 0x10CB2}, {0x10CC0, 0x10CF2}, {0x10D00, 0x10D23}, {0x10E80, 0x10EA9}, {0x10EB0, 0x10EB1}, {0x10F00, 0x10F1C},
-{0x10F27, 0x10F27}, {0x10F30, 0x10F45}, {0x10FB0, 0x10FC4}, {0x10FE0, 0x10FF6}, {0x11003, 0x11037}, {0x11083, 0x110AF}, {0x110D0, 0x110E8}, {0x11103, 0x11126}, {0x11144, 0x11144}, {0x11147, 0x11147},
-{0x11150, 0x11172}, {0x11176, 0x11176}, {0x11183, 0x111B2}, {0x111C1, 0x111C4}, {0x111DA, 0x111DA}, {0x111DC, 0x111DC}, {0x11200, 0x11211}, {0x11213, 0x1122B}, {0x11280, 0x11286}, {0x11288, 0x11288},
-{0x1128A, 0x1128D}, {0x1128F, 0x1129D}, {0x1129F, 0x112A8}, {0x112B0, 0x112DE}, {0x11305, 0x1130C}, {0x1130F, 0x11310}, {0x11313, 0x11328}, {0x1132A, 0x11330}, {0x11332, 0x11333}, {0x11335, 0x11339},
-{0x1133D, 0x1133D}, {0x11350, 0x11350}, {0x1135D, 0x11361}, {0x11400, 0x11434}, {0x11447, 0x1144A}, {0x1145F, 0x11461}, {0x11480, 0x114AF}, {0x114C4, 0x114C5}, {0x114C7, 0x114C7}, {0x11580, 0x115AE},
-{0x115D8, 0x115DB}, {0x11600, 0x1162F}, {0x11644, 0x11644}, {0x11680, 0x116AA}, {0x116B8, 0x116B8}, {0x11700, 0x1171A}, {0x11800, 0x1182B}, {0x118A0, 0x118DF}, {0x118FF, 0x11906}, {0x11909, 0x11909},
-{0x1190C, 0x11913}, {0x11915, 0x11916}, {0x11918, 0x1192F}, {0x1193F, 0x1193F}, {0x11941, 0x11941}, {0x119A0, 0x119A7}, {0x119AA, 0x119D0}, {0x119E1, 0x119E1}, {0x119E3, 0x119E3}, {0x11A00, 0x11A00},
-{0x11A0B, 0x11A32}, {0x11A3A, 0x11A3A}, {0x11A50, 0x11A50}, {0x11A5C, 0x11A89}, {0x11A9D, 0x11A9D}, {0x11AC0, 0x11AF8}, {0x11C00, 0x11C08}, {0x11C0A, 0x11C2E}, {0x11C40, 0x11C40}, {0x11C72, 0x11C8F},
-{0x11D00, 0x11D06}, {0x11D08, 0x11D09}, {0x11D0B, 0x11D30}, {0x11D46, 0x11D46}, {0x11D60, 0x11D65}, {0x11D67, 0x11D68}, {0x11D6A, 0x11D89}, {0x11D98, 0x11D98}, {0x11EE0, 0x11EF2}, {0x11FB0, 0x11FB0},
-{0x12000, 0x12399}, {0x12480, 0x12543}, {0x13000, 0x1342E}, {0x14400, 0x14646}, {0x16800, 0x16A38}, {0x16A40, 0x16A5E}, {0x16AD0, 0x16AED}, {0x16B00, 0x16B2F}, {0x16B40, 0x16B43}, {0x16B63, 0x16B77},
-{0x16B7D, 0x16B8F}, {0x16E40, 0x16E7F}, {0x16F00, 0x16F4A}, {0x16F50, 0x16F50}, {0x16F93, 0x16F9F}, {0x16FE0, 0x16FE1}, {0x16FE3, 0x16FE3}, {0x17000, 0x187F7}, {0x18800, 0x18CD5}, {0x18D00, 0x18D08},
-{0x1B000, 0x1B11E}, {0x1B150, 0x1B152}, {0x1B164, 0x1B167}, {0x1B170, 0x1B2FB}, {0x1BC00, 0x1BC6A}, {0x1BC70, 0x1BC7C}, {0x1BC80, 0x1BC88}, {0x1BC90, 0x1BC99}, {0x1D400, 0x1D454}, {0x1D456, 0x1D49C},
-{0x1D49E, 0x1D49F}, {0x1D4A2, 0x1D4A2}, {0x1D4A5, 0x1D4A6}, {0x1D4A9, 0x1D4AC}, {0x1D4AE, 0x1D4B9}, {0x1D4BB, 0x1D4BB}, {0x1D4BD, 0x1D4C3}, {0x1D4C5, 0x1D505}, {0x1D507, 0x1D50A}, {0x1D50D, 0x1D514},
-{0x1D516, 0x1D51C}, {0x1D51E, 0x1D539}, {0x1D53B, 0x1D53E}, {0x1D540, 0x1D544}, {0x1D546, 0x1D546}, {0x1D54A, 0x1D550}, {0x1D552, 0x1D6A5}, {0x1D6A8, 0x1D6C0}, {0x1D6C2, 0x1D6DA}, {0x1D6DC, 0x1D6FA},
-{0x1D6FC, 0x1D714}, {0x1D716, 0x1D734}, {0x1D736, 0x1D74E}, {0x1D750, 0x1D76E}, {0x1D770, 0x1D788}, {0x1D78A, 0x1D7A8}, {0x1D7AA, 0x1D7C2}, {0x1D7C4, 0x1D7CB}, {0x1E100, 0x1E12C}, {0x1E137, 0x1E13D},
-{0x1E14E, 0x1E14E}, {0x1E2C0, 0x1E2EB}, {0x1E800, 0x1E8C4}, {0x1E900, 0x1E943}, {0x1E94B, 0x1E94B}, {0x1EE00, 0x1EE03}, {0x1EE05, 0x1EE1F}, {0x1EE21, 0x1EE22}, {0x1EE24, 0x1EE24}, {0x1EE27, 0x1EE27},
-{0x1EE29, 0x1EE32}, {0x1EE34, 0x1EE37}, {0x1EE39, 0x1EE39}, {0x1EE3B, 0x1EE3B}, {0x1EE42, 0x1EE42}, {0x1EE47, 0x1EE47}, {0x1EE49, 0x1EE49}, {0x1EE4B, 0x1EE4B}, {0x1EE4D, 0x1EE4F}, {0x1EE51, 0x1EE52},
-{0x1EE54, 0x1EE54}, {0x1EE57, 0x1EE57}, {0x1EE59, 0x1EE59}, {0x1EE5B, 0x1EE5B}, {0x1EE5D, 0x1EE5D}, {0x1EE5F, 0x1EE5F}, {0x1EE61, 0x1EE62}, {0x1EE64, 0x1EE64}, {0x1EE67, 0x1EE6A}, {0x1EE6C, 0x1EE72},
-{0x1EE74, 0x1EE77}, {0x1EE79, 0x1EE7C}, {0x1EE7E, 0x1EE7E}, {0x1EE80, 0x1EE89}, {0x1EE8B, 0x1EE9B}, {0x1EEA1, 0x1EEA3}, {0x1EEA5, 0x1EEA9}, {0x1EEAB, 0x1EEBB}, {0x20000, 0x2A6DD}, {0x2A700, 0x2B734},
-{0x2B740, 0x2B81D}, {0x2B820, 0x2CEA1}, {0x2CEB0, 0x2EBE0}, {0x2F800, 0x2FA1D}, {0x30000, 0x3134A},
-};
-
-static const std::vector<std::pair<uint32_t, uint32_t>> whitespace_ranges = {
-{0x9, 0xD}, {0x1C, 0x20}, {0x85, 0x85}, {0xA0, 0xA0}, {0x1680, 0x1680}, {0x2000, 0x200A}, {0x2028, 0x2029}, {0x202F, 0x202F}, {0x205F, 0x205F}, {0x3000, 0x3000},
-};
-
-static const std::vector<std::pair<uint32_t, uint32_t>> accent_mark_ranges = {
-{0x300, 0x36F}, {0x483, 0x489}, {0x591, 0x5BD}, {0x5BF, 0x5BF}, {0x5C1, 0x5C2}, {0x5C4, 0x5C5}, {0x5C7, 0x5C7}, {0x610, 0x61A}, {0x64B, 0x65F}, {0x670, 0x670}, {0x6D6, 0x6DC}, {0x6DF, 0x6E4},
-{0x6E7, 0x6E8}, {0x6EA, 0x6ED}, {0x711, 0x711}, {0x730, 0x74A}, {0x7A6, 0x7B0}, {0x7EB, 0x7F3}, {0x7FD, 0x7FD}, {0x816, 0x819}, {0x81B, 0x823}, {0x825, 0x827}, {0x829, 0x82D}, {0x859, 0x85B},
-{0x8D3, 0x8E1}, {0x8E3, 0x903}, {0x93A, 0x93C}, {0x93E, 0x94F}, {0x951, 0x957}, {0x962, 0x963}, {0x981, 0x983}, {0x9BC, 0x9BC}, {0x9BE, 0x9C4}, {0x9C7, 0x9C8}, {0x9CB, 0x9CD}, {0x9D7, 0x9D7},
-{0x9E2, 0x9E3}, {0x9FE, 0x9FE}, {0xA01, 0xA03}, {0xA3C, 0xA3C}, {0xA3E, 0xA42}, {0xA47, 0xA48}, {0xA4B, 0xA4D}, {0xA51, 0xA51}, {0xA70, 0xA71}, {0xA75, 0xA75}, {0xA81, 0xA83}, {0xABC, 0xABC},
-{0xABE, 0xAC5}, {0xAC7, 0xAC9}, {0xACB, 0xACD}, {0xAE2, 0xAE3}, {0xAFA, 0xAFF}, {0xB01, 0xB03}, {0xB3C, 0xB3C}, {0xB3E, 0xB44}, {0xB47, 0xB48}, {0xB4B, 0xB4D}, {0xB55, 0xB57}, {0xB62, 0xB63},
-{0xB82, 0xB82}, {0xBBE, 0xBC2}, {0xBC6, 0xBC8}, {0xBCA, 0xBCD}, {0xBD7, 0xBD7}, {0xC00, 0xC04}, {0xC3E, 0xC44}, {0xC46, 0xC48}, {0xC4A, 0xC4D}, {0xC55, 0xC56}, {0xC62, 0xC63}, {0xC81, 0xC83},
-{0xCBC, 0xCBC}, {0xCBE, 0xCC4}, {0xCC6, 0xCC8}, {0xCCA, 0xCCD}, {0xCD5, 0xCD6}, {0xCE2, 0xCE3}, {0xD00, 0xD03}, {0xD3B, 0xD3C}, {0xD3E, 0xD44}, {0xD46, 0xD48}, {0xD4A, 0xD4D}, {0xD57, 0xD57},
-{0xD62, 0xD63}, {0xD81, 0xD83}, {0xDCA, 0xDCA}, {0xDCF, 0xDD4}, {0xDD6, 0xDD6}, {0xDD8, 0xDDF}, {0xDF2, 0xDF3}, {0xE31, 0xE31}, {0xE34, 0xE3A}, {0xE47, 0xE4E}, {0xEB1, 0xEB1}, {0xEB4, 0xEBC},
-{0xEC8, 0xECD}, {0xF18, 0xF19}, {0xF35, 0xF35}, {0xF37, 0xF37}, {0xF39, 0xF39}, {0xF3E, 0xF3F}, {0xF71, 0xF84}, {0xF86, 0xF87}, {0xF8D, 0xF97}, {0xF99, 0xFBC}, {0xFC6, 0xFC6}, {0x102B, 0x103E},
-{0x1056, 0x1059}, {0x105E, 0x1060}, {0x1062, 0x1064}, {0x1067, 0x106D}, {0x1071, 0x1074}, {0x1082, 0x108D}, {0x108F, 0x108F}, {0x109A, 0x109D}, {0x135D, 0x135F}, {0x1712, 0x1714}, {0x1732, 0x1734},
-{0x1752, 0x1753}, {0x1772, 0x1773}, {0x17B4, 0x17D3}, {0x17DD, 0x17DD}, {0x180B, 0x180D}, {0x1885, 0x1886}, {0x18A9, 0x18A9}, {0x1920, 0x192B}, {0x1930, 0x193B}, {0x1A17, 0x1A1B}, {0x1A55, 0x1A5E},
-{0x1A60, 0x1A7C}, {0x1A7F, 0x1A7F}, {0x1AB0, 0x1AC0}, {0x1B00, 0x1B04}, {0x1B34, 0x1B44}, {0x1B6B, 0x1B73}, {0x1B80, 0x1B82}, {0x1BA1, 0x1BAD}, {0x1BE6, 0x1BF3}, {0x1C24, 0x1C37}, {0x1CD0, 0x1CD2},
-{0x1CD4, 0x1CE8}, {0x1CED, 0x1CED}, {0x1CF4, 0x1CF4}, {0x1CF7, 0x1CF9}, {0x1DC0, 0x1DF9}, {0x1DFB, 0x1DFF}, {0x20D0, 0x20F0}, {0x2CEF, 0x2CF1}, {0x2D7F, 0x2D7F}, {0x2DE0, 0x2DFF}, {0x302A, 0x302F},
-{0x3099, 0x309A}, {0xA66F, 0xA672}, {0xA674, 0xA67D}, {0xA69E, 0xA69F}, {0xA6F0, 0xA6F1}, {0xA802, 0xA802}, {0xA806, 0xA806}, {0xA80B, 0xA80B}, {0xA823, 0xA827}, {0xA82C, 0xA82C}, {0xA880, 0xA881},
-{0xA8B4, 0xA8C5}, {0xA8E0, 0xA8F1}, {0xA8FF, 0xA8FF}, {0xA926, 0xA92D}, {0xA947, 0xA953}, {0xA980, 0xA983}, {0xA9B3, 0xA9C0}, {0xA9E5, 0xA9E5}, {0xAA29, 0xAA36}, {0xAA43, 0xAA43}, {0xAA4C, 0xAA4D},
-{0xAA7B, 0xAA7D}, {0xAAB0, 0xAAB0}, {0xAAB2, 0xAAB4}, {0xAAB7, 0xAAB8}, {0xAABE, 0xAABF}, {0xAAC1, 0xAAC1}, {0xAAEB, 0xAAEF}, {0xAAF5, 0xAAF6}, {0xABE3, 0xABEA}, {0xABEC, 0xABED}, {0xFB1E, 0xFB1E},
-{0xFE00, 0xFE0F}, {0xFE20, 0xFE2F}, {0x101FD, 0x101FD}, {0x102E0, 0x102E0}, {0x10376, 0x1037A}, {0x10A01, 0x10A03}, {0x10A05, 0x10A06}, {0x10A0C, 0x10A0F}, {0x10A38, 0x10A3A}, {0x10A3F, 0x10A3F},
-{0x10AE5, 0x10AE6}, {0x10D24, 0x10D27}, {0x10EAB, 0x10EAC}, {0x10F46, 0x10F50}, {0x11000, 0x11002}, {0x11038, 0x11046}, {0x1107F, 0x11082}, {0x110B0, 0x110BA}, {0x11100, 0x11102}, {0x11127, 0x11134},
-{0x11145, 0x11146}, {0x11173, 0x11173}, {0x11180, 0x11182}, {0x111B3, 0x111C0}, {0x111C9, 0x111CC}, {0x111CE, 0x111CF}, {0x1122C, 0x11237}, {0x1123E, 0x1123E}, {0x112DF, 0x112EA}, {0x11300, 0x11303},
-{0x1133B, 0x1133C}, {0x1133E, 0x11344}, {0x11347, 0x11348}, {0x1134B, 0x1134D}, {0x11357, 0x11357}, {0x11362, 0x11363}, {0x11366, 0x1136C}, {0x11370, 0x11374}, {0x11435, 0x11446}, {0x1145E, 0x1145E},
-{0x114B0, 0x114C3}, {0x115AF, 0x115B5}, {0x115B8, 0x115C0}, {0x115DC, 0x115DD}, {0x11630, 0x11640}, {0x116AB, 0x116B7}, {0x1171D, 0x1172B}, {0x1182C, 0x1183A}, {0x11930, 0x11935}, {0x11937, 0x11938},
-{0x1193B, 0x1193E}, {0x11940, 0x11940}, {0x11942, 0x11943}, {0x119D1, 0x119D7}, {0x119DA, 0x119E0}, {0x119E4, 0x119E4}, {0x11A01, 0x11A0A}, {0x11A33, 0x11A39}, {0x11A3B, 0x11A3E}, {0x11A47, 0x11A47},
-{0x11A51, 0x11A5B}, {0x11A8A, 0x11A99}, {0x11C2F, 0x11C36}, {0x11C38, 0x11C3F}, {0x11C92, 0x11CA7}, {0x11CA9, 0x11CB6}, {0x11D31, 0x11D36}, {0x11D3A, 0x11D3A}, {0x11D3C, 0x11D3D}, {0x11D3F, 0x11D45},
-{0x11D47, 0x11D47}, {0x11D8A, 0x11D8E}, {0x11D90, 0x11D91}, {0x11D93, 0x11D97}, {0x11EF3, 0x11EF6}, {0x16AF0, 0x16AF4}, {0x16B30, 0x16B36}, {0x16F4F, 0x16F4F}, {0x16F51, 0x16F87}, {0x16F8F, 0x16F92},
-{0x16FE4, 0x16FE4}, {0x16FF0, 0x16FF1}, {0x1BC9D, 0x1BC9E}, {0x1D165, 0x1D169}, {0x1D16D, 0x1D172}, {0x1D17B, 0x1D182}, {0x1D185, 0x1D18B}, {0x1D1AA, 0x1D1AD}, {0x1D242, 0x1D244}, {0x1DA00, 0x1DA36},
-{0x1DA3B, 0x1DA6C}, {0x1DA75, 0x1DA75}, {0x1DA84, 0x1DA84}, {0x1DA9B, 0x1DA9F}, {0x1DAA1, 0x1DAAF}, {0x1E000, 0x1E006}, {0x1E008, 0x1E018}, {0x1E01B, 0x1E021}, {0x1E023, 0x1E024}, {0x1E026, 0x1E02A},
-{0x1E130, 0x1E136}, {0x1E2EC, 0x1E2EF}, {0x1E8D0, 0x1E8D6}, {0x1E944, 0x1E94A}, {0xE0100, 0xE01EF},
-};
-
-static const std::vector<std::pair<uint32_t, uint32_t>> punctuation_ranges = {
-{0x21, 0x23}, {0x25, 0x2A}, {0x2C, 0x2F}, {0x3A, 0x3B}, {0x3F, 0x40}, {0x5B, 0x5D}, {0x5F, 0x5F}, {0x7B, 0x7B}, {0x7D, 0x7D}, {0xA1, 0xA1}, {0xA7, 0xA7}, {0xAB, 0xAB}, {0xB6, 0xB7}, {0xBB, 0xBB},
-{0xBF, 0xBF}, {0x37E, 0x37E}, {0x387, 0x387}, {0x55A, 0x55F}, {0x589, 0x58A}, {0x5BE, 0x5BE}, {0x5C0, 0x5C0}, {0x5C3, 0x5C3}, {0x5C6, 0x5C6}, {0x5F3, 0x5F4}, {0x609, 0x60A}, {0x60C, 0x60D},
-{0x61B, 0x61B}, {0x61E, 0x61F}, {0x66A, 0x66D}, {0x6D4, 0x6D4}, {0x700, 0x70D}, {0x7F7, 0x7F9}, {0x830, 0x83E}, {0x85E, 0x85E}, {0x964, 0x965}, {0x970, 0x970}, {0x9FD, 0x9FD}, {0xA76, 0xA76},
-{0xAF0, 0xAF0}, {0xC77, 0xC77}, {0xC84, 0xC84}, {0xDF4, 0xDF4}, {0xE4F, 0xE4F}, {0xE5A, 0xE5B}, {0xF04, 0xF12}, {0xF14, 0xF14}, {0xF3A, 0xF3D}, {0xF85, 0xF85}, {0xFD0, 0xFD4}, {0xFD9, 0xFDA},
-{0x104A, 0x104F}, {0x10FB, 0x10FB}, {0x1360, 0x1368}, {0x1400, 0x1400}, {0x166E, 0x166E}, {0x169B, 0x169C}, {0x16EB, 0x16ED}, {0x1735, 0x1736}, {0x17D4, 0x17D6}, {0x17D8, 0x17DA}, {0x1800, 0x180A},
-{0x1944, 0x1945}, {0x1A1E, 0x1A1F}, {0x1AA0, 0x1AA6}, {0x1AA8, 0x1AAD}, {0x1B5A, 0x1B60}, {0x1BFC, 0x1BFF}, {0x1C3B, 0x1C3F}, {0x1C7E, 0x1C7F}, {0x1CC0, 0x1CC7}, {0x1CD3, 0x1CD3}, {0x2010, 0x2027},
-{0x2030, 0x2043}, {0x2045, 0x2051}, {0x2053, 0x205E}, {0x207D, 0x207E}, {0x208D, 0x208E}, {0x2308, 0x230B}, {0x2329, 0x232A}, {0x2768, 0x2775}, {0x27C5, 0x27C6}, {0x27E6, 0x27EF}, {0x2983, 0x2998},
-{0x29D8, 0x29DB}, {0x29FC, 0x29FD}, {0x2CF9, 0x2CFC}, {0x2CFE, 0x2CFF}, {0x2D70, 0x2D70}, {0x2E00, 0x2E2E}, {0x2E30, 0x2E4F}, {0x2E52, 0x2E52}, {0x3001, 0x3003}, {0x3008, 0x3011}, {0x3014, 0x301F},
-{0x3030, 0x3030}, {0x303D, 0x303D}, {0x30A0, 0x30A0}, {0x30FB, 0x30FB}, {0xA4FE, 0xA4FF}, {0xA60D, 0xA60F}, {0xA673, 0xA673}, {0xA67E, 0xA67E}, {0xA6F2, 0xA6F7}, {0xA874, 0xA877}, {0xA8CE, 0xA8CF},
-{0xA8F8, 0xA8FA}, {0xA8FC, 0xA8FC}, {0xA92E, 0xA92F}, {0xA95F, 0xA95F}, {0xA9C1, 0xA9CD}, {0xA9DE, 0xA9DF}, {0xAA5C, 0xAA5F}, {0xAADE, 0xAADF}, {0xAAF0, 0xAAF1}, {0xABEB, 0xABEB}, {0xFD3E, 0xFD3F},
-{0xFE10, 0xFE19}, {0xFE30, 0xFE52}, {0xFE54, 0xFE61}, {0xFE63, 0xFE63}, {0xFE68, 0xFE68}, {0xFE6A, 0xFE6B}, {0xFF01, 0xFF03}, {0xFF05, 0xFF0A}, {0xFF0C, 0xFF0F}, {0xFF1A, 0xFF1B}, {0xFF1F, 0xFF20},
-{0xFF3B, 0xFF3D}, {0xFF3F, 0xFF3F}, {0xFF5B, 0xFF5B}, {0xFF5D, 0xFF5D}, {0xFF5F, 0xFF65}, {0x10100, 0x10102}, {0x1039F, 0x1039F}, {0x103D0, 0x103D0}, {0x1056F, 0x1056F}, {0x10857, 0x10857},
-{0x1091F, 0x1091F}, {0x1093F, 0x1093F}, {0x10A50, 0x10A58}, {0x10A7F, 0x10A7F}, {0x10AF0, 0x10AF6}, {0x10B39, 0x10B3F}, {0x10B99, 0x10B9C}, {0x10EAD, 0x10EAD}, {0x10F55, 0x10F59}, {0x11047, 0x1104D},
-{0x110BB, 0x110BC}, {0x110BE, 0x110C1}, {0x11140, 0x11143}, {0x11174, 0x11175}, {0x111C5, 0x111C8}, {0x111CD, 0x111CD}, {0x111DB, 0x111DB}, {0x111DD, 0x111DF}, {0x11238, 0x1123D}, {0x112A9, 0x112A9},
-{0x1144B, 0x1144F}, {0x1145A, 0x1145B}, {0x1145D, 0x1145D}, {0x114C6, 0x114C6}, {0x115C1, 0x115D7}, {0x11641, 0x11643}, {0x11660, 0x1166C}, {0x1173C, 0x1173E}, {0x1183B, 0x1183B}, {0x11944, 0x11946},
-{0x119E2, 0x119E2}, {0x11A3F, 0x11A46}, {0x11A9A, 0x11A9C}, {0x11A9E, 0x11AA2}, {0x11C41, 0x11C45}, {0x11C70, 0x11C71}, {0x11EF7, 0x11EF8}, {0x11FFF, 0x11FFF}, {0x12470, 0x12474}, {0x16A6E, 0x16A6F},
-{0x16AF5, 0x16AF5}, {0x16B37, 0x16B3B}, {0x16B44, 0x16B44}, {0x16E97, 0x16E9A}, {0x16FE2, 0x16FE2}, {0x1BC9F, 0x1BC9F}, {0x1DA87, 0x1DA8B}, {0x1E95E, 0x1E95F},
-};
-
-static const std::vector<std::pair<uint32_t, uint32_t>> symbol_ranges = {
-{0x24, 0x24}, {0x2B, 0x2B}, {0x3C, 0x3E}, {0x5E, 0x5E}, {0x60, 0x60}, {0x7C, 0x7C}, {0x7E, 0x7E}, {0xA2, 0xA6}, {0xA8, 0xA9}, {0xAC, 0xAC}, {0xAE, 0xB1}, {0xB4, 0xB4}, {0xB8, 0xB8}, {0xD7, 0xD7},
-{0xF7, 0xF7}, {0x2C2, 0x2C5}, {0x2D2, 0x2DF}, {0x2E5, 0x2EB}, {0x2ED, 0x2ED}, {0x2EF, 0x2FF}, {0x375, 0x375}, {0x384, 0x385}, {0x3F6, 0x3F6}, {0x482, 0x482}, {0x58D, 0x58F}, {0x606, 0x608},
-{0x60B, 0x60B}, {0x60E, 0x60F}, {0x6DE, 0x6DE}, {0x6E9, 0x6E9}, {0x6FD, 0x6FE}, {0x7F6, 0x7F6}, {0x7FE, 0x7FF}, {0x9F2, 0x9F3}, {0x9FA, 0x9FB}, {0xAF1, 0xAF1}, {0xB70, 0xB70}, {0xBF3, 0xBFA},
-{0xC7F, 0xC7F}, {0xD4F, 0xD4F}, {0xD79, 0xD79}, {0xE3F, 0xE3F}, {0xF01, 0xF03}, {0xF13, 0xF13}, {0xF15, 0xF17}, {0xF1A, 0xF1F}, {0xF34, 0xF34}, {0xF36, 0xF36}, {0xF38, 0xF38}, {0xFBE, 0xFC5},
-{0xFC7, 0xFCC}, {0xFCE, 0xFCF}, {0xFD5, 0xFD8}, {0x109E, 0x109F}, {0x1390, 0x1399}, {0x166D, 0x166D}, {0x17DB, 0x17DB}, {0x1940, 0x1940}, {0x19DE, 0x19FF}, {0x1B61, 0x1B6A}, {0x1B74, 0x1B7C},
-{0x1FBD, 0x1FBD}, {0x1FBF, 0x1FC1}, {0x1FCD, 0x1FCF}, {0x1FDD, 0x1FDF}, {0x1FED, 0x1FEF}, {0x1FFD, 0x1FFE}, {0x2044, 0x2044}, {0x2052, 0x2052}, {0x207A, 0x207C}, {0x208A, 0x208C}, {0x20A0, 0x20BF},
-{0x2100, 0x2101}, {0x2103, 0x2106}, {0x2108, 0x2109}, {0x2114, 0x2114}, {0x2116, 0x2118}, {0x211E, 0x2123}, {0x2125, 0x2125}, {0x2127, 0x2127}, {0x2129, 0x2129}, {0x212E, 0x212E}, {0x213A, 0x213B},
-{0x2140, 0x2144}, {0x214A, 0x214D}, {0x214F, 0x214F}, {0x218A, 0x218B}, {0x2190, 0x2307}, {0x230C, 0x2328}, {0x232B, 0x2426}, {0x2440, 0x244A}, {0x249C, 0x24E9}, {0x2500, 0x2767}, {0x2794, 0x27C4},
-{0x27C7, 0x27E5}, {0x27F0, 0x2982}, {0x2999, 0x29D7}, {0x29DC, 0x29FB}, {0x29FE, 0x2B73}, {0x2B76, 0x2B95}, {0x2B97, 0x2BFF}, {0x2CE5, 0x2CEA}, {0x2E50, 0x2E51}, {0x2E80, 0x2E99}, {0x2E9B, 0x2EF3},
-{0x2F00, 0x2FD5}, {0x2FF0, 0x2FFB}, {0x3004, 0x3004}, {0x3012, 0x3013}, {0x3020, 0x3020}, {0x3036, 0x3037}, {0x303E, 0x303F}, {0x309B, 0x309C}, {0x3190, 0x3191}, {0x3196, 0x319F}, {0x31C0, 0x31E3},
-{0x3200, 0x321E}, {0x322A, 0x3247}, {0x3250, 0x3250}, {0x3260, 0x327F}, {0x328A, 0x32B0}, {0x32C0, 0x33FF}, {0x4DC0, 0x4DFF}, {0xA490, 0xA4C6}, {0xA700, 0xA716}, {0xA720, 0xA721}, {0xA789, 0xA78A},
-{0xA828, 0xA82B}, {0xA836, 0xA839}, {0xAA77, 0xAA79}, {0xAB5B, 0xAB5B}, {0xAB6A, 0xAB6B}, {0xFB29, 0xFB29}, {0xFBB2, 0xFBC1}, {0xFDFC, 0xFDFD}, {0xFE62, 0xFE62}, {0xFE64, 0xFE66}, {0xFE69, 0xFE69},
-{0xFF04, 0xFF04}, {0xFF0B, 0xFF0B}, {0xFF1C, 0xFF1E}, {0xFF3E, 0xFF3E}, {0xFF40, 0xFF40}, {0xFF5C, 0xFF5C}, {0xFF5E, 0xFF5E}, {0xFFE0, 0xFFE6}, {0xFFE8, 0xFFEE}, {0xFFFC, 0xFFFD}, {0x10137, 0x1013F},
-{0x10179, 0x10189}, {0x1018C, 0x1018E}, {0x10190, 0x1019C}, {0x101A0, 0x101A0}, {0x101D0, 0x101FC}, {0x10877, 0x10878}, {0x10AC8, 0x10AC8}, {0x1173F, 0x1173F}, {0x11FD5, 0x11FF1}, {0x16B3C, 0x16B3F},
-{0x16B45, 0x16B45}, {0x1BC9C, 0x1BC9C}, {0x1D000, 0x1D0F5}, {0x1D100, 0x1D126}, {0x1D129, 0x1D164}, {0x1D16A, 0x1D16C}, {0x1D183, 0x1D184}, {0x1D18C, 0x1D1A9}, {0x1D1AE, 0x1D1E8}, {0x1D200, 0x1D241},
-{0x1D245, 0x1D245}, {0x1D300, 0x1D356}, {0x1D6C1, 0x1D6C1}, {0x1D6DB, 0x1D6DB}, {0x1D6FB, 0x1D6FB}, {0x1D715, 0x1D715}, {0x1D735, 0x1D735}, {0x1D74F, 0x1D74F}, {0x1D76F, 0x1D76F}, {0x1D789, 0x1D789},
-{0x1D7A9, 0x1D7A9}, {0x1D7C3, 0x1D7C3}, {0x1D800, 0x1D9FF}, {0x1DA37, 0x1DA3A}, {0x1DA6D, 0x1DA74}, {0x1DA76, 0x1DA83}, {0x1DA85, 0x1DA86}, {0x1E14F, 0x1E14F}, {0x1E2FF, 0x1E2FF}, {0x1ECAC, 0x1ECAC},
-{0x1ECB0, 0x1ECB0}, {0x1ED2E, 0x1ED2E}, {0x1EEF0, 0x1EEF1}, {0x1F000, 0x1F02B}, {0x1F030, 0x1F093}, {0x1F0A0, 0x1F0AE}, {0x1F0B1, 0x1F0BF}, {0x1F0C1, 0x1F0CF}, {0x1F0D1, 0x1F0F5}, {0x1F10D, 0x1F1AD},
-{0x1F1E6, 0x1F202}, {0x1F210, 0x1F23B}, {0x1F240, 0x1F248}, {0x1F250, 0x1F251}, {0x1F260, 0x1F265}, {0x1F300, 0x1F6D7}, {0x1F6E0, 0x1F6EC}, {0x1F6F0, 0x1F6FC}, {0x1F700, 0x1F773}, {0x1F780, 0x1F7D8},
-{0x1F7E0, 0x1F7EB}, {0x1F800, 0x1F80B}, {0x1F810, 0x1F847}, {0x1F850, 0x1F859}, {0x1F860, 0x1F887}, {0x1F890, 0x1F8AD}, {0x1F8B0, 0x1F8B1}, {0x1F900, 0x1F978}, {0x1F97A, 0x1F9CB}, {0x1F9CD, 0x1FA53},
-{0x1FA60, 0x1FA6D}, {0x1FA70, 0x1FA74}, {0x1FA78, 0x1FA7A}, {0x1FA80, 0x1FA86}, {0x1FA90, 0x1FAA8}, {0x1FAB0, 0x1FAB6}, {0x1FAC0, 0x1FAC2}, {0x1FAD0, 0x1FAD6}, {0x1FB00, 0x1FB92}, {0x1FB94, 0x1FBCA},
-};
-
-static const std::vector<std::pair<uint32_t, uint32_t>> control_ranges = {
-{0x0, 0x8}, {0xE, 0x1B}, {0x7F, 0x84}, {0x86, 0x9F}, {0xAD, 0xAD}, {0x378, 0x379}, {0x380, 0x383}, {0x38B, 0x38B}, {0x38D, 0x38D}, {0x3A2, 0x3A2}, {0x530, 0x530}, {0x557, 0x558}, {0x58B, 0x58C},
-{0x590, 0x590}, {0x5C8, 0x5CF}, {0x5EB, 0x5EE}, {0x5F5, 0x605}, {0x61C, 0x61D}, {0x6DD, 0x6DD}, {0x70E, 0x70F}, {0x74B, 0x74C}, {0x7B2, 0x7BF}, {0x7FB, 0x7FC}, {0x82E, 0x82F}, {0x83F, 0x83F},
-{0x85C, 0x85D}, {0x85F, 0x85F}, {0x86B, 0x89F}, {0x8B5, 0x8B5}, {0x8C8, 0x8D2}, {0x8E2, 0x8E2}, {0x984, 0x984}, {0x98D, 0x98E}, {0x991, 0x992}, {0x9A9, 0x9A9}, {0x9B1, 0x9B1}, {0x9B3, 0x9B5},
-{0x9BA, 0x9BB}, {0x9C5, 0x9C6}, {0x9C9, 0x9CA}, {0x9CF, 0x9D6}, {0x9D8, 0x9DB}, {0x9DE, 0x9DE}, {0x9E4, 0x9E5}, {0x9FF, 0xA00}, {0xA04, 0xA04}, {0xA0B, 0xA0E}, {0xA11, 0xA12}, {0xA29, 0xA29},
-{0xA31, 0xA31}, {0xA34, 0xA34}, {0xA37, 0xA37}, {0xA3A, 0xA3B}, {0xA3D, 0xA3D}, {0xA43, 0xA46}, {0xA49, 0xA4A}, {0xA4E, 0xA50}, {0xA52, 0xA58}, {0xA5D, 0xA5D}, {0xA5F, 0xA65}, {0xA77, 0xA80},
-{0xA84, 0xA84}, {0xA8E, 0xA8E}, {0xA92, 0xA92}, {0xAA9, 0xAA9}, {0xAB1, 0xAB1}, {0xAB4, 0xAB4}, {0xABA, 0xABB}, {0xAC6, 0xAC6}, {0xACA, 0xACA}, {0xACE, 0xACF}, {0xAD1, 0xADF}, {0xAE4, 0xAE5},
-{0xAF2, 0xAF8}, {0xB00, 0xB00}, {0xB04, 0xB04}, {0xB0D, 0xB0E}, {0xB11, 0xB12}, {0xB29, 0xB29}, {0xB31, 0xB31}, {0xB34, 0xB34}, {0xB3A, 0xB3B}, {0xB45, 0xB46}, {0xB49, 0xB4A}, {0xB4E, 0xB54},
-{0xB58, 0xB5B}, {0xB5E, 0xB5E}, {0xB64, 0xB65}, {0xB78, 0xB81}, {0xB84, 0xB84}, {0xB8B, 0xB8D}, {0xB91, 0xB91}, {0xB96, 0xB98}, {0xB9B, 0xB9B}, {0xB9D, 0xB9D}, {0xBA0, 0xBA2}, {0xBA5, 0xBA7},
-{0xBAB, 0xBAD}, {0xBBA, 0xBBD}, {0xBC3, 0xBC5}, {0xBC9, 0xBC9}, {0xBCE, 0xBCF}, {0xBD1, 0xBD6}, {0xBD8, 0xBE5}, {0xBFB, 0xBFF}, {0xC0D, 0xC0D}, {0xC11, 0xC11}, {0xC29, 0xC29}, {0xC3A, 0xC3C},
-{0xC45, 0xC45}, {0xC49, 0xC49}, {0xC4E, 0xC54}, {0xC57, 0xC57}, {0xC5B, 0xC5F}, {0xC64, 0xC65}, {0xC70, 0xC76}, {0xC8D, 0xC8D}, {0xC91, 0xC91}, {0xCA9, 0xCA9}, {0xCB4, 0xCB4}, {0xCBA, 0xCBB},
-{0xCC5, 0xCC5}, {0xCC9, 0xCC9}, {0xCCE, 0xCD4}, {0xCD7, 0xCDD}, {0xCDF, 0xCDF}, {0xCE4, 0xCE5}, {0xCF0, 0xCF0}, {0xCF3, 0xCFF}, {0xD0D, 0xD0D}, {0xD11, 0xD11}, {0xD45, 0xD45}, {0xD49, 0xD49},
-{0xD50, 0xD53}, {0xD64, 0xD65}, {0xD80, 0xD80}, {0xD84, 0xD84}, {0xD97, 0xD99}, {0xDB2, 0xDB2}, {0xDBC, 0xDBC}, {0xDBE, 0xDBF}, {0xDC7, 0xDC9}, {0xDCB, 0xDCE}, {0xDD5, 0xDD5}, {0xDD7, 0xDD7},
-{0xDE0, 0xDE5}, {0xDF0, 0xDF1}, {0xDF5, 0xE00}, {0xE3B, 0xE3E}, {0xE5C, 0xE80}, {0xE83, 0xE83}, {0xE85, 0xE85}, {0xE8B, 0xE8B}, {0xEA4, 0xEA4}, {0xEA6, 0xEA6}, {0xEBE, 0xEBF}, {0xEC5, 0xEC5},
-{0xEC7, 0xEC7}, {0xECE, 0xECF}, {0xEDA, 0xEDB}, {0xEE0, 0xEFF}, {0xF48, 0xF48}, {0xF6D, 0xF70}, {0xF98, 0xF98}, {0xFBD, 0xFBD}, {0xFCD, 0xFCD}, {0xFDB, 0xFFF}, {0x10C6, 0x10C6}, {0x10C8, 0x10CC},
-{0x10CE, 0x10CF}, {0x1249, 0x1249}, {0x124E, 0x124F}, {0x1257, 0x1257}, {0x1259, 0x1259}, {0x125E, 0x125F}, {0x1289, 0x1289}, {0x128E, 0x128F}, {0x12B1, 0x12B1}, {0x12B6, 0x12B7}, {0x12BF, 0x12BF},
-{0x12C1, 0x12C1}, {0x12C6, 0x12C7}, {0x12D7, 0x12D7}, {0x1311, 0x1311}, {0x1316, 0x1317}, {0x135B, 0x135C}, {0x137D, 0x137F}, {0x139A, 0x139F}, {0x13F6, 0x13F7}, {0x13FE, 0x13FF}, {0x169D, 0x169F},
-{0x16F9, 0x16FF}, {0x170D, 0x170D}, {0x1715, 0x171F}, {0x1737, 0x173F}, {0x1754, 0x175F}, {0x176D, 0x176D}, {0x1771, 0x1771}, {0x1774, 0x177F}, {0x17DE, 0x17DF}, {0x17EA, 0x17EF}, {0x17FA, 0x17FF},
-{0x180E, 0x180F}, {0x181A, 0x181F}, {0x1879, 0x187F}, {0x18AB, 0x18AF}, {0x18F6, 0x18FF}, {0x191F, 0x191F}, {0x192C, 0x192F}, {0x193C, 0x193F}, {0x1941, 0x1943}, {0x196E, 0x196F}, {0x1975, 0x197F},
-{0x19AC, 0x19AF}, {0x19CA, 0x19CF}, {0x19DB, 0x19DD}, {0x1A1C, 0x1A1D}, {0x1A5F, 0x1A5F}, {0x1A7D, 0x1A7E}, {0x1A8A, 0x1A8F}, {0x1A9A, 0x1A9F}, {0x1AAE, 0x1AAF}, {0x1AC1, 0x1AFF}, {0x1B4C, 0x1B4F},
-{0x1B7D, 0x1B7F}, {0x1BF4, 0x1BFB}, {0x1C38, 0x1C3A}, {0x1C4A, 0x1C4C}, {0x1C89, 0x1C8F}, {0x1CBB, 0x1CBC}, {0x1CC8, 0x1CCF}, {0x1CFB, 0x1CFF}, {0x1DFA, 0x1DFA}, {0x1F16, 0x1F17}, {0x1F1E, 0x1F1F},
-{0x1F46, 0x1F47}, {0x1F4E, 0x1F4F}, {0x1F58, 0x1F58}, {0x1F5A, 0x1F5A}, {0x1F5C, 0x1F5C}, {0x1F5E, 0x1F5E}, {0x1F7E, 0x1F7F}, {0x1FB5, 0x1FB5}, {0x1FC5, 0x1FC5}, {0x1FD4, 0x1FD5}, {0x1FDC, 0x1FDC},
-{0x1FF0, 0x1FF1}, {0x1FF5, 0x1FF5}, {0x1FFF, 0x1FFF}, {0x200B, 0x200F}, {0x202A, 0x202E}, {0x2060, 0x206F}, {0x2072, 0x2073}, {0x208F, 0x208F}, {0x209D, 0x209F}, {0x20C0, 0x20CF}, {0x20F1, 0x20FF},
-{0x218C, 0x218F}, {0x2427, 0x243F}, {0x244B, 0x245F}, {0x2B74, 0x2B75}, {0x2B96, 0x2B96}, {0x2C2F, 0x2C2F}, {0x2C5F, 0x2C5F}, {0x2CF4, 0x2CF8}, {0x2D26, 0x2D26}, {0x2D28, 0x2D2C}, {0x2D2E, 0x2D2F},
-{0x2D68, 0x2D6E}, {0x2D71, 0x2D7E}, {0x2D97, 0x2D9F}, {0x2DA7, 0x2DA7}, {0x2DAF, 0x2DAF}, {0x2DB7, 0x2DB7}, {0x2DBF, 0x2DBF}, {0x2DC7, 0x2DC7}, {0x2DCF, 0x2DCF}, {0x2DD7, 0x2DD7}, {0x2DDF, 0x2DDF},
-{0x2E53, 0x2E7F}, {0x2E9A, 0x2E9A}, {0x2EF4, 0x2EFF}, {0x2FD6, 0x2FEF}, {0x2FFC, 0x2FFF}, {0x3040, 0x3040}, {0x3097, 0x3098}, {0x3100, 0x3104}, {0x3130, 0x3130}, {0x318F, 0x318F}, {0x31E4, 0x31EF},
-{0x321F, 0x321F}, {0x9FFD, 0x9FFF}, {0xA48D, 0xA48F}, {0xA4C7, 0xA4CF}, {0xA62C, 0xA63F}, {0xA6F8, 0xA6FF}, {0xA7C0, 0xA7C1}, {0xA7CB, 0xA7F4}, {0xA82D, 0xA82F}, {0xA83A, 0xA83F}, {0xA878, 0xA87F},
-{0xA8C6, 0xA8CD}, {0xA8DA, 0xA8DF}, {0xA954, 0xA95E}, {0xA97D, 0xA97F}, {0xA9CE, 0xA9CE}, {0xA9DA, 0xA9DD}, {0xA9FF, 0xA9FF}, {0xAA37, 0xAA3F}, {0xAA4E, 0xAA4F}, {0xAA5A, 0xAA5B}, {0xAAC3, 0xAADA},
-{0xAAF7, 0xAB00}, {0xAB07, 0xAB08}, {0xAB0F, 0xAB10}, {0xAB17, 0xAB1F}, {0xAB27, 0xAB27}, {0xAB2F, 0xAB2F}, {0xAB6C, 0xAB6F}, {0xABEE, 0xABEF}, {0xABFA, 0xABFF}, {0xD7A4, 0xD7AF}, {0xD7C7, 0xD7CA},
-{0xD7FC, 0xF8FF}, {0xFA6E, 0xFA6F}, {0xFADA, 0xFAFF}, {0xFB07, 0xFB12}, {0xFB18, 0xFB1C}, {0xFB37, 0xFB37}, {0xFB3D, 0xFB3D}, {0xFB3F, 0xFB3F}, {0xFB42, 0xFB42}, {0xFB45, 0xFB45}, {0xFBC2, 0xFBD2},
-{0xFD40, 0xFD4F}, {0xFD90, 0xFD91}, {0xFDC8, 0xFDEF}, {0xFDFE, 0xFDFF}, {0xFE1A, 0xFE1F}, {0xFE53, 0xFE53}, {0xFE67, 0xFE67}, {0xFE6C, 0xFE6F}, {0xFE75, 0xFE75}, {0xFEFD, 0xFF00}, {0xFFBF, 0xFFC1},
-{0xFFC8, 0xFFC9}, {0xFFD0, 0xFFD1}, {0xFFD8, 0xFFD9}, {0xFFDD, 0xFFDF}, {0xFFE7, 0xFFE7}, {0xFFEF, 0xFFFB}, {0xFFFE, 0xFFFF}, {0x1000C, 0x1000C}, {0x10027, 0x10027}, {0x1003B, 0x1003B},
-{0x1003E, 0x1003E}, {0x1004E, 0x1004F}, {0x1005E, 0x1007F}, {0x100FB, 0x100FF}, {0x10103, 0x10106}, {0x10134, 0x10136}, {0x1018F, 0x1018F}, {0x1019D, 0x1019F}, {0x101A1, 0x101CF}, {0x101FE, 0x1027F},
-{0x1029D, 0x1029F}, {0x102D1, 0x102DF}, {0x102FC, 0x102FF}, {0x10324, 0x1032C}, {0x1034B, 0x1034F}, {0x1037B, 0x1037F}, {0x1039E, 0x1039E}, {0x103C4, 0x103C7}, {0x103D6, 0x103FF}, {0x1049E, 0x1049F},
-{0x104AA, 0x104AF}, {0x104D4, 0x104D7}, {0x104FC, 0x104FF}, {0x10528, 0x1052F}, {0x10564, 0x1056E}, {0x10570, 0x105FF}, {0x10737, 0x1073F}, {0x10756, 0x1075F}, {0x10768, 0x107FF}, {0x10806, 0x10807},
-{0x10809, 0x10809}, {0x10836, 0x10836}, {0x10839, 0x1083B}, {0x1083D, 0x1083E}, {0x10856, 0x10856}, {0x1089F, 0x108A6}, {0x108B0, 0x108DF}, {0x108F3, 0x108F3}, {0x108F6, 0x108FA}, {0x1091C, 0x1091E},
-{0x1093A, 0x1093E}, {0x10940, 0x1097F}, {0x109B8, 0x109BB}, {0x109D0, 0x109D1}, {0x10A04, 0x10A04}, {0x10A07, 0x10A0B}, {0x10A14, 0x10A14}, {0x10A18, 0x10A18}, {0x10A36, 0x10A37}, {0x10A3B, 0x10A3E},
-{0x10A49, 0x10A4F}, {0x10A59, 0x10A5F}, {0x10AA0, 0x10ABF}, {0x10AE7, 0x10AEA}, {0x10AF7, 0x10AFF}, {0x10B36, 0x10B38}, {0x10B56, 0x10B57}, {0x10B73, 0x10B77}, {0x10B92, 0x10B98}, {0x10B9D, 0x10BA8},
-{0x10BB0, 0x10BFF}, {0x10C49, 0x10C7F}, {0x10CB3, 0x10CBF}, {0x10CF3, 0x10CF9}, {0x10D28, 0x10D2F}, {0x10D3A, 0x10E5F}, {0x10E7F, 0x10E7F}, {0x10EAA, 0x10EAA}, {0x10EAE, 0x10EAF}, {0x10EB2, 0x10EFF},
-{0x10F28, 0x10F2F}, {0x10F5A, 0x10FAF}, {0x10FCC, 0x10FDF}, {0x10FF7, 0x10FFF}, {0x1104E, 0x11051}, {0x11070, 0x1107E}, {0x110BD, 0x110BD}, {0x110C2, 0x110CF}, {0x110E9, 0x110EF}, {0x110FA, 0x110FF},
-{0x11135, 0x11135}, {0x11148, 0x1114F}, {0x11177, 0x1117F}, {0x111E0, 0x111E0}, {0x111F5, 0x111FF}, {0x11212, 0x11212}, {0x1123F, 0x1127F}, {0x11287, 0x11287}, {0x11289, 0x11289}, {0x1128E, 0x1128E},
-{0x1129E, 0x1129E}, {0x112AA, 0x112AF}, {0x112EB, 0x112EF}, {0x112FA, 0x112FF}, {0x11304, 0x11304}, {0x1130D, 0x1130E}, {0x11311, 0x11312}, {0x11329, 0x11329}, {0x11331, 0x11331}, {0x11334, 0x11334},
-{0x1133A, 0x1133A}, {0x11345, 0x11346}, {0x11349, 0x1134A}, {0x1134E, 0x1134F}, {0x11351, 0x11356}, {0x11358, 0x1135C}, {0x11364, 0x11365}, {0x1136D, 0x1136F}, {0x11375, 0x113FF}, {0x1145C, 0x1145C},
-{0x11462, 0x1147F}, {0x114C8, 0x114CF}, {0x114DA, 0x1157F}, {0x115B6, 0x115B7}, {0x115DE, 0x115FF}, {0x11645, 0x1164F}, {0x1165A, 0x1165F}, {0x1166D, 0x1167F}, {0x116B9, 0x116BF}, {0x116CA, 0x116FF},
-{0x1171B, 0x1171C}, {0x1172C, 0x1172F}, {0x11740, 0x117FF}, {0x1183C, 0x1189F}, {0x118F3, 0x118FE}, {0x11907, 0x11908}, {0x1190A, 0x1190B}, {0x11914, 0x11914}, {0x11917, 0x11917}, {0x11936, 0x11936},
-{0x11939, 0x1193A}, {0x11947, 0x1194F}, {0x1195A, 0x1199F}, {0x119A8, 0x119A9}, {0x119D8, 0x119D9}, {0x119E5, 0x119FF}, {0x11A48, 0x11A4F}, {0x11AA3, 0x11ABF}, {0x11AF9, 0x11BFF}, {0x11C09, 0x11C09},
-{0x11C37, 0x11C37}, {0x11C46, 0x11C4F}, {0x11C6D, 0x11C6F}, {0x11C90, 0x11C91}, {0x11CA8, 0x11CA8}, {0x11CB7, 0x11CFF}, {0x11D07, 0x11D07}, {0x11D0A, 0x11D0A}, {0x11D37, 0x11D39}, {0x11D3B, 0x11D3B},
-{0x11D3E, 0x11D3E}, {0x11D48, 0x11D4F}, {0x11D5A, 0x11D5F}, {0x11D66, 0x11D66}, {0x11D69, 0x11D69}, {0x11D8F, 0x11D8F}, {0x11D92, 0x11D92}, {0x11D99, 0x11D9F}, {0x11DAA, 0x11EDF}, {0x11EF9, 0x11FAF},
-{0x11FB1, 0x11FBF}, {0x11FF2, 0x11FFE}, {0x1239A, 0x123FF}, {0x1246F, 0x1246F}, {0x12475, 0x1247F}, {0x12544, 0x12FFF}, {0x1342F, 0x143FF}, {0x14647, 0x167FF}, {0x16A39, 0x16A3F}, {0x16A5F, 0x16A5F},
-{0x16A6A, 0x16A6D}, {0x16A70, 0x16ACF}, {0x16AEE, 0x16AEF}, {0x16AF6, 0x16AFF}, {0x16B46, 0x16B4F}, {0x16B5A, 0x16B5A}, {0x16B62, 0x16B62}, {0x16B78, 0x16B7C}, {0x16B90, 0x16E3F}, {0x16E9B, 0x16EFF},
-{0x16F4B, 0x16F4E}, {0x16F88, 0x16F8E}, {0x16FA0, 0x16FDF}, {0x16FE5, 0x16FEF}, {0x16FF2, 0x16FFF}, {0x187F8, 0x187FF}, {0x18CD6, 0x18CFF}, {0x18D09, 0x1AFFF}, {0x1B11F, 0x1B14F}, {0x1B153, 0x1B163},
-{0x1B168, 0x1B16F}, {0x1B2FC, 0x1BBFF}, {0x1BC6B, 0x1BC6F}, {0x1BC7D, 0x1BC7F}, {0x1BC89, 0x1BC8F}, {0x1BC9A, 0x1BC9B}, {0x1BCA0, 0x1CFFF}, {0x1D0F6, 0x1D0FF}, {0x1D127, 0x1D128}, {0x1D173, 0x1D17A},
-{0x1D1E9, 0x1D1FF}, {0x1D246, 0x1D2DF}, {0x1D2F4, 0x1D2FF}, {0x1D357, 0x1D35F}, {0x1D379, 0x1D3FF}, {0x1D455, 0x1D455}, {0x1D49D, 0x1D49D}, {0x1D4A0, 0x1D4A1}, {0x1D4A3, 0x1D4A4}, {0x1D4A7, 0x1D4A8},
-{0x1D4AD, 0x1D4AD}, {0x1D4BA, 0x1D4BA}, {0x1D4BC, 0x1D4BC}, {0x1D4C4, 0x1D4C4}, {0x1D506, 0x1D506}, {0x1D50B, 0x1D50C}, {0x1D515, 0x1D515}, {0x1D51D, 0x1D51D}, {0x1D53A, 0x1D53A}, {0x1D53F, 0x1D53F},
-{0x1D545, 0x1D545}, {0x1D547, 0x1D549}, {0x1D551, 0x1D551}, {0x1D6A6, 0x1D6A7}, {0x1D7CC, 0x1D7CD}, {0x1DA8C, 0x1DA9A}, {0x1DAA0, 0x1DAA0}, {0x1DAB0, 0x1DFFF}, {0x1E007, 0x1E007}, {0x1E019, 0x1E01A},
-{0x1E022, 0x1E022}, {0x1E025, 0x1E025}, {0x1E02B, 0x1E0FF}, {0x1E12D, 0x1E12F}, {0x1E13E, 0x1E13F}, {0x1E14A, 0x1E14D}, {0x1E150, 0x1E2BF}, {0x1E2FA, 0x1E2FE}, {0x1E300, 0x1E7FF}, {0x1E8C5, 0x1E8C6},
-{0x1E8D7, 0x1E8FF}, {0x1E94C, 0x1E94F}, {0x1E95A, 0x1E95D}, {0x1E960, 0x1EC70}, {0x1ECB5, 0x1ED00}, {0x1ED3E, 0x1EDFF}, {0x1EE04, 0x1EE04}, {0x1EE20, 0x1EE20}, {0x1EE23, 0x1EE23}, {0x1EE25, 0x1EE26},
-{0x1EE28, 0x1EE28}, {0x1EE33, 0x1EE33}, {0x1EE38, 0x1EE38}, {0x1EE3A, 0x1EE3A}, {0x1EE3C, 0x1EE41}, {0x1EE43, 0x1EE46}, {0x1EE48, 0x1EE48}, {0x1EE4A, 0x1EE4A}, {0x1EE4C, 0x1EE4C}, {0x1EE50, 0x1EE50},
-{0x1EE53, 0x1EE53}, {0x1EE55, 0x1EE56}, {0x1EE58, 0x1EE58}, {0x1EE5A, 0x1EE5A}, {0x1EE5C, 0x1EE5C}, {0x1EE5E, 0x1EE5E}, {0x1EE60, 0x1EE60}, {0x1EE63, 0x1EE63}, {0x1EE65, 0x1EE66}, {0x1EE6B, 0x1EE6B},
-{0x1EE73, 0x1EE73}, {0x1EE78, 0x1EE78}, {0x1EE7D, 0x1EE7D}, {0x1EE7F, 0x1EE7F}, {0x1EE8A, 0x1EE8A}, {0x1EE9C, 0x1EEA0}, {0x1EEA4, 0x1EEA4}, {0x1EEAA, 0x1EEAA}, {0x1EEBC, 0x1EEEF}, {0x1EEF2, 0x1EFFF},
-{0x1F02C, 0x1F02F}, {0x1F094, 0x1F09F}, {0x1F0AF, 0x1F0B0}, {0x1F0C0, 0x1F0C0}, {0x1F0D0, 0x1F0D0}, {0x1F0F6, 0x1F0FF}, {0x1F1AE, 0x1F1E5}, {0x1F203, 0x1F20F}, {0x1F23C, 0x1F23F}, {0x1F249, 0x1F24F},
-{0x1F252, 0x1F25F}, {0x1F266, 0x1F2FF}, {0x1F6D8, 0x1F6DF}, {0x1F6ED, 0x1F6EF}, {0x1F6FD, 0x1F6FF}, {0x1F774, 0x1F77F}, {0x1F7D9, 0x1F7DF}, {0x1F7EC, 0x1F7FF}, {0x1F80C, 0x1F80F}, {0x1F848, 0x1F84F},
-{0x1F85A, 0x1F85F}, {0x1F888, 0x1F88F}, {0x1F8AE, 0x1F8AF}, {0x1F8B2, 0x1F8FF}, {0x1F979, 0x1F979}, {0x1F9CC, 0x1F9CC}, {0x1FA54, 0x1FA5F}, {0x1FA6E, 0x1FA6F}, {0x1FA75, 0x1FA77}, {0x1FA7B, 0x1FA7F},
-{0x1FA87, 0x1FA8F}, {0x1FAA9, 0x1FAAF}, {0x1FAB7, 0x1FABF}, {0x1FAC3, 0x1FACF}, {0x1FAD7, 0x1FAFF}, {0x1FB93, 0x1FB93}, {0x1FBCB, 0x1FBEF}, {0x1FBFA, 0x1FFFF}, {0x2A6DE, 0x2A6FF}, {0x2B735, 0x2B73F},
-{0x2B81E, 0x2B81F}, {0x2CEA2, 0x2CEAF}, {0x2EBE1, 0x2F7FF}, {0x2FA1E, 0x2FFFF}, {0x3134B, 0xE00FF}, {0xE01F0, 0x10FFFF},
-};
-
-static const std::multimap<uint32_t, uint32_t> nfd_map = {
-{0xC0, 0x41}, {0xC0, 0x300}, {0xC1, 0x41}, {0xC1, 0x301}, {0xC2, 0x41}, {0xC2, 0x302}, {0xC3, 0x41}, {0xC3, 0x303}, {0xC4, 0x41}, {0xC4, 0x308}, {0xC5, 0x41}, {0xC5, 0x30A}, {0xC7, 0x43},
-{0xC7, 0x327}, {0xC8, 0x45}, {0xC8, 0x300}, {0xC9, 0x45}, {0xC9, 0x301}, {0xCA, 0x45}, {0xCA, 0x302}, {0xCB, 0x45}, {0xCB, 0x308}, {0xCC, 0x49}, {0xCC, 0x300}, {0xCD, 0x49}, {0xCD, 0x301},
-{0xCE, 0x49}, {0xCE, 0x302}, {0xCF, 0x49}, {0xCF, 0x308}, {0xD1, 0x4E}, {0xD1, 0x303}, {0xD2, 0x4F}, {0xD2, 0x300}, {0xD3, 0x4F}, {0xD3, 0x301}, {0xD4, 0x4F}, {0xD4, 0x302}, {0xD5, 0x4F},
-{0xD5, 0x303}, {0xD6, 0x4F}, {0xD6, 0x308}, {0xD9, 0x55}, {0xD9, 0x300}, {0xDA, 0x55}, {0xDA, 0x301}, {0xDB, 0x55}, {0xDB, 0x302}, {0xDC, 0x55}, {0xDC, 0x308}, {0xDD, 0x59}, {0xDD, 0x301},
-{0xE0, 0x61}, {0xE0, 0x300}, {0xE1, 0x61}, {0xE1, 0x301}, {0xE2, 0x61}, {0xE2, 0x302}, {0xE3, 0x61}, {0xE3, 0x303}, {0xE4, 0x61}, {0xE4, 0x308}, {0xE5, 0x61}, {0xE5, 0x30A}, {0xE7, 0x63},
-{0xE7, 0x327}, {0xE8, 0x65}, {0xE8, 0x300}, {0xE9, 0x65}, {0xE9, 0x301}, {0xEA, 0x65}, {0xEA, 0x302}, {0xEB, 0x65}, {0xEB, 0x308}, {0xEC, 0x69}, {0xEC, 0x300}, {0xED, 0x69}, {0xED, 0x301},
-{0xEE, 0x69}, {0xEE, 0x302}, {0xEF, 0x69}, {0xEF, 0x308}, {0xF1, 0x6E}, {0xF1, 0x303}, {0xF2, 0x6F}, {0xF2, 0x300}, {0xF3, 0x6F}, {0xF3, 0x301}, {0xF4, 0x6F}, {0xF4, 0x302}, {0xF5, 0x6F},
-{0xF5, 0x303}, {0xF6, 0x6F}, {0xF6, 0x308}, {0xF9, 0x75}, {0xF9, 0x300}, {0xFA, 0x75}, {0xFA, 0x301}, {0xFB, 0x75}, {0xFB, 0x302}, {0xFC, 0x75}, {0xFC, 0x308}, {0xFD, 0x79}, {0xFD, 0x301},
-{0xFF, 0x79}, {0xFF, 0x308}, {0x100, 0x41}, {0x100, 0x304}, {0x101, 0x61}, {0x101, 0x304}, {0x102, 0x41}, {0x102, 0x306}, {0x103, 0x61}, {0x103, 0x306}, {0x104, 0x41}, {0x104, 0x328}, {0x105, 0x61},
-{0x105, 0x328}, {0x106, 0x43}, {0x106, 0x301}, {0x107, 0x63}, {0x107, 0x301}, {0x108, 0x43}, {0x108, 0x302}, {0x109, 0x63}, {0x109, 0x302}, {0x10A, 0x43}, {0x10A, 0x307}, {0x10B, 0x63},
-{0x10B, 0x307}, {0x10C, 0x43}, {0x10C, 0x30C}, {0x10D, 0x63}, {0x10D, 0x30C}, {0x10E, 0x44}, {0x10E, 0x30C}, {0x10F, 0x64}, {0x10F, 0x30C}, {0x112, 0x45}, {0x112, 0x304}, {0x113, 0x65},
-{0x113, 0x304}, {0x114, 0x45}, {0x114, 0x306}, {0x115, 0x65}, {0x115, 0x306}, {0x116, 0x45}, {0x116, 0x307}, {0x117, 0x65}, {0x117, 0x307}, {0x118, 0x45}, {0x118, 0x328}, {0x119, 0x65},
-{0x119, 0x328}, {0x11A, 0x45}, {0x11A, 0x30C}, {0x11B, 0x65}, {0x11B, 0x30C}, {0x11C, 0x47}, {0x11C, 0x302}, {0x11D, 0x67}, {0x11D, 0x302}, {0x11E, 0x47}, {0x11E, 0x306}, {0x11F, 0x67},
-{0x11F, 0x306}, {0x120, 0x47}, {0x120, 0x307}, {0x121, 0x67}, {0x121, 0x307}, {0x122, 0x47}, {0x122, 0x327}, {0x123, 0x67}, {0x123, 0x327}, {0x124, 0x48}, {0x124, 0x302}, {0x125, 0x68},
-{0x125, 0x302}, {0x128, 0x49}, {0x128, 0x303}, {0x129, 0x69}, {0x129, 0x303}, {0x12A, 0x49}, {0x12A, 0x304}, {0x12B, 0x69}, {0x12B, 0x304}, {0x12C, 0x49}, {0x12C, 0x306}, {0x12D, 0x69},
-{0x12D, 0x306}, {0x12E, 0x49}, {0x12E, 0x328}, {0x12F, 0x69}, {0x12F, 0x328}, {0x130, 0x49}, {0x130, 0x307}, {0x134, 0x4A}, {0x134, 0x302}, {0x135, 0x6A}, {0x135, 0x302}, {0x136, 0x4B},
-{0x136, 0x327}, {0x137, 0x6B}, {0x137, 0x327}, {0x139, 0x4C}, {0x139, 0x301}, {0x13A, 0x6C}, {0x13A, 0x301}, {0x13B, 0x4C}, {0x13B, 0x327}, {0x13C, 0x6C}, {0x13C, 0x327}, {0x13D, 0x4C},
-{0x13D, 0x30C}, {0x13E, 0x6C}, {0x13E, 0x30C}, {0x143, 0x4E}, {0x143, 0x301}, {0x144, 0x6E}, {0x144, 0x301}, {0x145, 0x4E}, {0x145, 0x327}, {0x146, 0x6E}, {0x146, 0x327}, {0x147, 0x4E},
-{0x147, 0x30C}, {0x148, 0x6E}, {0x148, 0x30C}, {0x14C, 0x4F}, {0x14C, 0x304}, {0x14D, 0x6F}, {0x14D, 0x304}, {0x14E, 0x4F}, {0x14E, 0x306}, {0x14F, 0x6F}, {0x14F, 0x306}, {0x150, 0x4F},
-{0x150, 0x30B}, {0x151, 0x6F}, {0x151, 0x30B}, {0x154, 0x52}, {0x154, 0x301}, {0x155, 0x72}, {0x155, 0x301}, {0x156, 0x52}, {0x156, 0x327}, {0x157, 0x72}, {0x157, 0x327}, {0x158, 0x52},
-{0x158, 0x30C}, {0x159, 0x72}, {0x159, 0x30C}, {0x15A, 0x53}, {0x15A, 0x301}, {0x15B, 0x73}, {0x15B, 0x301}, {0x15C, 0x53}, {0x15C, 0x302}, {0x15D, 0x73}, {0x15D, 0x302}, {0x15E, 0x53},
-{0x15E, 0x327}, {0x15F, 0x73}, {0x15F, 0x327}, {0x160, 0x53}, {0x160, 0x30C}, {0x161, 0x73}, {0x161, 0x30C}, {0x162, 0x54}, {0x162, 0x327}, {0x163, 0x74}, {0x163, 0x327}, {0x164, 0x54},
-{0x164, 0x30C}, {0x165, 0x74}, {0x165, 0x30C}, {0x168, 0x55}, {0x168, 0x303}, {0x169, 0x75}, {0x169, 0x303}, {0x16A, 0x55}, {0x16A, 0x304}, {0x16B, 0x75}, {0x16B, 0x304}, {0x16C, 0x55},
-{0x16C, 0x306}, {0x16D, 0x75}, {0x16D, 0x306}, {0x16E, 0x55}, {0x16E, 0x30A}, {0x16F, 0x75}, {0x16F, 0x30A}, {0x170, 0x55}, {0x170, 0x30B}, {0x171, 0x75}, {0x171, 0x30B}, {0x172, 0x55},
-{0x172, 0x328}, {0x173, 0x75}, {0x173, 0x328}, {0x174, 0x57}, {0x174, 0x302}, {0x175, 0x77}, {0x175, 0x302}, {0x176, 0x59}, {0x176, 0x302}, {0x177, 0x79}, {0x177, 0x302}, {0x178, 0x59},
-{0x178, 0x308}, {0x179, 0x5A}, {0x179, 0x301}, {0x17A, 0x7A}, {0x17A, 0x301}, {0x17B, 0x5A}, {0x17B, 0x307}, {0x17C, 0x7A}, {0x17C, 0x307}, {0x17D, 0x5A}, {0x17D, 0x30C}, {0x17E, 0x7A},
-{0x17E, 0x30C}, {0x1A0, 0x4F}, {0x1A0, 0x31B}, {0x1A1, 0x6F}, {0x1A1, 0x31B}, {0x1AF, 0x55}, {0x1AF, 0x31B}, {0x1B0, 0x75}, {0x1B0, 0x31B}, {0x1CD, 0x41}, {0x1CD, 0x30C}, {0x1CE, 0x61},
-{0x1CE, 0x30C}, {0x1CF, 0x49}, {0x1CF, 0x30C}, {0x1D0, 0x69}, {0x1D0, 0x30C}, {0x1D1, 0x4F}, {0x1D1, 0x30C}, {0x1D2, 0x6F}, {0x1D2, 0x30C}, {0x1D3, 0x55}, {0x1D3, 0x30C}, {0x1D4, 0x75},
-{0x1D4, 0x30C}, {0x1D5, 0x55}, {0x1D5, 0x308}, {0x1D5, 0x304}, {0x1D6, 0x75}, {0x1D6, 0x308}, {0x1D6, 0x304}, {0x1D7, 0x55}, {0x1D7, 0x308}, {0x1D7, 0x301}, {0x1D8, 0x75}, {0x1D8, 0x308},
-{0x1D8, 0x301}, {0x1D9, 0x55}, {0x1D9, 0x308}, {0x1D9, 0x30C}, {0x1DA, 0x75}, {0x1DA, 0x308}, {0x1DA, 0x30C}, {0x1DB, 0x55}, {0x1DB, 0x308}, {0x1DB, 0x300}, {0x1DC, 0x75}, {0x1DC, 0x308},
-{0x1DC, 0x300}, {0x1DE, 0x41}, {0x1DE, 0x308}, {0x1DE, 0x304}, {0x1DF, 0x61}, {0x1DF, 0x308}, {0x1DF, 0x304}, {0x1E0, 0x41}, {0x1E0, 0x307}, {0x1E0, 0x304}, {0x1E1, 0x61}, {0x1E1, 0x307},
-{0x1E1, 0x304}, {0x1E2, 0xC6}, {0x1E2, 0x304}, {0x1E3, 0xE6}, {0x1E3, 0x304}, {0x1E6, 0x47}, {0x1E6, 0x30C}, {0x1E7, 0x67}, {0x1E7, 0x30C}, {0x1E8, 0x4B}, {0x1E8, 0x30C}, {0x1E9, 0x6B},
-{0x1E9, 0x30C}, {0x1EA, 0x4F}, {0x1EA, 0x328}, {0x1EB, 0x6F}, {0x1EB, 0x328}, {0x1EC, 0x4F}, {0x1EC, 0x328}, {0x1EC, 0x304}, {0x1ED, 0x6F}, {0x1ED, 0x328}, {0x1ED, 0x304}, {0x1EE, 0x1B7},
-{0x1EE, 0x30C}, {0x1EF, 0x292}, {0x1EF, 0x30C}, {0x1F0, 0x6A}, {0x1F0, 0x30C}, {0x1F4, 0x47}, {0x1F4, 0x301}, {0x1F5, 0x67}, {0x1F5, 0x301}, {0x1F8, 0x4E}, {0x1F8, 0x300}, {0x1F9, 0x6E},
-{0x1F9, 0x300}, {0x1FA, 0x41}, {0x1FA, 0x30A}, {0x1FA, 0x301}, {0x1FB, 0x61}, {0x1FB, 0x30A}, {0x1FB, 0x301}, {0x1FC, 0xC6}, {0x1FC, 0x301}, {0x1FD, 0xE6}, {0x1FD, 0x301}, {0x1FE, 0xD8},
-{0x1FE, 0x301}, {0x1FF, 0xF8}, {0x1FF, 0x301}, {0x200, 0x41}, {0x200, 0x30F}, {0x201, 0x61}, {0x201, 0x30F}, {0x202, 0x41}, {0x202, 0x311}, {0x203, 0x61}, {0x203, 0x311}, {0x204, 0x45},
-{0x204, 0x30F}, {0x205, 0x65}, {0x205, 0x30F}, {0x206, 0x45}, {0x206, 0x311}, {0x207, 0x65}, {0x207, 0x311}, {0x208, 0x49}, {0x208, 0x30F}, {0x209, 0x69}, {0x209, 0x30F}, {0x20A, 0x49},
-{0x20A, 0x311}, {0x20B, 0x69}, {0x20B, 0x311}, {0x20C, 0x4F}, {0x20C, 0x30F}, {0x20D, 0x6F}, {0x20D, 0x30F}, {0x20E, 0x4F}, {0x20E, 0x311}, {0x20F, 0x6F}, {0x20F, 0x311}, {0x210, 0x52},
-{0x210, 0x30F}, {0x211, 0x72}, {0x211, 0x30F}, {0x212, 0x52}, {0x212, 0x311}, {0x213, 0x72}, {0x213, 0x311}, {0x214, 0x55}, {0x214, 0x30F}, {0x215, 0x75}, {0x215, 0x30F}, {0x216, 0x55},
-{0x216, 0x311}, {0x217, 0x75}, {0x217, 0x311}, {0x218, 0x53}, {0x218, 0x326}, {0x219, 0x73}, {0x219, 0x326}, {0x21A, 0x54}, {0x21A, 0x326}, {0x21B, 0x74}, {0x21B, 0x326}, {0x21E, 0x48},
-{0x21E, 0x30C}, {0x21F, 0x68}, {0x21F, 0x30C}, {0x226, 0x41}, {0x226, 0x307}, {0x227, 0x61}, {0x227, 0x307}, {0x228, 0x45}, {0x228, 0x327}, {0x229, 0x65}, {0x229, 0x327}, {0x22A, 0x4F},
-{0x22A, 0x308}, {0x22A, 0x304}, {0x22B, 0x6F}, {0x22B, 0x308}, {0x22B, 0x304}, {0x22C, 0x4F}, {0x22C, 0x303}, {0x22C, 0x304}, {0x22D, 0x6F}, {0x22D, 0x303}, {0x22D, 0x304}, {0x22E, 0x4F},
-{0x22E, 0x307}, {0x22F, 0x6F}, {0x22F, 0x307}, {0x230, 0x4F}, {0x230, 0x307}, {0x230, 0x304}, {0x231, 0x6F}, {0x231, 0x307}, {0x231, 0x304}, {0x232, 0x59}, {0x232, 0x304}, {0x233, 0x79},
-{0x233, 0x304}, {0x340, 0x300}, {0x341, 0x301}, {0x343, 0x313}, {0x344, 0x308}, {0x344, 0x301}, {0x374, 0x2B9}, {0x37E, 0x3B}, {0x385, 0xA8}, {0x385, 0x301}, {0x386, 0x391}, {0x386, 0x301},
-{0x387, 0xB7}, {0x388, 0x395}, {0x388, 0x301}, {0x389, 0x397}, {0x389, 0x301}, {0x38A, 0x399}, {0x38A, 0x301}, {0x38C, 0x39F}, {0x38C, 0x301}, {0x38E, 0x3A5}, {0x38E, 0x301}, {0x38F, 0x3A9},
-{0x38F, 0x301}, {0x390, 0x3B9}, {0x390, 0x308}, {0x390, 0x301}, {0x3AA, 0x399}, {0x3AA, 0x308}, {0x3AB, 0x3A5}, {0x3AB, 0x308}, {0x3AC, 0x3B1}, {0x3AC, 0x301}, {0x3AD, 0x3B5}, {0x3AD, 0x301},
-{0x3AE, 0x3B7}, {0x3AE, 0x301}, {0x3AF, 0x3B9}, {0x3AF, 0x301}, {0x3B0, 0x3C5}, {0x3B0, 0x308}, {0x3B0, 0x301}, {0x3CA, 0x3B9}, {0x3CA, 0x308}, {0x3CB, 0x3C5}, {0x3CB, 0x308}, {0x3CC, 0x3BF},
-{0x3CC, 0x301}, {0x3CD, 0x3C5}, {0x3CD, 0x301}, {0x3CE, 0x3C9}, {0x3CE, 0x301}, {0x3D3, 0x3D2}, {0x3D3, 0x301}, {0x3D4, 0x3D2}, {0x3D4, 0x308}, {0x400, 0x415}, {0x400, 0x300}, {0x401, 0x415},
-{0x401, 0x308}, {0x403, 0x413}, {0x403, 0x301}, {0x407, 0x406}, {0x407, 0x308}, {0x40C, 0x41A}, {0x40C, 0x301}, {0x40D, 0x418}, {0x40D, 0x300}, {0x40E, 0x423}, {0x40E, 0x306}, {0x419, 0x418},
-{0x419, 0x306}, {0x439, 0x438}, {0x439, 0x306}, {0x450, 0x435}, {0x450, 0x300}, {0x451, 0x435}, {0x451, 0x308}, {0x453, 0x433}, {0x453, 0x301}, {0x457, 0x456}, {0x457, 0x308}, {0x45C, 0x43A},
-{0x45C, 0x301}, {0x45D, 0x438}, {0x45D, 0x300}, {0x45E, 0x443}, {0x45E, 0x306}, {0x476, 0x474}, {0x476, 0x30F}, {0x477, 0x475}, {0x477, 0x30F}, {0x4C1, 0x416}, {0x4C1, 0x306}, {0x4C2, 0x436},
-{0x4C2, 0x306}, {0x4D0, 0x410}, {0x4D0, 0x306}, {0x4D1, 0x430}, {0x4D1, 0x306}, {0x4D2, 0x410}, {0x4D2, 0x308}, {0x4D3, 0x430}, {0x4D3, 0x308}, {0x4D6, 0x415}, {0x4D6, 0x306}, {0x4D7, 0x435},
-{0x4D7, 0x306}, {0x4DA, 0x4D8}, {0x4DA, 0x308}, {0x4DB, 0x4D9}, {0x4DB, 0x308}, {0x4DC, 0x416}, {0x4DC, 0x308}, {0x4DD, 0x436}, {0x4DD, 0x308}, {0x4DE, 0x417}, {0x4DE, 0x308}, {0x4DF, 0x437},
-{0x4DF, 0x308}, {0x4E2, 0x418}, {0x4E2, 0x304}, {0x4E3, 0x438}, {0x4E3, 0x304}, {0x4E4, 0x418}, {0x4E4, 0x308}, {0x4E5, 0x438}, {0x4E5, 0x308}, {0x4E6, 0x41E}, {0x4E6, 0x308}, {0x4E7, 0x43E},
-{0x4E7, 0x308}, {0x4EA, 0x4E8}, {0x4EA, 0x308}, {0x4EB, 0x4E9}, {0x4EB, 0x308}, {0x4EC, 0x42D}, {0x4EC, 0x308}, {0x4ED, 0x44D}, {0x4ED, 0x308}, {0x4EE, 0x423}, {0x4EE, 0x304}, {0x4EF, 0x443},
-{0x4EF, 0x304}, {0x4F0, 0x423}, {0x4F0, 0x308}, {0x4F1, 0x443}, {0x4F1, 0x308}, {0x4F2, 0x423}, {0x4F2, 0x30B}, {0x4F3, 0x443}, {0x4F3, 0x30B}, {0x4F4, 0x427}, {0x4F4, 0x308}, {0x4F5, 0x447},
-{0x4F5, 0x308}, {0x4F8, 0x42B}, {0x4F8, 0x308}, {0x4F9, 0x44B}, {0x4F9, 0x308}, {0x622, 0x627}, {0x622, 0x653}, {0x623, 0x627}, {0x623, 0x654}, {0x624, 0x648}, {0x624, 0x654}, {0x625, 0x627},
-{0x625, 0x655}, {0x626, 0x64A}, {0x626, 0x654}, {0x6C0, 0x6D5}, {0x6C0, 0x654}, {0x6C2, 0x6C1}, {0x6C2, 0x654}, {0x6D3, 0x6D2}, {0x6D3, 0x654}, {0x929, 0x928}, {0x929, 0x93C}, {0x931, 0x930},
-{0x931, 0x93C}, {0x934, 0x933}, {0x934, 0x93C}, {0x958, 0x915}, {0x958, 0x93C}, {0x959, 0x916}, {0x959, 0x93C}, {0x95A, 0x917}, {0x95A, 0x93C}, {0x95B, 0x91C}, {0x95B, 0x93C}, {0x95C, 0x921},
-{0x95C, 0x93C}, {0x95D, 0x922}, {0x95D, 0x93C}, {0x95E, 0x92B}, {0x95E, 0x93C}, {0x95F, 0x92F}, {0x95F, 0x93C}, {0x9CB, 0x9C7}, {0x9CB, 0x9BE}, {0x9CC, 0x9C7}, {0x9CC, 0x9D7}, {0x9DC, 0x9A1},
-{0x9DC, 0x9BC}, {0x9DD, 0x9A2}, {0x9DD, 0x9BC}, {0x9DF, 0x9AF}, {0x9DF, 0x9BC}, {0xA33, 0xA32}, {0xA33, 0xA3C}, {0xA36, 0xA38}, {0xA36, 0xA3C}, {0xA59, 0xA16}, {0xA59, 0xA3C}, {0xA5A, 0xA17},
-{0xA5A, 0xA3C}, {0xA5B, 0xA1C}, {0xA5B, 0xA3C}, {0xA5E, 0xA2B}, {0xA5E, 0xA3C}, {0xB48, 0xB47}, {0xB48, 0xB56}, {0xB4B, 0xB47}, {0xB4B, 0xB3E}, {0xB4C, 0xB47}, {0xB4C, 0xB57}, {0xB5C, 0xB21},
-{0xB5C, 0xB3C}, {0xB5D, 0xB22}, {0xB5D, 0xB3C}, {0xB94, 0xB92}, {0xB94, 0xBD7}, {0xBCA, 0xBC6}, {0xBCA, 0xBBE}, {0xBCB, 0xBC7}, {0xBCB, 0xBBE}, {0xBCC, 0xBC6}, {0xBCC, 0xBD7}, {0xC48, 0xC46},
-{0xC48, 0xC56}, {0xCC0, 0xCBF}, {0xCC0, 0xCD5}, {0xCC7, 0xCC6}, {0xCC7, 0xCD5}, {0xCC8, 0xCC6}, {0xCC8, 0xCD6}, {0xCCA, 0xCC6}, {0xCCA, 0xCC2}, {0xCCB, 0xCC6}, {0xCCB, 0xCC2}, {0xCCB, 0xCD5},
-{0xD4A, 0xD46}, {0xD4A, 0xD3E}, {0xD4B, 0xD47}, {0xD4B, 0xD3E}, {0xD4C, 0xD46}, {0xD4C, 0xD57}, {0xDDA, 0xDD9}, {0xDDA, 0xDCA}, {0xDDC, 0xDD9}, {0xDDC, 0xDCF}, {0xDDD, 0xDD9}, {0xDDD, 0xDCF},
-{0xDDD, 0xDCA}, {0xDDE, 0xDD9}, {0xDDE, 0xDDF}, {0xF43, 0xF42}, {0xF43, 0xFB7}, {0xF4D, 0xF4C}, {0xF4D, 0xFB7}, {0xF52, 0xF51}, {0xF52, 0xFB7}, {0xF57, 0xF56}, {0xF57, 0xFB7}, {0xF5C, 0xF5B},
-{0xF5C, 0xFB7}, {0xF69, 0xF40}, {0xF69, 0xFB5}, {0xF73, 0xF71}, {0xF73, 0xF72}, {0xF75, 0xF71}, {0xF75, 0xF74}, {0xF76, 0xFB2}, {0xF76, 0xF80}, {0xF78, 0xFB3}, {0xF78, 0xF80}, {0xF81, 0xF71},
-{0xF81, 0xF80}, {0xF93, 0xF92}, {0xF93, 0xFB7}, {0xF9D, 0xF9C}, {0xF9D, 0xFB7}, {0xFA2, 0xFA1}, {0xFA2, 0xFB7}, {0xFA7, 0xFA6}, {0xFA7, 0xFB7}, {0xFAC, 0xFAB}, {0xFAC, 0xFB7}, {0xFB9, 0xF90},
-{0xFB9, 0xFB5}, {0x1026, 0x1025}, {0x1026, 0x102E}, {0x1B06, 0x1B05}, {0x1B06, 0x1B35}, {0x1B08, 0x1B07}, {0x1B08, 0x1B35}, {0x1B0A, 0x1B09}, {0x1B0A, 0x1B35}, {0x1B0C, 0x1B0B}, {0x1B0C, 0x1B35},
-{0x1B0E, 0x1B0D}, {0x1B0E, 0x1B35}, {0x1B12, 0x1B11}, {0x1B12, 0x1B35}, {0x1B3B, 0x1B3A}, {0x1B3B, 0x1B35}, {0x1B3D, 0x1B3C}, {0x1B3D, 0x1B35}, {0x1B40, 0x1B3E}, {0x1B40, 0x1B35}, {0x1B41, 0x1B3F},
-{0x1B41, 0x1B35}, {0x1B43, 0x1B42}, {0x1B43, 0x1B35}, {0x1E00, 0x41}, {0x1E00, 0x325}, {0x1E01, 0x61}, {0x1E01, 0x325}, {0x1E02, 0x42}, {0x1E02, 0x307}, {0x1E03, 0x62}, {0x1E03, 0x307},
-{0x1E04, 0x42}, {0x1E04, 0x323}, {0x1E05, 0x62}, {0x1E05, 0x323}, {0x1E06, 0x42}, {0x1E06, 0x331}, {0x1E07, 0x62}, {0x1E07, 0x331}, {0x1E08, 0x43}, {0x1E08, 0x327}, {0x1E08, 0x301}, {0x1E09, 0x63},
-{0x1E09, 0x327}, {0x1E09, 0x301}, {0x1E0A, 0x44}, {0x1E0A, 0x307}, {0x1E0B, 0x64}, {0x1E0B, 0x307}, {0x1E0C, 0x44}, {0x1E0C, 0x323}, {0x1E0D, 0x64}, {0x1E0D, 0x323}, {0x1E0E, 0x44}, {0x1E0E, 0x331},
-{0x1E0F, 0x64}, {0x1E0F, 0x331}, {0x1E10, 0x44}, {0x1E10, 0x327}, {0x1E11, 0x64}, {0x1E11, 0x327}, {0x1E12, 0x44}, {0x1E12, 0x32D}, {0x1E13, 0x64}, {0x1E13, 0x32D}, {0x1E14, 0x45}, {0x1E14, 0x304},
-{0x1E14, 0x300}, {0x1E15, 0x65}, {0x1E15, 0x304}, {0x1E15, 0x300}, {0x1E16, 0x45}, {0x1E16, 0x304}, {0x1E16, 0x301}, {0x1E17, 0x65}, {0x1E17, 0x304}, {0x1E17, 0x301}, {0x1E18, 0x45}, {0x1E18, 0x32D},
-{0x1E19, 0x65}, {0x1E19, 0x32D}, {0x1E1A, 0x45}, {0x1E1A, 0x330}, {0x1E1B, 0x65}, {0x1E1B, 0x330}, {0x1E1C, 0x45}, {0x1E1C, 0x327}, {0x1E1C, 0x306}, {0x1E1D, 0x65}, {0x1E1D, 0x327}, {0x1E1D, 0x306},
-{0x1E1E, 0x46}, {0x1E1E, 0x307}, {0x1E1F, 0x66}, {0x1E1F, 0x307}, {0x1E20, 0x47}, {0x1E20, 0x304}, {0x1E21, 0x67}, {0x1E21, 0x304}, {0x1E22, 0x48}, {0x1E22, 0x307}, {0x1E23, 0x68}, {0x1E23, 0x307},
-{0x1E24, 0x48}, {0x1E24, 0x323}, {0x1E25, 0x68}, {0x1E25, 0x323}, {0x1E26, 0x48}, {0x1E26, 0x308}, {0x1E27, 0x68}, {0x1E27, 0x308}, {0x1E28, 0x48}, {0x1E28, 0x327}, {0x1E29, 0x68}, {0x1E29, 0x327},
-{0x1E2A, 0x48}, {0x1E2A, 0x32E}, {0x1E2B, 0x68}, {0x1E2B, 0x32E}, {0x1E2C, 0x49}, {0x1E2C, 0x330}, {0x1E2D, 0x69}, {0x1E2D, 0x330}, {0x1E2E, 0x49}, {0x1E2E, 0x308}, {0x1E2E, 0x301}, {0x1E2F, 0x69},
-{0x1E2F, 0x308}, {0x1E2F, 0x301}, {0x1E30, 0x4B}, {0x1E30, 0x301}, {0x1E31, 0x6B}, {0x1E31, 0x301}, {0x1E32, 0x4B}, {0x1E32, 0x323}, {0x1E33, 0x6B}, {0x1E33, 0x323}, {0x1E34, 0x4B}, {0x1E34, 0x331},
-{0x1E35, 0x6B}, {0x1E35, 0x331}, {0x1E36, 0x4C}, {0x1E36, 0x323}, {0x1E37, 0x6C}, {0x1E37, 0x323}, {0x1E38, 0x4C}, {0x1E38, 0x323}, {0x1E38, 0x304}, {0x1E39, 0x6C}, {0x1E39, 0x323}, {0x1E39, 0x304},
-{0x1E3A, 0x4C}, {0x1E3A, 0x331}, {0x1E3B, 0x6C}, {0x1E3B, 0x331}, {0x1E3C, 0x4C}, {0x1E3C, 0x32D}, {0x1E3D, 0x6C}, {0x1E3D, 0x32D}, {0x1E3E, 0x4D}, {0x1E3E, 0x301}, {0x1E3F, 0x6D}, {0x1E3F, 0x301},
-{0x1E40, 0x4D}, {0x1E40, 0x307}, {0x1E41, 0x6D}, {0x1E41, 0x307}, {0x1E42, 0x4D}, {0x1E42, 0x323}, {0x1E43, 0x6D}, {0x1E43, 0x323}, {0x1E44, 0x4E}, {0x1E44, 0x307}, {0x1E45, 0x6E}, {0x1E45, 0x307},
-{0x1E46, 0x4E}, {0x1E46, 0x323}, {0x1E47, 0x6E}, {0x1E47, 0x323}, {0x1E48, 0x4E}, {0x1E48, 0x331}, {0x1E49, 0x6E}, {0x1E49, 0x331}, {0x1E4A, 0x4E}, {0x1E4A, 0x32D}, {0x1E4B, 0x6E}, {0x1E4B, 0x32D},
-{0x1E4C, 0x4F}, {0x1E4C, 0x303}, {0x1E4C, 0x301}, {0x1E4D, 0x6F}, {0x1E4D, 0x303}, {0x1E4D, 0x301}, {0x1E4E, 0x4F}, {0x1E4E, 0x303}, {0x1E4E, 0x308}, {0x1E4F, 0x6F}, {0x1E4F, 0x303}, {0x1E4F, 0x308},
-{0x1E50, 0x4F}, {0x1E50, 0x304}, {0x1E50, 0x300}, {0x1E51, 0x6F}, {0x1E51, 0x304}, {0x1E51, 0x300}, {0x1E52, 0x4F}, {0x1E52, 0x304}, {0x1E52, 0x301}, {0x1E53, 0x6F}, {0x1E53, 0x304}, {0x1E53, 0x301},
-{0x1E54, 0x50}, {0x1E54, 0x301}, {0x1E55, 0x70}, {0x1E55, 0x301}, {0x1E56, 0x50}, {0x1E56, 0x307}, {0x1E57, 0x70}, {0x1E57, 0x307}, {0x1E58, 0x52}, {0x1E58, 0x307}, {0x1E59, 0x72}, {0x1E59, 0x307},
-{0x1E5A, 0x52}, {0x1E5A, 0x323}, {0x1E5B, 0x72}, {0x1E5B, 0x323}, {0x1E5C, 0x52}, {0x1E5C, 0x323}, {0x1E5C, 0x304}, {0x1E5D, 0x72}, {0x1E5D, 0x323}, {0x1E5D, 0x304}, {0x1E5E, 0x52}, {0x1E5E, 0x331},
-{0x1E5F, 0x72}, {0x1E5F, 0x331}, {0x1E60, 0x53}, {0x1E60, 0x307}, {0x1E61, 0x73}, {0x1E61, 0x307}, {0x1E62, 0x53}, {0x1E62, 0x323}, {0x1E63, 0x73}, {0x1E63, 0x323}, {0x1E64, 0x53}, {0x1E64, 0x301},
-{0x1E64, 0x307}, {0x1E65, 0x73}, {0x1E65, 0x301}, {0x1E65, 0x307}, {0x1E66, 0x53}, {0x1E66, 0x30C}, {0x1E66, 0x307}, {0x1E67, 0x73}, {0x1E67, 0x30C}, {0x1E67, 0x307}, {0x1E68, 0x53}, {0x1E68, 0x323},
-{0x1E68, 0x307}, {0x1E69, 0x73}, {0x1E69, 0x323}, {0x1E69, 0x307}, {0x1E6A, 0x54}, {0x1E6A, 0x307}, {0x1E6B, 0x74}, {0x1E6B, 0x307}, {0x1E6C, 0x54}, {0x1E6C, 0x323}, {0x1E6D, 0x74}, {0x1E6D, 0x323},
-{0x1E6E, 0x54}, {0x1E6E, 0x331}, {0x1E6F, 0x74}, {0x1E6F, 0x331}, {0x1E70, 0x54}, {0x1E70, 0x32D}, {0x1E71, 0x74}, {0x1E71, 0x32D}, {0x1E72, 0x55}, {0x1E72, 0x324}, {0x1E73, 0x75}, {0x1E73, 0x324},
-{0x1E74, 0x55}, {0x1E74, 0x330}, {0x1E75, 0x75}, {0x1E75, 0x330}, {0x1E76, 0x55}, {0x1E76, 0x32D}, {0x1E77, 0x75}, {0x1E77, 0x32D}, {0x1E78, 0x55}, {0x1E78, 0x303}, {0x1E78, 0x301}, {0x1E79, 0x75},
-{0x1E79, 0x303}, {0x1E79, 0x301}, {0x1E7A, 0x55}, {0x1E7A, 0x304}, {0x1E7A, 0x308}, {0x1E7B, 0x75}, {0x1E7B, 0x304}, {0x1E7B, 0x308}, {0x1E7C, 0x56}, {0x1E7C, 0x303}, {0x1E7D, 0x76}, {0x1E7D, 0x303},
-{0x1E7E, 0x56}, {0x1E7E, 0x323}, {0x1E7F, 0x76}, {0x1E7F, 0x323}, {0x1E80, 0x57}, {0x1E80, 0x300}, {0x1E81, 0x77}, {0x1E81, 0x300}, {0x1E82, 0x57}, {0x1E82, 0x301}, {0x1E83, 0x77}, {0x1E83, 0x301},
-{0x1E84, 0x57}, {0x1E84, 0x308}, {0x1E85, 0x77}, {0x1E85, 0x308}, {0x1E86, 0x57}, {0x1E86, 0x307}, {0x1E87, 0x77}, {0x1E87, 0x307}, {0x1E88, 0x57}, {0x1E88, 0x323}, {0x1E89, 0x77}, {0x1E89, 0x323},
-{0x1E8A, 0x58}, {0x1E8A, 0x307}, {0x1E8B, 0x78}, {0x1E8B, 0x307}, {0x1E8C, 0x58}, {0x1E8C, 0x308}, {0x1E8D, 0x78}, {0x1E8D, 0x308}, {0x1E8E, 0x59}, {0x1E8E, 0x307}, {0x1E8F, 0x79}, {0x1E8F, 0x307},
-{0x1E90, 0x5A}, {0x1E90, 0x302}, {0x1E91, 0x7A}, {0x1E91, 0x302}, {0x1E92, 0x5A}, {0x1E92, 0x323}, {0x1E93, 0x7A}, {0x1E93, 0x323}, {0x1E94, 0x5A}, {0x1E94, 0x331}, {0x1E95, 0x7A}, {0x1E95, 0x331},
-{0x1E96, 0x68}, {0x1E96, 0x331}, {0x1E97, 0x74}, {0x1E97, 0x308}, {0x1E98, 0x77}, {0x1E98, 0x30A}, {0x1E99, 0x79}, {0x1E99, 0x30A}, {0x1E9B, 0x17F}, {0x1E9B, 0x307}, {0x1EA0, 0x41}, {0x1EA0, 0x323},
-{0x1EA1, 0x61}, {0x1EA1, 0x323}, {0x1EA2, 0x41}, {0x1EA2, 0x309}, {0x1EA3, 0x61}, {0x1EA3, 0x309}, {0x1EA4, 0x41}, {0x1EA4, 0x302}, {0x1EA4, 0x301}, {0x1EA5, 0x61}, {0x1EA5, 0x302}, {0x1EA5, 0x301},
-{0x1EA6, 0x41}, {0x1EA6, 0x302}, {0x1EA6, 0x300}, {0x1EA7, 0x61}, {0x1EA7, 0x302}, {0x1EA7, 0x300}, {0x1EA8, 0x41}, {0x1EA8, 0x302}, {0x1EA8, 0x309}, {0x1EA9, 0x61}, {0x1EA9, 0x302}, {0x1EA9, 0x309},
-{0x1EAA, 0x41}, {0x1EAA, 0x302}, {0x1EAA, 0x303}, {0x1EAB, 0x61}, {0x1EAB, 0x302}, {0x1EAB, 0x303}, {0x1EAC, 0x41}, {0x1EAC, 0x323}, {0x1EAC, 0x302}, {0x1EAD, 0x61}, {0x1EAD, 0x323}, {0x1EAD, 0x302},
-{0x1EAE, 0x41}, {0x1EAE, 0x306}, {0x1EAE, 0x301}, {0x1EAF, 0x61}, {0x1EAF, 0x306}, {0x1EAF, 0x301}, {0x1EB0, 0x41}, {0x1EB0, 0x306}, {0x1EB0, 0x300}, {0x1EB1, 0x61}, {0x1EB1, 0x306}, {0x1EB1, 0x300},
-{0x1EB2, 0x41}, {0x1EB2, 0x306}, {0x1EB2, 0x309}, {0x1EB3, 0x61}, {0x1EB3, 0x306}, {0x1EB3, 0x309}, {0x1EB4, 0x41}, {0x1EB4, 0x306}, {0x1EB4, 0x303}, {0x1EB5, 0x61}, {0x1EB5, 0x306}, {0x1EB5, 0x303},
-{0x1EB6, 0x41}, {0x1EB6, 0x323}, {0x1EB6, 0x306}, {0x1EB7, 0x61}, {0x1EB7, 0x323}, {0x1EB7, 0x306}, {0x1EB8, 0x45}, {0x1EB8, 0x323}, {0x1EB9, 0x65}, {0x1EB9, 0x323}, {0x1EBA, 0x45}, {0x1EBA, 0x309},
-{0x1EBB, 0x65}, {0x1EBB, 0x309}, {0x1EBC, 0x45}, {0x1EBC, 0x303}, {0x1EBD, 0x65}, {0x1EBD, 0x303}, {0x1EBE, 0x45}, {0x1EBE, 0x302}, {0x1EBE, 0x301}, {0x1EBF, 0x65}, {0x1EBF, 0x302}, {0x1EBF, 0x301},
-{0x1EC0, 0x45}, {0x1EC0, 0x302}, {0x1EC0, 0x300}, {0x1EC1, 0x65}, {0x1EC1, 0x302}, {0x1EC1, 0x300}, {0x1EC2, 0x45}, {0x1EC2, 0x302}, {0x1EC2, 0x309}, {0x1EC3, 0x65}, {0x1EC3, 0x302}, {0x1EC3, 0x309},
-{0x1EC4, 0x45}, {0x1EC4, 0x302}, {0x1EC4, 0x303}, {0x1EC5, 0x65}, {0x1EC5, 0x302}, {0x1EC5, 0x303}, {0x1EC6, 0x45}, {0x1EC6, 0x323}, {0x1EC6, 0x302}, {0x1EC7, 0x65}, {0x1EC7, 0x323}, {0x1EC7, 0x302},
-{0x1EC8, 0x49}, {0x1EC8, 0x309}, {0x1EC9, 0x69}, {0x1EC9, 0x309}, {0x1ECA, 0x49}, {0x1ECA, 0x323}, {0x1ECB, 0x69}, {0x1ECB, 0x323}, {0x1ECC, 0x4F}, {0x1ECC, 0x323}, {0x1ECD, 0x6F}, {0x1ECD, 0x323},
-{0x1ECE, 0x4F}, {0x1ECE, 0x309}, {0x1ECF, 0x6F}, {0x1ECF, 0x309}, {0x1ED0, 0x4F}, {0x1ED0, 0x302}, {0x1ED0, 0x301}, {0x1ED1, 0x6F}, {0x1ED1, 0x302}, {0x1ED1, 0x301}, {0x1ED2, 0x4F}, {0x1ED2, 0x302},
-{0x1ED2, 0x300}, {0x1ED3, 0x6F}, {0x1ED3, 0x302}, {0x1ED3, 0x300}, {0x1ED4, 0x4F}, {0x1ED4, 0x302}, {0x1ED4, 0x309}, {0x1ED5, 0x6F}, {0x1ED5, 0x302}, {0x1ED5, 0x309}, {0x1ED6, 0x4F}, {0x1ED6, 0x302},
-{0x1ED6, 0x303}, {0x1ED7, 0x6F}, {0x1ED7, 0x302}, {0x1ED7, 0x303}, {0x1ED8, 0x4F}, {0x1ED8, 0x323}, {0x1ED8, 0x302}, {0x1ED9, 0x6F}, {0x1ED9, 0x323}, {0x1ED9, 0x302}, {0x1EDA, 0x4F}, {0x1EDA, 0x31B},
-{0x1EDA, 0x301}, {0x1EDB, 0x6F}, {0x1EDB, 0x31B}, {0x1EDB, 0x301}, {0x1EDC, 0x4F}, {0x1EDC, 0x31B}, {0x1EDC, 0x300}, {0x1EDD, 0x6F}, {0x1EDD, 0x31B}, {0x1EDD, 0x300}, {0x1EDE, 0x4F}, {0x1EDE, 0x31B},
-{0x1EDE, 0x309}, {0x1EDF, 0x6F}, {0x1EDF, 0x31B}, {0x1EDF, 0x309}, {0x1EE0, 0x4F}, {0x1EE0, 0x31B}, {0x1EE0, 0x303}, {0x1EE1, 0x6F}, {0x1EE1, 0x31B}, {0x1EE1, 0x303}, {0x1EE2, 0x4F}, {0x1EE2, 0x31B},
-{0x1EE2, 0x323}, {0x1EE3, 0x6F}, {0x1EE3, 0x31B}, {0x1EE3, 0x323}, {0x1EE4, 0x55}, {0x1EE4, 0x323}, {0x1EE5, 0x75}, {0x1EE5, 0x323}, {0x1EE6, 0x55}, {0x1EE6, 0x309}, {0x1EE7, 0x75}, {0x1EE7, 0x309},
-{0x1EE8, 0x55}, {0x1EE8, 0x31B}, {0x1EE8, 0x301}, {0x1EE9, 0x75}, {0x1EE9, 0x31B}, {0x1EE9, 0x301}, {0x1EEA, 0x55}, {0x1EEA, 0x31B}, {0x1EEA, 0x300}, {0x1EEB, 0x75}, {0x1EEB, 0x31B}, {0x1EEB, 0x300},
-{0x1EEC, 0x55}, {0x1EEC, 0x31B}, {0x1EEC, 0x309}, {0x1EED, 0x75}, {0x1EED, 0x31B}, {0x1EED, 0x309}, {0x1EEE, 0x55}, {0x1EEE, 0x31B}, {0x1EEE, 0x303}, {0x1EEF, 0x75}, {0x1EEF, 0x31B}, {0x1EEF, 0x303},
-{0x1EF0, 0x55}, {0x1EF0, 0x31B}, {0x1EF0, 0x323}, {0x1EF1, 0x75}, {0x1EF1, 0x31B}, {0x1EF1, 0x323}, {0x1EF2, 0x59}, {0x1EF2, 0x300}, {0x1EF3, 0x79}, {0x1EF3, 0x300}, {0x1EF4, 0x59}, {0x1EF4, 0x323},
-{0x1EF5, 0x79}, {0x1EF5, 0x323}, {0x1EF6, 0x59}, {0x1EF6, 0x309}, {0x1EF7, 0x79}, {0x1EF7, 0x309}, {0x1EF8, 0x59}, {0x1EF8, 0x303}, {0x1EF9, 0x79}, {0x1EF9, 0x303}, {0x1F00, 0x3B1}, {0x1F00, 0x313},
-{0x1F01, 0x3B1}, {0x1F01, 0x314}, {0x1F02, 0x3B1}, {0x1F02, 0x313}, {0x1F02, 0x300}, {0x1F03, 0x3B1}, {0x1F03, 0x314}, {0x1F03, 0x300}, {0x1F04, 0x3B1}, {0x1F04, 0x313}, {0x1F04, 0x301},
-{0x1F05, 0x3B1}, {0x1F05, 0x314}, {0x1F05, 0x301}, {0x1F06, 0x3B1}, {0x1F06, 0x313}, {0x1F06, 0x342}, {0x1F07, 0x3B1}, {0x1F07, 0x314}, {0x1F07, 0x342}, {0x1F08, 0x391}, {0x1F08, 0x313},
-{0x1F09, 0x391}, {0x1F09, 0x314}, {0x1F0A, 0x391}, {0x1F0A, 0x313}, {0x1F0A, 0x300}, {0x1F0B, 0x391}, {0x1F0B, 0x314}, {0x1F0B, 0x300}, {0x1F0C, 0x391}, {0x1F0C, 0x313}, {0x1F0C, 0x301},
-{0x1F0D, 0x391}, {0x1F0D, 0x314}, {0x1F0D, 0x301}, {0x1F0E, 0x391}, {0x1F0E, 0x313}, {0x1F0E, 0x342}, {0x1F0F, 0x391}, {0x1F0F, 0x314}, {0x1F0F, 0x342}, {0x1F10, 0x3B5}, {0x1F10, 0x313},
-{0x1F11, 0x3B5}, {0x1F11, 0x314}, {0x1F12, 0x3B5}, {0x1F12, 0x313}, {0x1F12, 0x300}, {0x1F13, 0x3B5}, {0x1F13, 0x314}, {0x1F13, 0x300}, {0x1F14, 0x3B5}, {0x1F14, 0x313}, {0x1F14, 0x301},
-{0x1F15, 0x3B5}, {0x1F15, 0x314}, {0x1F15, 0x301}, {0x1F18, 0x395}, {0x1F18, 0x313}, {0x1F19, 0x395}, {0x1F19, 0x314}, {0x1F1A, 0x395}, {0x1F1A, 0x313}, {0x1F1A, 0x300}, {0x1F1B, 0x395},
-{0x1F1B, 0x314}, {0x1F1B, 0x300}, {0x1F1C, 0x395}, {0x1F1C, 0x313}, {0x1F1C, 0x301}, {0x1F1D, 0x395}, {0x1F1D, 0x314}, {0x1F1D, 0x301}, {0x1F20, 0x3B7}, {0x1F20, 0x313}, {0x1F21, 0x3B7},
-{0x1F21, 0x314}, {0x1F22, 0x3B7}, {0x1F22, 0x313}, {0x1F22, 0x300}, {0x1F23, 0x3B7}, {0x1F23, 0x314}, {0x1F23, 0x300}, {0x1F24, 0x3B7}, {0x1F24, 0x313}, {0x1F24, 0x301}, {0x1F25, 0x3B7},
-{0x1F25, 0x314}, {0x1F25, 0x301}, {0x1F26, 0x3B7}, {0x1F26, 0x313}, {0x1F26, 0x342}, {0x1F27, 0x3B7}, {0x1F27, 0x314}, {0x1F27, 0x342}, {0x1F28, 0x397}, {0x1F28, 0x313}, {0x1F29, 0x397},
-{0x1F29, 0x314}, {0x1F2A, 0x397}, {0x1F2A, 0x313}, {0x1F2A, 0x300}, {0x1F2B, 0x397}, {0x1F2B, 0x314}, {0x1F2B, 0x300}, {0x1F2C, 0x397}, {0x1F2C, 0x313}, {0x1F2C, 0x301}, {0x1F2D, 0x397},
-{0x1F2D, 0x314}, {0x1F2D, 0x301}, {0x1F2E, 0x397}, {0x1F2E, 0x313}, {0x1F2E, 0x342}, {0x1F2F, 0x397}, {0x1F2F, 0x314}, {0x1F2F, 0x342}, {0x1F30, 0x3B9}, {0x1F30, 0x313}, {0x1F31, 0x3B9},
-{0x1F31, 0x314}, {0x1F32, 0x3B9}, {0x1F32, 0x313}, {0x1F32, 0x300}, {0x1F33, 0x3B9}, {0x1F33, 0x314}, {0x1F33, 0x300}, {0x1F34, 0x3B9}, {0x1F34, 0x313}, {0x1F34, 0x301}, {0x1F35, 0x3B9},
-{0x1F35, 0x314}, {0x1F35, 0x301}, {0x1F36, 0x3B9}, {0x1F36, 0x313}, {0x1F36, 0x342}, {0x1F37, 0x3B9}, {0x1F37, 0x314}, {0x1F37, 0x342}, {0x1F38, 0x399}, {0x1F38, 0x313}, {0x1F39, 0x399},
-{0x1F39, 0x314}, {0x1F3A, 0x399}, {0x1F3A, 0x313}, {0x1F3A, 0x300}, {0x1F3B, 0x399}, {0x1F3B, 0x314}, {0x1F3B, 0x300}, {0x1F3C, 0x399}, {0x1F3C, 0x313}, {0x1F3C, 0x301}, {0x1F3D, 0x399},
-{0x1F3D, 0x314}, {0x1F3D, 0x301}, {0x1F3E, 0x399}, {0x1F3E, 0x313}, {0x1F3E, 0x342}, {0x1F3F, 0x399}, {0x1F3F, 0x314}, {0x1F3F, 0x342}, {0x1F40, 0x3BF}, {0x1F40, 0x313}, {0x1F41, 0x3BF},
-{0x1F41, 0x314}, {0x1F42, 0x3BF}, {0x1F42, 0x313}, {0x1F42, 0x300}, {0x1F43, 0x3BF}, {0x1F43, 0x314}, {0x1F43, 0x300}, {0x1F44, 0x3BF}, {0x1F44, 0x313}, {0x1F44, 0x301}, {0x1F45, 0x3BF},
-{0x1F45, 0x314}, {0x1F45, 0x301}, {0x1F48, 0x39F}, {0x1F48, 0x313}, {0x1F49, 0x39F}, {0x1F49, 0x314}, {0x1F4A, 0x39F}, {0x1F4A, 0x313}, {0x1F4A, 0x300}, {0x1F4B, 0x39F}, {0x1F4B, 0x314},
-{0x1F4B, 0x300}, {0x1F4C, 0x39F}, {0x1F4C, 0x313}, {0x1F4C, 0x301}, {0x1F4D, 0x39F}, {0x1F4D, 0x314}, {0x1F4D, 0x301}, {0x1F50, 0x3C5}, {0x1F50, 0x313}, {0x1F51, 0x3C5}, {0x1F51, 0x314},
-{0x1F52, 0x3C5}, {0x1F52, 0x313}, {0x1F52, 0x300}, {0x1F53, 0x3C5}, {0x1F53, 0x314}, {0x1F53, 0x300}, {0x1F54, 0x3C5}, {0x1F54, 0x313}, {0x1F54, 0x301}, {0x1F55, 0x3C5}, {0x1F55, 0x314},
-{0x1F55, 0x301}, {0x1F56, 0x3C5}, {0x1F56, 0x313}, {0x1F56, 0x342}, {0x1F57, 0x3C5}, {0x1F57, 0x314}, {0x1F57, 0x342}, {0x1F59, 0x3A5}, {0x1F59, 0x314}, {0x1F5B, 0x3A5}, {0x1F5B, 0x314},
-{0x1F5B, 0x300}, {0x1F5D, 0x3A5}, {0x1F5D, 0x314}, {0x1F5D, 0x301}, {0x1F5F, 0x3A5}, {0x1F5F, 0x314}, {0x1F5F, 0x342}, {0x1F60, 0x3C9}, {0x1F60, 0x313}, {0x1F61, 0x3C9}, {0x1F61, 0x314},
-{0x1F62, 0x3C9}, {0x1F62, 0x313}, {0x1F62, 0x300}, {0x1F63, 0x3C9}, {0x1F63, 0x314}, {0x1F63, 0x300}, {0x1F64, 0x3C9}, {0x1F64, 0x313}, {0x1F64, 0x301}, {0x1F65, 0x3C9}, {0x1F65, 0x314},
-{0x1F65, 0x301}, {0x1F66, 0x3C9}, {0x1F66, 0x313}, {0x1F66, 0x342}, {0x1F67, 0x3C9}, {0x1F67, 0x314}, {0x1F67, 0x342}, {0x1F68, 0x3A9}, {0x1F68, 0x313}, {0x1F69, 0x3A9}, {0x1F69, 0x314},
-{0x1F6A, 0x3A9}, {0x1F6A, 0x313}, {0x1F6A, 0x300}, {0x1F6B, 0x3A9}, {0x1F6B, 0x314}, {0x1F6B, 0x300}, {0x1F6C, 0x3A9}, {0x1F6C, 0x313}, {0x1F6C, 0x301}, {0x1F6D, 0x3A9}, {0x1F6D, 0x314},
-{0x1F6D, 0x301}, {0x1F6E, 0x3A9}, {0x1F6E, 0x313}, {0x1F6E, 0x342}, {0x1F6F, 0x3A9}, {0x1F6F, 0x314}, {0x1F6F, 0x342}, {0x1F70, 0x3B1}, {0x1F70, 0x300}, {0x1F71, 0x3B1}, {0x1F71, 0x301},
-{0x1F72, 0x3B5}, {0x1F72, 0x300}, {0x1F73, 0x3B5}, {0x1F73, 0x301}, {0x1F74, 0x3B7}, {0x1F74, 0x300}, {0x1F75, 0x3B7}, {0x1F75, 0x301}, {0x1F76, 0x3B9}, {0x1F76, 0x300}, {0x1F77, 0x3B9},
-{0x1F77, 0x301}, {0x1F78, 0x3BF}, {0x1F78, 0x300}, {0x1F79, 0x3BF}, {0x1F79, 0x301}, {0x1F7A, 0x3C5}, {0x1F7A, 0x300}, {0x1F7B, 0x3C5}, {0x1F7B, 0x301}, {0x1F7C, 0x3C9}, {0x1F7C, 0x300},
-{0x1F7D, 0x3C9}, {0x1F7D, 0x301}, {0x1F80, 0x3B1}, {0x1F80, 0x313}, {0x1F80, 0x345}, {0x1F81, 0x3B1}, {0x1F81, 0x314}, {0x1F81, 0x345}, {0x1F82, 0x3B1}, {0x1F82, 0x313}, {0x1F82, 0x300},
-{0x1F82, 0x345}, {0x1F83, 0x3B1}, {0x1F83, 0x314}, {0x1F83, 0x300}, {0x1F83, 0x345}, {0x1F84, 0x3B1}, {0x1F84, 0x313}, {0x1F84, 0x301}, {0x1F84, 0x345}, {0x1F85, 0x3B1}, {0x1F85, 0x314},
-{0x1F85, 0x301}, {0x1F85, 0x345}, {0x1F86, 0x3B1}, {0x1F86, 0x313}, {0x1F86, 0x342}, {0x1F86, 0x345}, {0x1F87, 0x3B1}, {0x1F87, 0x314}, {0x1F87, 0x342}, {0x1F87, 0x345}, {0x1F88, 0x391},
-{0x1F88, 0x313}, {0x1F88, 0x345}, {0x1F89, 0x391}, {0x1F89, 0x314}, {0x1F89, 0x345}, {0x1F8A, 0x391}, {0x1F8A, 0x313}, {0x1F8A, 0x300}, {0x1F8A, 0x345}, {0x1F8B, 0x391}, {0x1F8B, 0x314},
-{0x1F8B, 0x300}, {0x1F8B, 0x345}, {0x1F8C, 0x391}, {0x1F8C, 0x313}, {0x1F8C, 0x301}, {0x1F8C, 0x345}, {0x1F8D, 0x391}, {0x1F8D, 0x314}, {0x1F8D, 0x301}, {0x1F8D, 0x345}, {0x1F8E, 0x391},
-{0x1F8E, 0x313}, {0x1F8E, 0x342}, {0x1F8E, 0x345}, {0x1F8F, 0x391}, {0x1F8F, 0x314}, {0x1F8F, 0x342}, {0x1F8F, 0x345}, {0x1F90, 0x3B7}, {0x1F90, 0x313}, {0x1F90, 0x345}, {0x1F91, 0x3B7},
-{0x1F91, 0x314}, {0x1F91, 0x345}, {0x1F92, 0x3B7}, {0x1F92, 0x313}, {0x1F92, 0x300}, {0x1F92, 0x345}, {0x1F93, 0x3B7}, {0x1F93, 0x314}, {0x1F93, 0x300}, {0x1F93, 0x345}, {0x1F94, 0x3B7},
-{0x1F94, 0x313}, {0x1F94, 0x301}, {0x1F94, 0x345}, {0x1F95, 0x3B7}, {0x1F95, 0x314}, {0x1F95, 0x301}, {0x1F95, 0x345}, {0x1F96, 0x3B7}, {0x1F96, 0x313}, {0x1F96, 0x342}, {0x1F96, 0x345},
-{0x1F97, 0x3B7}, {0x1F97, 0x314}, {0x1F97, 0x342}, {0x1F97, 0x345}, {0x1F98, 0x397}, {0x1F98, 0x313}, {0x1F98, 0x345}, {0x1F99, 0x397}, {0x1F99, 0x314}, {0x1F99, 0x345}, {0x1F9A, 0x397},
-{0x1F9A, 0x313}, {0x1F9A, 0x300}, {0x1F9A, 0x345}, {0x1F9B, 0x397}, {0x1F9B, 0x314}, {0x1F9B, 0x300}, {0x1F9B, 0x345}, {0x1F9C, 0x397}, {0x1F9C, 0x313}, {0x1F9C, 0x301}, {0x1F9C, 0x345},
-{0x1F9D, 0x397}, {0x1F9D, 0x314}, {0x1F9D, 0x301}, {0x1F9D, 0x345}, {0x1F9E, 0x397}, {0x1F9E, 0x313}, {0x1F9E, 0x342}, {0x1F9E, 0x345}, {0x1F9F, 0x397}, {0x1F9F, 0x314}, {0x1F9F, 0x342},
-{0x1F9F, 0x345}, {0x1FA0, 0x3C9}, {0x1FA0, 0x313}, {0x1FA0, 0x345}, {0x1FA1, 0x3C9}, {0x1FA1, 0x314}, {0x1FA1, 0x345}, {0x1FA2, 0x3C9}, {0x1FA2, 0x313}, {0x1FA2, 0x300}, {0x1FA2, 0x345},
-{0x1FA3, 0x3C9}, {0x1FA3, 0x314}, {0x1FA3, 0x300}, {0x1FA3, 0x345}, {0x1FA4, 0x3C9}, {0x1FA4, 0x313}, {0x1FA4, 0x301}, {0x1FA4, 0x345}, {0x1FA5, 0x3C9}, {0x1FA5, 0x314}, {0x1FA5, 0x301},
-{0x1FA5, 0x345}, {0x1FA6, 0x3C9}, {0x1FA6, 0x313}, {0x1FA6, 0x342}, {0x1FA6, 0x345}, {0x1FA7, 0x3C9}, {0x1FA7, 0x314}, {0x1FA7, 0x342}, {0x1FA7, 0x345}, {0x1FA8, 0x3A9}, {0x1FA8, 0x313},
-{0x1FA8, 0x345}, {0x1FA9, 0x3A9}, {0x1FA9, 0x314}, {0x1FA9, 0x345}, {0x1FAA, 0x3A9}, {0x1FAA, 0x313}, {0x1FAA, 0x300}, {0x1FAA, 0x345}, {0x1FAB, 0x3A9}, {0x1FAB, 0x314}, {0x1FAB, 0x300},
-{0x1FAB, 0x345}, {0x1FAC, 0x3A9}, {0x1FAC, 0x313}, {0x1FAC, 0x301}, {0x1FAC, 0x345}, {0x1FAD, 0x3A9}, {0x1FAD, 0x314}, {0x1FAD, 0x301}, {0x1FAD, 0x345}, {0x1FAE, 0x3A9}, {0x1FAE, 0x313},
-{0x1FAE, 0x342}, {0x1FAE, 0x345}, {0x1FAF, 0x3A9}, {0x1FAF, 0x314}, {0x1FAF, 0x342}, {0x1FAF, 0x345}, {0x1FB0, 0x3B1}, {0x1FB0, 0x306}, {0x1FB1, 0x3B1}, {0x1FB1, 0x304}, {0x1FB2, 0x3B1},
-{0x1FB2, 0x300}, {0x1FB2, 0x345}, {0x1FB3, 0x3B1}, {0x1FB3, 0x345}, {0x1FB4, 0x3B1}, {0x1FB4, 0x301}, {0x1FB4, 0x345}, {0x1FB6, 0x3B1}, {0x1FB6, 0x342}, {0x1FB7, 0x3B1}, {0x1FB7, 0x342},
-{0x1FB7, 0x345}, {0x1FB8, 0x391}, {0x1FB8, 0x306}, {0x1FB9, 0x391}, {0x1FB9, 0x304}, {0x1FBA, 0x391}, {0x1FBA, 0x300}, {0x1FBB, 0x391}, {0x1FBB, 0x301}, {0x1FBC, 0x391}, {0x1FBC, 0x345},
-{0x1FBE, 0x3B9}, {0x1FC1, 0xA8}, {0x1FC1, 0x342}, {0x1FC2, 0x3B7}, {0x1FC2, 0x300}, {0x1FC2, 0x345}, {0x1FC3, 0x3B7}, {0x1FC3, 0x345}, {0x1FC4, 0x3B7}, {0x1FC4, 0x301}, {0x1FC4, 0x345},
-{0x1FC6, 0x3B7}, {0x1FC6, 0x342}, {0x1FC7, 0x3B7}, {0x1FC7, 0x342}, {0x1FC7, 0x345}, {0x1FC8, 0x395}, {0x1FC8, 0x300}, {0x1FC9, 0x395}, {0x1FC9, 0x301}, {0x1FCA, 0x397}, {0x1FCA, 0x300},
-{0x1FCB, 0x397}, {0x1FCB, 0x301}, {0x1FCC, 0x397}, {0x1FCC, 0x345}, {0x1FCD, 0x1FBF}, {0x1FCD, 0x300}, {0x1FCE, 0x1FBF}, {0x1FCE, 0x301}, {0x1FCF, 0x1FBF}, {0x1FCF, 0x342}, {0x1FD0, 0x3B9},
-{0x1FD0, 0x306}, {0x1FD1, 0x3B9}, {0x1FD1, 0x304}, {0x1FD2, 0x3B9}, {0x1FD2, 0x308}, {0x1FD2, 0x300}, {0x1FD3, 0x3B9}, {0x1FD3, 0x308}, {0x1FD3, 0x301}, {0x1FD6, 0x3B9}, {0x1FD6, 0x342},
-{0x1FD7, 0x3B9}, {0x1FD7, 0x308}, {0x1FD7, 0x342}, {0x1FD8, 0x399}, {0x1FD8, 0x306}, {0x1FD9, 0x399}, {0x1FD9, 0x304}, {0x1FDA, 0x399}, {0x1FDA, 0x300}, {0x1FDB, 0x399}, {0x1FDB, 0x301},
-{0x1FDD, 0x1FFE}, {0x1FDD, 0x300}, {0x1FDE, 0x1FFE}, {0x1FDE, 0x301}, {0x1FDF, 0x1FFE}, {0x1FDF, 0x342}, {0x1FE0, 0x3C5}, {0x1FE0, 0x306}, {0x1FE1, 0x3C5}, {0x1FE1, 0x304}, {0x1FE2, 0x3C5},
-{0x1FE2, 0x308}, {0x1FE2, 0x300}, {0x1FE3, 0x3C5}, {0x1FE3, 0x308}, {0x1FE3, 0x301}, {0x1FE4, 0x3C1}, {0x1FE4, 0x313}, {0x1FE5, 0x3C1}, {0x1FE5, 0x314}, {0x1FE6, 0x3C5}, {0x1FE6, 0x342},
-{0x1FE7, 0x3C5}, {0x1FE7, 0x308}, {0x1FE7, 0x342}, {0x1FE8, 0x3A5}, {0x1FE8, 0x306}, {0x1FE9, 0x3A5}, {0x1FE9, 0x304}, {0x1FEA, 0x3A5}, {0x1FEA, 0x300}, {0x1FEB, 0x3A5}, {0x1FEB, 0x301},
-{0x1FEC, 0x3A1}, {0x1FEC, 0x314}, {0x1FED, 0xA8}, {0x1FED, 0x300}, {0x1FEE, 0xA8}, {0x1FEE, 0x301}, {0x1FEF, 0x60}, {0x1FF2, 0x3C9}, {0x1FF2, 0x300}, {0x1FF2, 0x345}, {0x1FF3, 0x3C9}, {0x1FF3, 0x345},
-{0x1FF4, 0x3C9}, {0x1FF4, 0x301}, {0x1FF4, 0x345}, {0x1FF6, 0x3C9}, {0x1FF6, 0x342}, {0x1FF7, 0x3C9}, {0x1FF7, 0x342}, {0x1FF7, 0x345}, {0x1FF8, 0x39F}, {0x1FF8, 0x300}, {0x1FF9, 0x39F},
-{0x1FF9, 0x301}, {0x1FFA, 0x3A9}, {0x1FFA, 0x300}, {0x1FFB, 0x3A9}, {0x1FFB, 0x301}, {0x1FFC, 0x3A9}, {0x1FFC, 0x345}, {0x1FFD, 0xB4}, {0x2000, 0x2002}, {0x2001, 0x2003}, {0x2126, 0x3A9},
-{0x212A, 0x4B}, {0x212B, 0x41}, {0x212B, 0x30A}, {0x219A, 0x2190}, {0x219A, 0x338}, {0x219B, 0x2192}, {0x219B, 0x338}, {0x21AE, 0x2194}, {0x21AE, 0x338}, {0x21CD, 0x21D0}, {0x21CD, 0x338},
-{0x21CE, 0x21D4}, {0x21CE, 0x338}, {0x21CF, 0x21D2}, {0x21CF, 0x338}, {0x2204, 0x2203}, {0x2204, 0x338}, {0x2209, 0x2208}, {0x2209, 0x338}, {0x220C, 0x220B}, {0x220C, 0x338}, {0x2224, 0x2223},
-{0x2224, 0x338}, {0x2226, 0x2225}, {0x2226, 0x338}, {0x2241, 0x223C}, {0x2241, 0x338}, {0x2244, 0x2243}, {0x2244, 0x338}, {0x2247, 0x2245}, {0x2247, 0x338}, {0x2249, 0x2248}, {0x2249, 0x338},
-{0x2260, 0x3D}, {0x2260, 0x338}, {0x2262, 0x2261}, {0x2262, 0x338}, {0x226D, 0x224D}, {0x226D, 0x338}, {0x226E, 0x3C}, {0x226E, 0x338}, {0x226F, 0x3E}, {0x226F, 0x338}, {0x2270, 0x2264},
-{0x2270, 0x338}, {0x2271, 0x2265}, {0x2271, 0x338}, {0x2274, 0x2272}, {0x2274, 0x338}, {0x2275, 0x2273}, {0x2275, 0x338}, {0x2278, 0x2276}, {0x2278, 0x338}, {0x2279, 0x2277}, {0x2279, 0x338},
-{0x2280, 0x227A}, {0x2280, 0x338}, {0x2281, 0x227B}, {0x2281, 0x338}, {0x2284, 0x2282}, {0x2284, 0x338}, {0x2285, 0x2283}, {0x2285, 0x338}, {0x2288, 0x2286}, {0x2288, 0x338}, {0x2289, 0x2287},
-{0x2289, 0x338}, {0x22AC, 0x22A2}, {0x22AC, 0x338}, {0x22AD, 0x22A8}, {0x22AD, 0x338}, {0x22AE, 0x22A9}, {0x22AE, 0x338}, {0x22AF, 0x22AB}, {0x22AF, 0x338}, {0x22E0, 0x227C}, {0x22E0, 0x338},
-{0x22E1, 0x227D}, {0x22E1, 0x338}, {0x22E2, 0x2291}, {0x22E2, 0x338}, {0x22E3, 0x2292}, {0x22E3, 0x338}, {0x22EA, 0x22B2}, {0x22EA, 0x338}, {0x22EB, 0x22B3}, {0x22EB, 0x338}, {0x22EC, 0x22B4},
-{0x22EC, 0x338}, {0x22ED, 0x22B5}, {0x22ED, 0x338}, {0x2329, 0x3008}, {0x232A, 0x3009}, {0x2ADC, 0x2ADD}, {0x2ADC, 0x338}, {0x304C, 0x304B}, {0x304C, 0x3099}, {0x304E, 0x304D}, {0x304E, 0x3099},
-{0x3050, 0x304F}, {0x3050, 0x3099}, {0x3052, 0x3051}, {0x3052, 0x3099}, {0x3054, 0x3053}, {0x3054, 0x3099}, {0x3056, 0x3055}, {0x3056, 0x3099}, {0x3058, 0x3057}, {0x3058, 0x3099}, {0x305A, 0x3059},
-{0x305A, 0x3099}, {0x305C, 0x305B}, {0x305C, 0x3099}, {0x305E, 0x305D}, {0x305E, 0x3099}, {0x3060, 0x305F}, {0x3060, 0x3099}, {0x3062, 0x3061}, {0x3062, 0x3099}, {0x3065, 0x3064}, {0x3065, 0x3099},
-{0x3067, 0x3066}, {0x3067, 0x3099}, {0x3069, 0x3068}, {0x3069, 0x3099}, {0x3070, 0x306F}, {0x3070, 0x3099}, {0x3071, 0x306F}, {0x3071, 0x309A}, {0x3073, 0x3072}, {0x3073, 0x3099}, {0x3074, 0x3072},
-{0x3074, 0x309A}, {0x3076, 0x3075}, {0x3076, 0x3099}, {0x3077, 0x3075}, {0x3077, 0x309A}, {0x3079, 0x3078}, {0x3079, 0x3099}, {0x307A, 0x3078}, {0x307A, 0x309A}, {0x307C, 0x307B}, {0x307C, 0x3099},
-{0x307D, 0x307B}, {0x307D, 0x309A}, {0x3094, 0x3046}, {0x3094, 0x3099}, {0x309E, 0x309D}, {0x309E, 0x3099}, {0x30AC, 0x30AB}, {0x30AC, 0x3099}, {0x30AE, 0x30AD}, {0x30AE, 0x3099}, {0x30B0, 0x30AF},
-{0x30B0, 0x3099}, {0x30B2, 0x30B1}, {0x30B2, 0x3099}, {0x30B4, 0x30B3}, {0x30B4, 0x3099}, {0x30B6, 0x30B5}, {0x30B6, 0x3099}, {0x30B8, 0x30B7}, {0x30B8, 0x3099}, {0x30BA, 0x30B9}, {0x30BA, 0x3099},
-{0x30BC, 0x30BB}, {0x30BC, 0x3099}, {0x30BE, 0x30BD}, {0x30BE, 0x3099}, {0x30C0, 0x30BF}, {0x30C0, 0x3099}, {0x30C2, 0x30C1}, {0x30C2, 0x3099}, {0x30C5, 0x30C4}, {0x30C5, 0x3099}, {0x30C7, 0x30C6},
-{0x30C7, 0x3099}, {0x30C9, 0x30C8}, {0x30C9, 0x3099}, {0x30D0, 0x30CF}, {0x30D0, 0x3099}, {0x30D1, 0x30CF}, {0x30D1, 0x309A}, {0x30D3, 0x30D2}, {0x30D3, 0x3099}, {0x30D4, 0x30D2}, {0x30D4, 0x309A},
-{0x30D6, 0x30D5}, {0x30D6, 0x3099}, {0x30D7, 0x30D5}, {0x30D7, 0x309A}, {0x30D9, 0x30D8}, {0x30D9, 0x3099}, {0x30DA, 0x30D8}, {0x30DA, 0x309A}, {0x30DC, 0x30DB}, {0x30DC, 0x3099}, {0x30DD, 0x30DB},
-{0x30DD, 0x309A}, {0x30F4, 0x30A6}, {0x30F4, 0x3099}, {0x30F7, 0x30EF}, {0x30F7, 0x3099}, {0x30F8, 0x30F0}, {0x30F8, 0x3099}, {0x30F9, 0x30F1}, {0x30F9, 0x3099}, {0x30FA, 0x30F2}, {0x30FA, 0x3099},
-{0x30FE, 0x30FD}, {0x30FE, 0x3099}, {0xF900, 0x8C48}, {0xF901, 0x66F4}, {0xF902, 0x8ECA}, {0xF903, 0x8CC8}, {0xF904, 0x6ED1}, {0xF905, 0x4E32}, {0xF906, 0x53E5}, {0xF907, 0x9F9C}, {0xF908, 0x9F9C},
-{0xF909, 0x5951}, {0xF90A, 0x91D1}, {0xF90B, 0x5587}, {0xF90C, 0x5948}, {0xF90D, 0x61F6}, {0xF90E, 0x7669}, {0xF90F, 0x7F85}, {0xF910, 0x863F}, {0xF911, 0x87BA}, {0xF912, 0x88F8}, {0xF913, 0x908F},
-{0xF914, 0x6A02}, {0xF915, 0x6D1B}, {0xF916, 0x70D9}, {0xF917, 0x73DE}, {0xF918, 0x843D}, {0xF919, 0x916A}, {0xF91A, 0x99F1}, {0xF91B, 0x4E82}, {0xF91C, 0x5375}, {0xF91D, 0x6B04}, {0xF91E, 0x721B},
-{0xF91F, 0x862D}, {0xF920, 0x9E1E}, {0xF921, 0x5D50}, {0xF922, 0x6FEB}, {0xF923, 0x85CD}, {0xF924, 0x8964}, {0xF925, 0x62C9}, {0xF926, 0x81D8}, {0xF927, 0x881F}, {0xF928, 0x5ECA}, {0xF929, 0x6717},
-{0xF92A, 0x6D6A}, {0xF92B, 0x72FC}, {0xF92C, 0x90CE}, {0xF92D, 0x4F86}, {0xF92E, 0x51B7}, {0xF92F, 0x52DE}, {0xF930, 0x64C4}, {0xF931, 0x6AD3}, {0xF932, 0x7210}, {0xF933, 0x76E7}, {0xF934, 0x8001},
-{0xF935, 0x8606}, {0xF936, 0x865C}, {0xF937, 0x8DEF}, {0xF938, 0x9732}, {0xF939, 0x9B6F}, {0xF93A, 0x9DFA}, {0xF93B, 0x788C}, {0xF93C, 0x797F}, {0xF93D, 0x7DA0}, {0xF93E, 0x83C9}, {0xF93F, 0x9304},
-{0xF940, 0x9E7F}, {0xF941, 0x8AD6}, {0xF942, 0x58DF}, {0xF943, 0x5F04}, {0xF944, 0x7C60}, {0xF945, 0x807E}, {0xF946, 0x7262}, {0xF947, 0x78CA}, {0xF948, 0x8CC2}, {0xF949, 0x96F7}, {0xF94A, 0x58D8},
-{0xF94B, 0x5C62}, {0xF94C, 0x6A13}, {0xF94D, 0x6DDA}, {0xF94E, 0x6F0F}, {0xF94F, 0x7D2F}, {0xF950, 0x7E37}, {0xF951, 0x964B}, {0xF952, 0x52D2}, {0xF953, 0x808B}, {0xF954, 0x51DC}, {0xF955, 0x51CC},
-{0xF956, 0x7A1C}, {0xF957, 0x7DBE}, {0xF958, 0x83F1}, {0xF959, 0x9675}, {0xF95A, 0x8B80}, {0xF95B, 0x62CF}, {0xF95C, 0x6A02}, {0xF95D, 0x8AFE}, {0xF95E, 0x4E39}, {0xF95F, 0x5BE7}, {0xF960, 0x6012},
-{0xF961, 0x7387}, {0xF962, 0x7570}, {0xF963, 0x5317}, {0xF964, 0x78FB}, {0xF965, 0x4FBF}, {0xF966, 0x5FA9}, {0xF967, 0x4E0D}, {0xF968, 0x6CCC}, {0xF969, 0x6578}, {0xF96A, 0x7D22}, {0xF96B, 0x53C3},
-{0xF96C, 0x585E}, {0xF96D, 0x7701}, {0xF96E, 0x8449}, {0xF96F, 0x8AAA}, {0xF970, 0x6BBA}, {0xF971, 0x8FB0}, {0xF972, 0x6C88}, {0xF973, 0x62FE}, {0xF974, 0x82E5}, {0xF975, 0x63A0}, {0xF976, 0x7565},
-{0xF977, 0x4EAE}, {0xF978, 0x5169}, {0xF979, 0x51C9}, {0xF97A, 0x6881}, {0xF97B, 0x7CE7}, {0xF97C, 0x826F}, {0xF97D, 0x8AD2}, {0xF97E, 0x91CF}, {0xF97F, 0x52F5}, {0xF980, 0x5442}, {0xF981, 0x5973},
-{0xF982, 0x5EEC}, {0xF983, 0x65C5}, {0xF984, 0x6FFE}, {0xF985, 0x792A}, {0xF986, 0x95AD}, {0xF987, 0x9A6A}, {0xF988, 0x9E97}, {0xF989, 0x9ECE}, {0xF98A, 0x529B}, {0xF98B, 0x66C6}, {0xF98C, 0x6B77},
-{0xF98D, 0x8F62}, {0xF98E, 0x5E74}, {0xF98F, 0x6190}, {0xF990, 0x6200}, {0xF991, 0x649A}, {0xF992, 0x6F23}, {0xF993, 0x7149}, {0xF994, 0x7489}, {0xF995, 0x79CA}, {0xF996, 0x7DF4}, {0xF997, 0x806F},
-{0xF998, 0x8F26}, {0xF999, 0x84EE}, {0xF99A, 0x9023}, {0xF99B, 0x934A}, {0xF99C, 0x5217}, {0xF99D, 0x52A3}, {0xF99E, 0x54BD}, {0xF99F, 0x70C8}, {0xF9A0, 0x88C2}, {0xF9A1, 0x8AAA}, {0xF9A2, 0x5EC9},
-{0xF9A3, 0x5FF5}, {0xF9A4, 0x637B}, {0xF9A5, 0x6BAE}, {0xF9A6, 0x7C3E}, {0xF9A7, 0x7375}, {0xF9A8, 0x4EE4}, {0xF9A9, 0x56F9}, {0xF9AA, 0x5BE7}, {0xF9AB, 0x5DBA}, {0xF9AC, 0x601C}, {0xF9AD, 0x73B2},
-{0xF9AE, 0x7469}, {0xF9AF, 0x7F9A}, {0xF9B0, 0x8046}, {0xF9B1, 0x9234}, {0xF9B2, 0x96F6}, {0xF9B3, 0x9748}, {0xF9B4, 0x9818}, {0xF9B5, 0x4F8B}, {0xF9B6, 0x79AE}, {0xF9B7, 0x91B4}, {0xF9B8, 0x96B8},
-{0xF9B9, 0x60E1}, {0xF9BA, 0x4E86}, {0xF9BB, 0x50DA}, {0xF9BC, 0x5BEE}, {0xF9BD, 0x5C3F}, {0xF9BE, 0x6599}, {0xF9BF, 0x6A02}, {0xF9C0, 0x71CE}, {0xF9C1, 0x7642}, {0xF9C2, 0x84FC}, {0xF9C3, 0x907C},
-{0xF9C4, 0x9F8D}, {0xF9C5, 0x6688}, {0xF9C6, 0x962E}, {0xF9C7, 0x5289}, {0xF9C8, 0x677B}, {0xF9C9, 0x67F3}, {0xF9CA, 0x6D41}, {0xF9CB, 0x6E9C}, {0xF9CC, 0x7409}, {0xF9CD, 0x7559}, {0xF9CE, 0x786B},
-{0xF9CF, 0x7D10}, {0xF9D0, 0x985E}, {0xF9D1, 0x516D}, {0xF9D2, 0x622E}, {0xF9D3, 0x9678}, {0xF9D4, 0x502B}, {0xF9D5, 0x5D19}, {0xF9D6, 0x6DEA}, {0xF9D7, 0x8F2A}, {0xF9D8, 0x5F8B}, {0xF9D9, 0x6144},
-{0xF9DA, 0x6817}, {0xF9DB, 0x7387}, {0xF9DC, 0x9686}, {0xF9DD, 0x5229}, {0xF9DE, 0x540F}, {0xF9DF, 0x5C65}, {0xF9E0, 0x6613}, {0xF9E1, 0x674E}, {0xF9E2, 0x68A8}, {0xF9E3, 0x6CE5}, {0xF9E4, 0x7406},
-{0xF9E5, 0x75E2}, {0xF9E6, 0x7F79}, {0xF9E7, 0x88CF}, {0xF9E8, 0x88E1}, {0xF9E9, 0x91CC}, {0xF9EA, 0x96E2}, {0xF9EB, 0x533F}, {0xF9EC, 0x6EBA}, {0xF9ED, 0x541D}, {0xF9EE, 0x71D0}, {0xF9EF, 0x7498},
-{0xF9F0, 0x85FA}, {0xF9F1, 0x96A3}, {0xF9F2, 0x9C57}, {0xF9F3, 0x9E9F}, {0xF9F4, 0x6797}, {0xF9F5, 0x6DCB}, {0xF9F6, 0x81E8}, {0xF9F7, 0x7ACB}, {0xF9F8, 0x7B20}, {0xF9F9, 0x7C92}, {0xF9FA, 0x72C0},
-{0xF9FB, 0x7099}, {0xF9FC, 0x8B58}, {0xF9FD, 0x4EC0}, {0xF9FE, 0x8336}, {0xF9FF, 0x523A}, {0xFA00, 0x5207}, {0xFA01, 0x5EA6}, {0xFA02, 0x62D3}, {0xFA03, 0x7CD6}, {0xFA04, 0x5B85}, {0xFA05, 0x6D1E},
-{0xFA06, 0x66B4}, {0xFA07, 0x8F3B}, {0xFA08, 0x884C}, {0xFA09, 0x964D}, {0xFA0A, 0x898B}, {0xFA0B, 0x5ED3}, {0xFA0C, 0x5140}, {0xFA0D, 0x55C0}, {0xFA10, 0x585A}, {0xFA12, 0x6674}, {0xFA15, 0x51DE},
-{0xFA16, 0x732A}, {0xFA17, 0x76CA}, {0xFA18, 0x793C}, {0xFA19, 0x795E}, {0xFA1A, 0x7965}, {0xFA1B, 0x798F}, {0xFA1C, 0x9756}, {0xFA1D, 0x7CBE}, {0xFA1E, 0x7FBD}, {0xFA20, 0x8612}, {0xFA22, 0x8AF8},
-{0xFA25, 0x9038}, {0xFA26, 0x90FD}, {0xFA2A, 0x98EF}, {0xFA2B, 0x98FC}, {0xFA2C, 0x9928}, {0xFA2D, 0x9DB4}, {0xFA2E, 0x90DE}, {0xFA2F, 0x96B7}, {0xFA30, 0x4FAE}, {0xFA31, 0x50E7}, {0xFA32, 0x514D},
-{0xFA33, 0x52C9}, {0xFA34, 0x52E4}, {0xFA35, 0x5351}, {0xFA36, 0x559D}, {0xFA37, 0x5606}, {0xFA38, 0x5668}, {0xFA39, 0x5840}, {0xFA3A, 0x58A8}, {0xFA3B, 0x5C64}, {0xFA3C, 0x5C6E}, {0xFA3D, 0x6094},
-{0xFA3E, 0x6168}, {0xFA3F, 0x618E}, {0xFA40, 0x61F2}, {0xFA41, 0x654F}, {0xFA42, 0x65E2}, {0xFA43, 0x6691}, {0xFA44, 0x6885}, {0xFA45, 0x6D77}, {0xFA46, 0x6E1A}, {0xFA47, 0x6F22}, {0xFA48, 0x716E},
-{0xFA49, 0x722B}, {0xFA4A, 0x7422}, {0xFA4B, 0x7891}, {0xFA4C, 0x793E}, {0xFA4D, 0x7949}, {0xFA4E, 0x7948}, {0xFA4F, 0x7950}, {0xFA50, 0x7956}, {0xFA51, 0x795D}, {0xFA52, 0x798D}, {0xFA53, 0x798E},
-{0xFA54, 0x7A40}, {0xFA55, 0x7A81}, {0xFA56, 0x7BC0}, {0xFA57, 0x7DF4}, {0xFA58, 0x7E09}, {0xFA59, 0x7E41}, {0xFA5A, 0x7F72}, {0xFA5B, 0x8005}, {0xFA5C, 0x81ED}, {0xFA5D, 0x8279}, {0xFA5E, 0x8279},
-{0xFA5F, 0x8457}, {0xFA60, 0x8910}, {0xFA61, 0x8996}, {0xFA62, 0x8B01}, {0xFA63, 0x8B39}, {0xFA64, 0x8CD3}, {0xFA65, 0x8D08}, {0xFA66, 0x8FB6}, {0xFA67, 0x9038}, {0xFA68, 0x96E3}, {0xFA69, 0x97FF},
-{0xFA6A, 0x983B}, {0xFA6B, 0x6075}, {0xFA6C, 0x242EE}, {0xFA6D, 0x8218}, {0xFA70, 0x4E26}, {0xFA71, 0x51B5}, {0xFA72, 0x5168}, {0xFA73, 0x4F80}, {0xFA74, 0x5145}, {0xFA75, 0x5180}, {0xFA76, 0x52C7},
-{0xFA77, 0x52FA}, {0xFA78, 0x559D}, {0xFA79, 0x5555}, {0xFA7A, 0x5599}, {0xFA7B, 0x55E2}, {0xFA7C, 0x585A}, {0xFA7D, 0x58B3}, {0xFA7E, 0x5944}, {0xFA7F, 0x5954}, {0xFA80, 0x5A62}, {0xFA81, 0x5B28},
-{0xFA82, 0x5ED2}, {0xFA83, 0x5ED9}, {0xFA84, 0x5F69}, {0xFA85, 0x5FAD}, {0xFA86, 0x60D8}, {0xFA87, 0x614E}, {0xFA88, 0x6108}, {0xFA89, 0x618E}, {0xFA8A, 0x6160}, {0xFA8B, 0x61F2}, {0xFA8C, 0x6234},
-{0xFA8D, 0x63C4}, {0xFA8E, 0x641C}, {0xFA8F, 0x6452}, {0xFA90, 0x6556}, {0xFA91, 0x6674}, {0xFA92, 0x6717}, {0xFA93, 0x671B}, {0xFA94, 0x6756}, {0xFA95, 0x6B79}, {0xFA96, 0x6BBA}, {0xFA97, 0x6D41},
-{0xFA98, 0x6EDB}, {0xFA99, 0x6ECB}, {0xFA9A, 0x6F22}, {0xFA9B, 0x701E}, {0xFA9C, 0x716E}, {0xFA9D, 0x77A7}, {0xFA9E, 0x7235}, {0xFA9F, 0x72AF}, {0xFAA0, 0x732A}, {0xFAA1, 0x7471}, {0xFAA2, 0x7506},
-{0xFAA3, 0x753B}, {0xFAA4, 0x761D}, {0xFAA5, 0x761F}, {0xFAA6, 0x76CA}, {0xFAA7, 0x76DB}, {0xFAA8, 0x76F4}, {0xFAA9, 0x774A}, {0xFAAA, 0x7740}, {0xFAAB, 0x78CC}, {0xFAAC, 0x7AB1}, {0xFAAD, 0x7BC0},
-{0xFAAE, 0x7C7B}, {0xFAAF, 0x7D5B}, {0xFAB0, 0x7DF4}, {0xFAB1, 0x7F3E}, {0xFAB2, 0x8005}, {0xFAB3, 0x8352}, {0xFAB4, 0x83EF}, {0xFAB5, 0x8779}, {0xFAB6, 0x8941}, {0xFAB7, 0x8986}, {0xFAB8, 0x8996},
-{0xFAB9, 0x8ABF}, {0xFABA, 0x8AF8}, {0xFABB, 0x8ACB}, {0xFABC, 0x8B01}, {0xFABD, 0x8AFE}, {0xFABE, 0x8AED}, {0xFABF, 0x8B39}, {0xFAC0, 0x8B8A}, {0xFAC1, 0x8D08}, {0xFAC2, 0x8F38}, {0xFAC3, 0x9072},
-{0xFAC4, 0x9199}, {0xFAC5, 0x9276}, {0xFAC6, 0x967C}, {0xFAC7, 0x96E3}, {0xFAC8, 0x9756}, {0xFAC9, 0x97DB}, {0xFACA, 0x97FF}, {0xFACB, 0x980B}, {0xFACC, 0x983B}, {0xFACD, 0x9B12}, {0xFACE, 0x9F9C},
-{0xFACF, 0x2284A}, {0xFAD0, 0x22844}, {0xFAD1, 0x233D5}, {0xFAD2, 0x3B9D}, {0xFAD3, 0x4018}, {0xFAD4, 0x4039}, {0xFAD5, 0x25249}, {0xFAD6, 0x25CD0}, {0xFAD7, 0x27ED3}, {0xFAD8, 0x9F43},
-{0xFAD9, 0x9F8E}, {0xFB1D, 0x5D9}, {0xFB1D, 0x5B4}, {0xFB1F, 0x5F2}, {0xFB1F, 0x5B7}, {0xFB2A, 0x5E9}, {0xFB2A, 0x5C1}, {0xFB2B, 0x5E9}, {0xFB2B, 0x5C2}, {0xFB2C, 0x5E9}, {0xFB2C, 0x5BC},
-{0xFB2C, 0x5C1}, {0xFB2D, 0x5E9}, {0xFB2D, 0x5BC}, {0xFB2D, 0x5C2}, {0xFB2E, 0x5D0}, {0xFB2E, 0x5B7}, {0xFB2F, 0x5D0}, {0xFB2F, 0x5B8}, {0xFB30, 0x5D0}, {0xFB30, 0x5BC}, {0xFB31, 0x5D1},
-{0xFB31, 0x5BC}, {0xFB32, 0x5D2}, {0xFB32, 0x5BC}, {0xFB33, 0x5D3}, {0xFB33, 0x5BC}, {0xFB34, 0x5D4}, {0xFB34, 0x5BC}, {0xFB35, 0x5D5}, {0xFB35, 0x5BC}, {0xFB36, 0x5D6}, {0xFB36, 0x5BC},
-{0xFB38, 0x5D8}, {0xFB38, 0x5BC}, {0xFB39, 0x5D9}, {0xFB39, 0x5BC}, {0xFB3A, 0x5DA}, {0xFB3A, 0x5BC}, {0xFB3B, 0x5DB}, {0xFB3B, 0x5BC}, {0xFB3C, 0x5DC}, {0xFB3C, 0x5BC}, {0xFB3E, 0x5DE},
-{0xFB3E, 0x5BC}, {0xFB40, 0x5E0}, {0xFB40, 0x5BC}, {0xFB41, 0x5E1}, {0xFB41, 0x5BC}, {0xFB43, 0x5E3}, {0xFB43, 0x5BC}, {0xFB44, 0x5E4}, {0xFB44, 0x5BC}, {0xFB46, 0x5E6}, {0xFB46, 0x5BC},
-{0xFB47, 0x5E7}, {0xFB47, 0x5BC}, {0xFB48, 0x5E8}, {0xFB48, 0x5BC}, {0xFB49, 0x5E9}, {0xFB49, 0x5BC}, {0xFB4A, 0x5EA}, {0xFB4A, 0x5BC}, {0xFB4B, 0x5D5}, {0xFB4B, 0x5B9}, {0xFB4C, 0x5D1},
-{0xFB4C, 0x5BF}, {0xFB4D, 0x5DB}, {0xFB4D, 0x5BF}, {0xFB4E, 0x5E4}, {0xFB4E, 0x5BF}, {0x1109A, 0x11099}, {0x1109A, 0x110BA}, {0x1109C, 0x1109B}, {0x1109C, 0x110BA}, {0x110AB, 0x110A5},
-{0x110AB, 0x110BA}, {0x1112E, 0x11131}, {0x1112E, 0x11127}, {0x1112F, 0x11132}, {0x1112F, 0x11127}, {0x1134B, 0x11347}, {0x1134B, 0x1133E}, {0x1134C, 0x11347}, {0x1134C, 0x11357}, {0x114BB, 0x114B9},
-{0x114BB, 0x114BA}, {0x114BC, 0x114B9}, {0x114BC, 0x114B0}, {0x114BE, 0x114B9}, {0x114BE, 0x114BD}, {0x115BA, 0x115B8}, {0x115BA, 0x115AF}, {0x115BB, 0x115B9}, {0x115BB, 0x115AF}, {0x1D15E, 0x1D157},
-{0x1D15E, 0x1D165}, {0x1D15F, 0x1D158}, {0x1D15F, 0x1D165}, {0x1D160, 0x1D158}, {0x1D160, 0x1D165}, {0x1D160, 0x1D16E}, {0x1D161, 0x1D158}, {0x1D161, 0x1D165}, {0x1D161, 0x1D16F}, {0x1D162, 0x1D158},
-{0x1D162, 0x1D165}, {0x1D162, 0x1D170}, {0x1D163, 0x1D158}, {0x1D163, 0x1D165}, {0x1D163, 0x1D171}, {0x1D164, 0x1D158}, {0x1D164, 0x1D165}, {0x1D164, 0x1D172}, {0x1D1BB, 0x1D1B9}, {0x1D1BB, 0x1D165},
-{0x1D1BC, 0x1D1BA}, {0x1D1BC, 0x1D165}, {0x1D1BD, 0x1D1B9}, {0x1D1BD, 0x1D165}, {0x1D1BD, 0x1D16E}, {0x1D1BE, 0x1D1BA}, {0x1D1BE, 0x1D165}, {0x1D1BE, 0x1D16E}, {0x1D1BF, 0x1D1B9}, {0x1D1BF, 0x1D165},
-{0x1D1BF, 0x1D16F}, {0x1D1C0, 0x1D1BA}, {0x1D1C0, 0x1D165}, {0x1D1C0, 0x1D16F}, {0x2F800, 0x4E3D}, {0x2F801, 0x4E38}, {0x2F802, 0x4E41}, {0x2F803, 0x20122}, {0x2F804, 0x4F60}, {0x2F805, 0x4FAE},
-{0x2F806, 0x4FBB}, {0x2F807, 0x5002}, {0x2F808, 0x507A}, {0x2F809, 0x5099}, {0x2F80A, 0x50E7}, {0x2F80B, 0x50CF}, {0x2F80C, 0x349E}, {0x2F80D, 0x2063A}, {0x2F80E, 0x514D}, {0x2F80F, 0x5154},
-{0x2F810, 0x5164}, {0x2F811, 0x5177}, {0x2F812, 0x2051C}, {0x2F813, 0x34B9}, {0x2F814, 0x5167}, {0x2F815, 0x518D}, {0x2F816, 0x2054B}, {0x2F817, 0x5197}, {0x2F818, 0x51A4}, {0x2F819, 0x4ECC},
-{0x2F81A, 0x51AC}, {0x2F81B, 0x51B5}, {0x2F81C, 0x291DF}, {0x2F81D, 0x51F5}, {0x2F81E, 0x5203}, {0x2F81F, 0x34DF}, {0x2F820, 0x523B}, {0x2F821, 0x5246}, {0x2F822, 0x5272}, {0x2F823, 0x5277},
-{0x2F824, 0x3515}, {0x2F825, 0x52C7}, {0x2F826, 0x52C9}, {0x2F827, 0x52E4}, {0x2F828, 0x52FA}, {0x2F829, 0x5305}, {0x2F82A, 0x5306}, {0x2F82B, 0x5317}, {0x2F82C, 0x5349}, {0x2F82D, 0x5351},
-{0x2F82E, 0x535A}, {0x2F82F, 0x5373}, {0x2F830, 0x537D}, {0x2F831, 0x537F}, {0x2F832, 0x537F}, {0x2F833, 0x537F}, {0x2F834, 0x20A2C}, {0x2F835, 0x7070}, {0x2F836, 0x53CA}, {0x2F837, 0x53DF},
-{0x2F838, 0x20B63}, {0x2F839, 0x53EB}, {0x2F83A, 0x53F1}, {0x2F83B, 0x5406}, {0x2F83C, 0x549E}, {0x2F83D, 0x5438}, {0x2F83E, 0x5448}, {0x2F83F, 0x5468}, {0x2F840, 0x54A2}, {0x2F841, 0x54F6},
-{0x2F842, 0x5510}, {0x2F843, 0x5553}, {0x2F844, 0x5563}, {0x2F845, 0x5584}, {0x2F846, 0x5584}, {0x2F847, 0x5599}, {0x2F848, 0x55AB}, {0x2F849, 0x55B3}, {0x2F84A, 0x55C2}, {0x2F84B, 0x5716},
-{0x2F84C, 0x5606}, {0x2F84D, 0x5717}, {0x2F84E, 0x5651}, {0x2F84F, 0x5674}, {0x2F850, 0x5207}, {0x2F851, 0x58EE}, {0x2F852, 0x57CE}, {0x2F853, 0x57F4}, {0x2F854, 0x580D}, {0x2F855, 0x578B},
-{0x2F856, 0x5832}, {0x2F857, 0x5831}, {0x2F858, 0x58AC}, {0x2F859, 0x214E4}, {0x2F85A, 0x58F2}, {0x2F85B, 0x58F7}, {0x2F85C, 0x5906}, {0x2F85D, 0x591A}, {0x2F85E, 0x5922}, {0x2F85F, 0x5962},
-{0x2F860, 0x216A8}, {0x2F861, 0x216EA}, {0x2F862, 0x59EC}, {0x2F863, 0x5A1B}, {0x2F864, 0x5A27}, {0x2F865, 0x59D8}, {0x2F866, 0x5A66}, {0x2F867, 0x36EE}, {0x2F868, 0x36FC}, {0x2F869, 0x5B08},
-{0x2F86A, 0x5B3E}, {0x2F86B, 0x5B3E}, {0x2F86C, 0x219C8}, {0x2F86D, 0x5BC3}, {0x2F86E, 0x5BD8}, {0x2F86F, 0x5BE7}, {0x2F870, 0x5BF3}, {0x2F871, 0x21B18}, {0x2F872, 0x5BFF}, {0x2F873, 0x5C06},
-{0x2F874, 0x5F53}, {0x2F875, 0x5C22}, {0x2F876, 0x3781}, {0x2F877, 0x5C60}, {0x2F878, 0x5C6E}, {0x2F879, 0x5CC0}, {0x2F87A, 0x5C8D}, {0x2F87B, 0x21DE4}, {0x2F87C, 0x5D43}, {0x2F87D, 0x21DE6},
-{0x2F87E, 0x5D6E}, {0x2F87F, 0x5D6B}, {0x2F880, 0x5D7C}, {0x2F881, 0x5DE1}, {0x2F882, 0x5DE2}, {0x2F883, 0x382F}, {0x2F884, 0x5DFD}, {0x2F885, 0x5E28}, {0x2F886, 0x5E3D}, {0x2F887, 0x5E69},
-{0x2F888, 0x3862}, {0x2F889, 0x22183}, {0x2F88A, 0x387C}, {0x2F88B, 0x5EB0}, {0x2F88C, 0x5EB3}, {0x2F88D, 0x5EB6}, {0x2F88E, 0x5ECA}, {0x2F88F, 0x2A392}, {0x2F890, 0x5EFE}, {0x2F891, 0x22331},
-{0x2F892, 0x22331}, {0x2F893, 0x8201}, {0x2F894, 0x5F22}, {0x2F895, 0x5F22}, {0x2F896, 0x38C7}, {0x2F897, 0x232B8}, {0x2F898, 0x261DA}, {0x2F899, 0x5F62}, {0x2F89A, 0x5F6B}, {0x2F89B, 0x38E3},
-{0x2F89C, 0x5F9A}, {0x2F89D, 0x5FCD}, {0x2F89E, 0x5FD7}, {0x2F89F, 0x5FF9}, {0x2F8A0, 0x6081}, {0x2F8A1, 0x393A}, {0x2F8A2, 0x391C}, {0x2F8A3, 0x6094}, {0x2F8A4, 0x226D4}, {0x2F8A5, 0x60C7},
-{0x2F8A6, 0x6148}, {0x2F8A7, 0x614C}, {0x2F8A8, 0x614E}, {0x2F8A9, 0x614C}, {0x2F8AA, 0x617A}, {0x2F8AB, 0x618E}, {0x2F8AC, 0x61B2}, {0x2F8AD, 0x61A4}, {0x2F8AE, 0x61AF}, {0x2F8AF, 0x61DE},
-{0x2F8B0, 0x61F2}, {0x2F8B1, 0x61F6}, {0x2F8B2, 0x6210}, {0x2F8B3, 0x621B}, {0x2F8B4, 0x625D}, {0x2F8B5, 0x62B1}, {0x2F8B6, 0x62D4}, {0x2F8B7, 0x6350}, {0x2F8B8, 0x22B0C}, {0x2F8B9, 0x633D},
-{0x2F8BA, 0x62FC}, {0x2F8BB, 0x6368}, {0x2F8BC, 0x6383}, {0x2F8BD, 0x63E4}, {0x2F8BE, 0x22BF1}, {0x2F8BF, 0x6422}, {0x2F8C0, 0x63C5}, {0x2F8C1, 0x63A9}, {0x2F8C2, 0x3A2E}, {0x2F8C3, 0x6469},
-{0x2F8C4, 0x647E}, {0x2F8C5, 0x649D}, {0x2F8C6, 0x6477}, {0x2F8C7, 0x3A6C}, {0x2F8C8, 0x654F}, {0x2F8C9, 0x656C}, {0x2F8CA, 0x2300A}, {0x2F8CB, 0x65E3}, {0x2F8CC, 0x66F8}, {0x2F8CD, 0x6649},
-{0x2F8CE, 0x3B19}, {0x2F8CF, 0x6691}, {0x2F8D0, 0x3B08}, {0x2F8D1, 0x3AE4}, {0x2F8D2, 0x5192}, {0x2F8D3, 0x5195}, {0x2F8D4, 0x6700}, {0x2F8D5, 0x669C}, {0x2F8D6, 0x80AD}, {0x2F8D7, 0x43D9},
-{0x2F8D8, 0x6717}, {0x2F8D9, 0x671B}, {0x2F8DA, 0x6721}, {0x2F8DB, 0x675E}, {0x2F8DC, 0x6753}, {0x2F8DD, 0x233C3}, {0x2F8DE, 0x3B49}, {0x2F8DF, 0x67FA}, {0x2F8E0, 0x6785}, {0x2F8E1, 0x6852},
-{0x2F8E2, 0x6885}, {0x2F8E3, 0x2346D}, {0x2F8E4, 0x688E}, {0x2F8E5, 0x681F}, {0x2F8E6, 0x6914}, {0x2F8E7, 0x3B9D}, {0x2F8E8, 0x6942}, {0x2F8E9, 0x69A3}, {0x2F8EA, 0x69EA}, {0x2F8EB, 0x6AA8},
-{0x2F8EC, 0x236A3}, {0x2F8ED, 0x6ADB}, {0x2F8EE, 0x3C18}, {0x2F8EF, 0x6B21}, {0x2F8F0, 0x238A7}, {0x2F8F1, 0x6B54}, {0x2F8F2, 0x3C4E}, {0x2F8F3, 0x6B72}, {0x2F8F4, 0x6B9F}, {0x2F8F5, 0x6BBA},
-{0x2F8F6, 0x6BBB}, {0x2F8F7, 0x23A8D}, {0x2F8F8, 0x21D0B}, {0x2F8F9, 0x23AFA}, {0x2F8FA, 0x6C4E}, {0x2F8FB, 0x23CBC}, {0x2F8FC, 0x6CBF}, {0x2F8FD, 0x6CCD}, {0x2F8FE, 0x6C67}, {0x2F8FF, 0x6D16},
-{0x2F900, 0x6D3E}, {0x2F901, 0x6D77}, {0x2F902, 0x6D41}, {0x2F903, 0x6D69}, {0x2F904, 0x6D78}, {0x2F905, 0x6D85}, {0x2F906, 0x23D1E}, {0x2F907, 0x6D34}, {0x2F908, 0x6E2F}, {0x2F909, 0x6E6E},
-{0x2F90A, 0x3D33}, {0x2F90B, 0x6ECB}, {0x2F90C, 0x6EC7}, {0x2F90D, 0x23ED1}, {0x2F90E, 0x6DF9}, {0x2F90F, 0x6F6E}, {0x2F910, 0x23F5E}, {0x2F911, 0x23F8E}, {0x2F912, 0x6FC6}, {0x2F913, 0x7039},
-{0x2F914, 0x701E}, {0x2F915, 0x701B}, {0x2F916, 0x3D96}, {0x2F917, 0x704A}, {0x2F918, 0x707D}, {0x2F919, 0x7077}, {0x2F91A, 0x70AD}, {0x2F91B, 0x20525}, {0x2F91C, 0x7145}, {0x2F91D, 0x24263},
-{0x2F91E, 0x719C}, {0x2F91F, 0x243AB}, {0x2F920, 0x7228}, {0x2F921, 0x7235}, {0x2F922, 0x7250}, {0x2F923, 0x24608}, {0x2F924, 0x7280}, {0x2F925, 0x7295}, {0x2F926, 0x24735}, {0x2F927, 0x24814},
-{0x2F928, 0x737A}, {0x2F929, 0x738B}, {0x2F92A, 0x3EAC}, {0x2F92B, 0x73A5}, {0x2F92C, 0x3EB8}, {0x2F92D, 0x3EB8}, {0x2F92E, 0x7447}, {0x2F92F, 0x745C}, {0x2F930, 0x7471}, {0x2F931, 0x7485},
-{0x2F932, 0x74CA}, {0x2F933, 0x3F1B}, {0x2F934, 0x7524}, {0x2F935, 0x24C36}, {0x2F936, 0x753E}, {0x2F937, 0x24C92}, {0x2F938, 0x7570}, {0x2F939, 0x2219F}, {0x2F93A, 0x7610}, {0x2F93B, 0x24FA1},
-{0x2F93C, 0x24FB8}, {0x2F93D, 0x25044}, {0x2F93E, 0x3FFC}, {0x2F93F, 0x4008}, {0x2F940, 0x76F4}, {0x2F941, 0x250F3}, {0x2F942, 0x250F2}, {0x2F943, 0x25119}, {0x2F944, 0x25133}, {0x2F945, 0x771E},
-{0x2F946, 0x771F}, {0x2F947, 0x771F}, {0x2F948, 0x774A}, {0x2F949, 0x4039}, {0x2F94A, 0x778B}, {0x2F94B, 0x4046}, {0x2F94C, 0x4096}, {0x2F94D, 0x2541D}, {0x2F94E, 0x784E}, {0x2F94F, 0x788C},
-{0x2F950, 0x78CC}, {0x2F951, 0x40E3}, {0x2F952, 0x25626}, {0x2F953, 0x7956}, {0x2F954, 0x2569A}, {0x2F955, 0x256C5}, {0x2F956, 0x798F}, {0x2F957, 0x79EB}, {0x2F958, 0x412F}, {0x2F959, 0x7A40},
-{0x2F95A, 0x7A4A}, {0x2F95B, 0x7A4F}, {0x2F95C, 0x2597C}, {0x2F95D, 0x25AA7}, {0x2F95E, 0x25AA7}, {0x2F95F, 0x7AEE}, {0x2F960, 0x4202}, {0x2F961, 0x25BAB}, {0x2F962, 0x7BC6}, {0x2F963, 0x7BC9},
-{0x2F964, 0x4227}, {0x2F965, 0x25C80}, {0x2F966, 0x7CD2}, {0x2F967, 0x42A0}, {0x2F968, 0x7CE8}, {0x2F969, 0x7CE3}, {0x2F96A, 0x7D00}, {0x2F96B, 0x25F86}, {0x2F96C, 0x7D63}, {0x2F96D, 0x4301},
-{0x2F96E, 0x7DC7}, {0x2F96F, 0x7E02}, {0x2F970, 0x7E45}, {0x2F971, 0x4334}, {0x2F972, 0x26228}, {0x2F973, 0x26247}, {0x2F974, 0x4359}, {0x2F975, 0x262D9}, {0x2F976, 0x7F7A}, {0x2F977, 0x2633E},
-{0x2F978, 0x7F95}, {0x2F979, 0x7FFA}, {0x2F97A, 0x8005}, {0x2F97B, 0x264DA}, {0x2F97C, 0x26523}, {0x2F97D, 0x8060}, {0x2F97E, 0x265A8}, {0x2F97F, 0x8070}, {0x2F980, 0x2335F}, {0x2F981, 0x43D5},
-{0x2F982, 0x80B2}, {0x2F983, 0x8103}, {0x2F984, 0x440B}, {0x2F985, 0x813E}, {0x2F986, 0x5AB5}, {0x2F987, 0x267A7}, {0x2F988, 0x267B5}, {0x2F989, 0x23393}, {0x2F98A, 0x2339C}, {0x2F98B, 0x8201},
-{0x2F98C, 0x8204}, {0x2F98D, 0x8F9E}, {0x2F98E, 0x446B}, {0x2F98F, 0x8291}, {0x2F990, 0x828B}, {0x2F991, 0x829D}, {0x2F992, 0x52B3}, {0x2F993, 0x82B1}, {0x2F994, 0x82B3}, {0x2F995, 0x82BD},
-{0x2F996, 0x82E6}, {0x2F997, 0x26B3C}, {0x2F998, 0x82E5}, {0x2F999, 0x831D}, {0x2F99A, 0x8363}, {0x2F99B, 0x83AD}, {0x2F99C, 0x8323}, {0x2F99D, 0x83BD}, {0x2F99E, 0x83E7}, {0x2F99F, 0x8457},
-{0x2F9A0, 0x8353}, {0x2F9A1, 0x83CA}, {0x2F9A2, 0x83CC}, {0x2F9A3, 0x83DC}, {0x2F9A4, 0x26C36}, {0x2F9A5, 0x26D6B}, {0x2F9A6, 0x26CD5}, {0x2F9A7, 0x452B}, {0x2F9A8, 0x84F1}, {0x2F9A9, 0x84F3},
-{0x2F9AA, 0x8516}, {0x2F9AB, 0x273CA}, {0x2F9AC, 0x8564}, {0x2F9AD, 0x26F2C}, {0x2F9AE, 0x455D}, {0x2F9AF, 0x4561}, {0x2F9B0, 0x26FB1}, {0x2F9B1, 0x270D2}, {0x2F9B2, 0x456B}, {0x2F9B3, 0x8650},
-{0x2F9B4, 0x865C}, {0x2F9B5, 0x8667}, {0x2F9B6, 0x8669}, {0x2F9B7, 0x86A9}, {0x2F9B8, 0x8688}, {0x2F9B9, 0x870E}, {0x2F9BA, 0x86E2}, {0x2F9BB, 0x8779}, {0x2F9BC, 0x8728}, {0x2F9BD, 0x876B},
-{0x2F9BE, 0x8786}, {0x2F9BF, 0x45D7}, {0x2F9C0, 0x87E1}, {0x2F9C1, 0x8801}, {0x2F9C2, 0x45F9}, {0x2F9C3, 0x8860}, {0x2F9C4, 0x8863}, {0x2F9C5, 0x27667}, {0x2F9C6, 0x88D7}, {0x2F9C7, 0x88DE},
-{0x2F9C8, 0x4635}, {0x2F9C9, 0x88FA}, {0x2F9CA, 0x34BB}, {0x2F9CB, 0x278AE}, {0x2F9CC, 0x27966}, {0x2F9CD, 0x46BE}, {0x2F9CE, 0x46C7}, {0x2F9CF, 0x8AA0}, {0x2F9D0, 0x8AED}, {0x2F9D1, 0x8B8A},
-{0x2F9D2, 0x8C55}, {0x2F9D3, 0x27CA8}, {0x2F9D4, 0x8CAB}, {0x2F9D5, 0x8CC1}, {0x2F9D6, 0x8D1B}, {0x2F9D7, 0x8D77}, {0x2F9D8, 0x27F2F}, {0x2F9D9, 0x20804}, {0x2F9DA, 0x8DCB}, {0x2F9DB, 0x8DBC},
-{0x2F9DC, 0x8DF0}, {0x2F9DD, 0x208DE}, {0x2F9DE, 0x8ED4}, {0x2F9DF, 0x8F38}, {0x2F9E0, 0x285D2}, {0x2F9E1, 0x285ED}, {0x2F9E2, 0x9094}, {0x2F9E3, 0x90F1}, {0x2F9E4, 0x9111}, {0x2F9E5, 0x2872E},
-{0x2F9E6, 0x911B}, {0x2F9E7, 0x9238}, {0x2F9E8, 0x92D7}, {0x2F9E9, 0x92D8}, {0x2F9EA, 0x927C}, {0x2F9EB, 0x93F9}, {0x2F9EC, 0x9415}, {0x2F9ED, 0x28BFA}, {0x2F9EE, 0x958B}, {0x2F9EF, 0x4995},
-{0x2F9F0, 0x95B7}, {0x2F9F1, 0x28D77}, {0x2F9F2, 0x49E6}, {0x2F9F3, 0x96C3}, {0x2F9F4, 0x5DB2}, {0x2F9F5, 0x9723}, {0x2F9F6, 0x29145}, {0x2F9F7, 0x2921A}, {0x2F9F8, 0x4A6E}, {0x2F9F9, 0x4A76},
-{0x2F9FA, 0x97E0}, {0x2F9FB, 0x2940A}, {0x2F9FC, 0x4AB2}, {0x2F9FD, 0x29496}, {0x2F9FE, 0x980B}, {0x2F9FF, 0x980B}, {0x2FA00, 0x9829}, {0x2FA01, 0x295B6}, {0x2FA02, 0x98E2}, {0x2FA03, 0x4B33},
-{0x2FA04, 0x9929}, {0x2FA05, 0x99A7}, {0x2FA06, 0x99C2}, {0x2FA07, 0x99FE}, {0x2FA08, 0x4BCE}, {0x2FA09, 0x29B30}, {0x2FA0A, 0x9B12}, {0x2FA0B, 0x9C40}, {0x2FA0C, 0x9CFD}, {0x2FA0D, 0x4CCE},
-{0x2FA0E, 0x4CED}, {0x2FA0F, 0x9D67}, {0x2FA10, 0x2A0CE}, {0x2FA11, 0x4CF8}, {0x2FA12, 0x2A105}, {0x2FA13, 0x2A20E}, {0x2FA14, 0x2A291}, {0x2FA15, 0x9EBB}, {0x2FA16, 0x4D56}, {0x2FA17, 0x9EF9},
-{0x2FA18, 0x9EFE}, {0x2FA19, 0x9F05}, {0x2FA1A, 0x9F0F}, {0x2FA1B, 0x9F16}, {0x2FA1D, 0x2A600},
-};
-
-static std::string codepoint_to_utf8(uint32_t cp) {
-    std::string result;
-    if (/* 0x00 <= cp && */ cp <= 0x7f) {
-        result.push_back(cp);
-    }
-    else if (0x80 <= cp && cp <= 0x7ff) {
-        result.push_back(0xc0 | ((cp >> 6) & 0x1f));
-        result.push_back(0x80 | (cp & 0x3f));
-    }
-    else if (0x800 <= cp && cp <= 0xffff) {
-        result.push_back(0xe0 | ((cp >> 12) & 0x0f));
-        result.push_back(0x80 | ((cp >> 6) & 0x3f));
-        result.push_back(0x80 | (cp & 0x3f));
-    }
-    else if (0x10000 <= cp && cp <= 0x10ffff) {
-        result.push_back(0xf0 | ((cp >> 18) & 0x07));
-        result.push_back(0x80 | ((cp >> 12) & 0x3f));
-        result.push_back(0x80 | ((cp >> 6) & 0x3f));
-        result.push_back(0x80 | (cp & 0x3f));
-    }
-    else {
-        throw std::invalid_argument("invalid codepoint");
-    }
-    return result;
-}
-
-static std::string codepoints_to_utf8(const std::vector<uint32_t> & cps) {
-    std::string result;
-    for (size_t i = 0; i < cps.size(); ++i) {
-        result.append(codepoint_to_utf8(cps[i]));
-    }
-    return result;
-}
-
-static uint32_t codepoint_from_utf8(const std::string & utf8, size_t & offset) {
-    assert(offset < utf8.size());
-    if (!(utf8[offset + 0] & 0x80)) {
-        auto result = utf8[offset + 0];
-        offset += 1;
-        return result;
-    }
-    if (!(utf8[offset + 0] & 0x40)) {
-        throw std::invalid_argument("invalid character");
-    }
-    if (!(utf8[offset + 0] & 0x20)) {
-        if (offset + 1 >= utf8.size() || ! ((utf8[offset + 1] & 0xc0) == 0x80)) {
-            throw std::invalid_argument("invalid character");
-        }
-        auto result = ((utf8[offset + 0] & 0x1f) << 6) | (utf8[offset + 1] & 0x3f);
-        offset += 2;
-        return result;
-    }
-    if (!(utf8[offset + 0] & 0x10)) {
-        if (offset + 2 >= utf8.size() || ! ((utf8[offset + 1] & 0xc0) == 0x80) || ! ((utf8[offset + 2] & 0xc0) == 0x80)) {
-            throw std::invalid_argument("invalid character");
-        }
-        auto result = ((utf8[offset + 0] & 0x0f) << 12) | ((utf8[offset + 1] & 0x3f) << 6) | (utf8[offset + 2] & 0x3f);
-        offset += 3;
-        return result;
-    }
-    if (!(utf8[offset + 0] & 0x08)) {
-        if (offset + 3 >= utf8.size() || ! ((utf8[offset + 1] & 0xc0) == 0x80) || ! ((utf8[offset + 2] & 0xc0) == 0x80) || !((utf8[offset + 3] & 0xc0) == 0x80)) {
-            throw std::invalid_argument("invalid character");
-        }
-        auto result = ((utf8[offset + 0] & 0x07) << 18) | ((utf8[offset + 1] & 0x3f) << 12) | ((utf8[offset + 2] & 0x3f) << 6) | (utf8[offset + 3] & 0x3f);
-        offset += 4;
-        return result;
-    }
-    throw std::invalid_argument("invalid string");
-}
-
-static std::vector<uint32_t> codepoints_from_utf8(const std::string & utf8) {
-    std::vector<uint32_t> result;
-    size_t offset = 0;
-    while (offset < utf8.size()) {
-        result.push_back(codepoint_from_utf8(utf8, offset));
-    }
-    return result;
-}
-
-static std::vector<uint16_t> codepoint_to_utf16(uint32_t cp) {
-    std::vector<uint16_t> result;
-    if (/* 0x0000 <= cp && */ cp <= 0xffff) {
-        result.emplace_back(cp);
-    }
-    else if (0x10000 <= cp && cp <= 0x10ffff) {
-        result.emplace_back(0xd800 | ((cp - 0x10000) >> 10));
-        result.emplace_back(0xdc00 | ((cp - 0x10000) & 0x03ff));
-    }
-    else {
-        throw std::invalid_argument("invalid codepoint");
-    }
-    return result;
-}
-
-static std::vector<uint16_t> codepoints_to_utf16(const std::vector<uint32_t> & cps) {
-    std::vector<uint16_t> result;
-    for (size_t i = 0; i < cps.size(); ++i) {
-        auto temp = codepoint_to_utf16(cps[i]);
-        result.insert(result.end(), temp.begin(), temp.end());
-    }
-    return result;
-}
-
-static uint32_t codepoint_from_utf16(const std::vector<uint16_t> & utf16, size_t & offset) {
-    assert(offset < utf16.size());
-    if (((utf16[0] >> 10) << 10) != 0xd800) {
-        auto result = utf16[offset + 0];
-        offset += 1;
-        return result;
-    }
-
-    if (offset + 1 >= utf16.size() || !((utf16[1] & 0xdc00) == 0xdc00)) {
-        throw std::invalid_argument("invalid character");
-    }
-
-    auto result = 0x10000 + (((utf16[0] & 0x03ff) << 10) | (utf16[1] & 0x03ff));
-    offset += 2;
-    return result;
-}
-
-static std::vector<uint32_t> codepoints_from_utf16(const std::vector<uint16_t> & utf16) {
-    std::vector<uint32_t> result;
-    size_t offset = 0;
-    while (offset < utf16.size()) {
-        result.push_back(codepoint_from_utf16(utf16, offset));
-    }
-    return result;
-}
-
 #define CODEPOINT_TYPE_UNIDENTIFIED 0
-#define CODEPOINT_TYPE_DIGIT 1
-#define CODEPOINT_TYPE_LETTER 2
-#define CODEPOINT_TYPE_WHITESPACE 3
-#define CODEPOINT_TYPE_ACCENT_MARK 4
-#define CODEPOINT_TYPE_PUNCTUATION 5
-#define CODEPOINT_TYPE_SYMBOL 6
-#define CODEPOINT_TYPE_CONTROL 7
+#define CODEPOINT_TYPE_DIGIT        1
+#define CODEPOINT_TYPE_LETTER       2
+#define CODEPOINT_TYPE_WHITESPACE   3
+#define CODEPOINT_TYPE_ACCENT_MARK  4
+#define CODEPOINT_TYPE_PUNCTUATION  5
+#define CODEPOINT_TYPE_SYMBOL       6
+#define CODEPOINT_TYPE_CONTROL      7
 
-static std::unordered_map<uint32_t, int> codepoint_type_map() {
-    std::unordered_map<uint32_t, int> codepoint_types;
-    for (auto p : digit_ranges) {
-        for (auto i = p.first; i <= p.second; ++ i) {
-            codepoint_types[i] = CODEPOINT_TYPE_DIGIT;
-        }
-    }
-    for (auto p : letter_ranges) {
-        for (auto i = p.first; i <= p.second; ++ i) {
-            codepoint_types[i] = CODEPOINT_TYPE_LETTER;
-        }
-    }
-    for (auto p : whitespace_ranges) {
-        for (auto i = p.first; i <= p.second; ++ i) {
-            codepoint_types[i] = CODEPOINT_TYPE_WHITESPACE;
-        }
-    }
-    for (auto p : accent_mark_ranges) {
-        for (auto i = p.first; i <= p.second; ++ i) {
-            codepoint_types[i] = CODEPOINT_TYPE_ACCENT_MARK;
-        }
-    }
-    for (auto p : punctuation_ranges) {
-        for (auto i = p.first; i <= p.second; ++ i) {
-            codepoint_types[i] = CODEPOINT_TYPE_PUNCTUATION;
-        }
-    }
-    for  (auto p : symbol_ranges) {
-        for (auto i = p.first; i <= p.second; ++i) {
-            codepoint_types[i] = CODEPOINT_TYPE_SYMBOL;
-        }
-    }
-    for (auto p : control_ranges) {
-        for (auto i = p.first; i <= p.second; ++ i) {
-            codepoint_types[i] = CODEPOINT_TYPE_CONTROL;
-        }
-    }
-    return codepoint_types;
-}
+std::string unicode_cpt_to_utf8(uint32_t cp);
+std::vector<uint32_t> unicode_cpts_from_utf8(const std::string & utf8);
 
-static int codepoint_type(uint32_t cp) {
-    static std::unordered_map<uint32_t, int> codepoint_types = codepoint_type_map();
-    const auto it = codepoint_types.find(cp);
-    return it == codepoint_types.end() ? CODEPOINT_TYPE_UNIDENTIFIED : it->second;
-}
+std::vector<uint32_t> unicode_cpts_normalize_nfd(const std::vector<uint32_t> & cpts);
 
-static int codepoint_type(const std::string & utf8) {
-    if (utf8.length() == 0) {
-        return CODEPOINT_TYPE_UNIDENTIFIED;
-    }
-    size_t offset = 0;
-    return codepoint_type(codepoint_from_utf8(utf8, offset));
-}
+int unicode_cpt_type(uint32_t cp);
+int unicode_cpt_type(const std::string & utf8);
 
-static std::unordered_map<uint8_t, std::string> bytes_to_unicode_map_bpe() {
-    std::unordered_map<uint8_t, std::string> map;
-    for (int ch = u'!'; ch <= u'~'; ++ch) {
-        assert(0 <= ch && ch < 256);
-        map[ch] = codepoint_to_utf8(ch);
-    }
-    for (int ch = u'¡'; ch <= u'¬'; ++ch) {
-        assert(0 <= ch && ch < 256);
-        map[ch] = codepoint_to_utf8(ch);
-    }
-    for (int ch = u'®'; ch <= u'ÿ'; ++ch) {
-        assert(0 <= ch && ch < 256);
-        map[ch] = codepoint_to_utf8(ch);
-    }
-    auto n = 0;
-    for (int ch = 0; ch < 256; ++ch) {
-        if (map.find(ch) == map.end()) {
-            map[ch] = codepoint_to_utf8(256 + n);
-            ++n;
-        }
-    }
-    return map;
-}
-
-static std::string bytes_to_unicode_bpe(uint8_t byte) {
-    static std::unordered_map<uint8_t, std::string> map = bytes_to_unicode_map_bpe();
-    return map.at(byte);
-}
-
-static std::unordered_map<std::string, uint8_t> unicode_to_bytes_map_bpe() {
-    std::unordered_map<std::string, uint8_t> map;
-    for (int ch = u'!'; ch <= u'~'; ++ch) {
-        assert(0 <= ch && ch < 256);
-        map[codepoint_to_utf8(ch)] = ch;
-    }
-    for (int ch = u'¡'; ch <= u'¬'; ++ch) {
-        assert(0 <= ch && ch < 256);
-        map[codepoint_to_utf8(ch)] = ch;
-    }
-    for (int ch = u'®'; ch <= u'ÿ'; ++ch) {
-        assert(0 <= ch && ch < 256);
-        map[codepoint_to_utf8(ch)] = ch;
-    }
-    auto n = 0;
-    for (int ch = 0; ch < 256; ++ch) {
-        if (map.find(codepoint_to_utf8(ch)) == map.end()) {
-            map[codepoint_to_utf8(256 + n)] = ch;
-            ++n;
-        }
-    }
-    return map;
-}
-
-static uint8_t unicode_to_bytes_bpe(const std::string & utf8) {
-    static std::unordered_map<std::string, uint8_t> map = unicode_to_bytes_map_bpe();
-    return map.at(utf8);
-}
+std::string unicode_byte_to_utf8(uint8_t byte);
+uint8_t unicode_utf8_to_byte(const std::string & utf8);