diff --git a/CMakeLists.txt b/CMakeLists.txt index 0ed4fc4..b27062f 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -26,6 +26,8 @@ option(GGML_FMA "ggml: enable FMA" option(GGML_CUBLAS "ggml: use cuBLAS" OFF) option(GGML_METAL "ggml: use Metal" OFF) +option(BERT_BUILD_TESTS "bert: Build tests" ON) + # # Compile flags # @@ -94,3 +96,8 @@ install(TARGETS ggml LIBRARY DESTINATION bert_cpp) # add bert add_subdirectory(src) + +if (BERT_BUILD_TESTS) + include(CTest) + add_subdirectory(tests) +endif () diff --git a/tests/CMakeLists.txt b/tests/CMakeLists.txt new file mode 100644 index 0000000..4503cb0 --- /dev/null +++ b/tests/CMakeLists.txt @@ -0,0 +1,24 @@ +include_directories(${CMAKE_SOURCE_DIR}/src) + +# add_executable(test_tokenizer test_tokenizer.cpp) +# target_link_libraries(test_tokenizer PRIVATE bert ggml) + +set(TEST_MODEL_NAME "bge-large-zh-v1.5") + +function(bert_build_executable source) + get_filename_component(TEST_TARGET ${source} NAME_WE) + add_executable(${TEST_TARGET} ${source}) + install(TARGETS ${TEST_TARGET} RUNTIME) + target_link_libraries(${TEST_TARGET} PRIVATE bert ggml) +endfunction() + +function(bert_test_executable name source) + get_filename_component(TEST_TARGET ${source} NAME_WE) + add_test(NAME "Generate_HF_tokens" COMMAND python3 ${CMAKE_CURRENT_SOURCE_DIR}/test_hf_tokenizer.py ${TEST_MODEL_NAME}) + add_test(NAME ${name} COMMAND $ ${ARGN}) + set_property(TEST ${name} PROPERTY LABELS "main") +endfunction() + + +bert_build_executable(test_tokenizer.cpp) +bert_test_executable (test_tokenizer test_tokenizer.cpp -m ${CMAKE_CURRENT_SOURCE_DIR}/../models/${TEST_MODEL_NAME}/bge-large-zh-v1.5-q4_1.gguf) diff --git a/tests/test.sh b/tests/test.sh new file mode 100755 index 0000000..6e15c36 --- /dev/null +++ b/tests/test.sh @@ -0,0 +1,19 @@ +#!/usr/bin/env bash + +set -e + +SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd ) +MODEL_NAME=${1:-bge-large-zh-v1.5} +MODEL_DIR=$(realpath "$SCRIPT_DIR/../models/$MODEL_NAME") + +if [ ! -d "$MODEL_DIR" ]; then + python3 $SCRIPT_DIR/../models/download-repo.py $MODEL_NAME +fi + +if [ ! -d "$MODEL_DIR/ggml-model-q4_1.gguf" ]; then + $SCRIPT_DIR/../models/run_conversions.sh $MODEL_NAME q4_1 +fi + +python3 $SCRIPT_DIR/test_hf_tokenizer.py $MODEL_DIR + +$SCRIPT_DIR/../build/bin/test_tokenizer -m $MODEL_DIR/ggml-model-q4_1.gguf diff --git a/tests/test_hf_tokenizer.py b/tests/test_hf_tokenizer.py new file mode 100644 index 0000000..58d2550 --- /dev/null +++ b/tests/test_hf_tokenizer.py @@ -0,0 +1,39 @@ +from ast import arg +from transformers import AutoTokenizer, AutoModel +import argparse +import os + +SCRIPT_PATH=os.path.dirname(os.path.realpath(__file__)) + +def main(args): + # tokenizer_name = "sentence-transformers/multi-qa-MiniLM-L6-cos-v1" + if "/" in args.model_name: + tokenizer_name = args.model_name + elif "MiniLM" in args.model_name: + tokenizer_name = f"sentence-transformers/{args.model_name}" + elif "bge-" in args.model_name: + tokenizer_name = f"BAAI/{args.model_name}" + else: + raise ValueError(f"Unknown model name: {args.model_name}") + tokenizer = AutoTokenizer.from_pretrained(tokenizer_name) + + with open(SCRIPT_PATH + "/test_prompts.txt", "r", encoding="utf-8") as f: + inps = f.readlines() + inps = list(map(lambda x: x.strip(), inps)) + + print("Using tokenizer:", tokenizer_name) + output = [] + for inp in inps: + oup = tokenizer(inp, return_tensors="pt").input_ids[0].tolist() + output.append(",".join([str(x) for x in oup])) + for token in oup: + print(f"{token} <--> {tokenizer.decode([token])}") + + with open(SCRIPT_PATH + "/hf_tokenized_ids.txt", "w", encoding="utf-8") as f: + f.write("\n".join(output)) + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description='Download original repo files') + parser.add_argument('model_name', type=str, help='Name of the repo') + args = parser.parse_args() + main(args) diff --git a/tests/test_prompts.txt b/tests/test_prompts.txt new file mode 100644 index 0000000..7a8a0c0 --- /dev/null +++ b/tests/test_prompts.txt @@ -0,0 +1,8 @@ +hello world +i'm going to the store to buy 3 apples and a banana! you're welcome to come along if you'd like. the time is 2:30 p.m. and it's partly cloudy outside. i'll be back soon, so don't go anywhere. +"5 2 + 3 * 4 -"; int stack[1000], top = -1; int calculate(int a, int b, char operator) { return operator == \'+\' ? a + b : operator == \'-\' ? a - b : operator == \'*\' ? a * b : a / b; } void push(int x) { stack[++top] = x; } int pop() { return stack[top--]; } int evaluatepostfix(char* expression) { for (int i = 0; expression[i]; i++) { if (isdigit(expression[i])) push(expression[i] - \'0\'); else { int a = pop(), b = pop(); push(calculate(b, a, expression[i])); } } return pop(); } int result = evaluatepostfix(input); +你好，世界！ +こんにちは、世界！ +1231 2431431 +你好我是gpt +然而，分音符号（diaeresis）和变音符号（umlaut）在一些情况下也可以被泛称为 "accent"，这是因为它们都是附加在字母上的符号，用于改变字母的原始发音。 diff --git a/tests/test_tokenizer.cpp b/tests/test_tokenizer.cpp new file mode 100644 index 0000000..d6f89bf --- /dev/null +++ b/tests/test_tokenizer.cpp @@ -0,0 +1,193 @@ +#ifdef NDEBUG +#undef NDEBUG +#endif + +#include "bert.h" +#include "ggml.h" + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#define ANSI_COLOR_RED "\x1b[31m" +#define ANSI_COLOR_RESET "\x1b[0m" +#define ANSI_COLOR_GREEN "\x1b[32m" + + +std::vector txt2list(const std::string& filename) { + std::ifstream file(filename); + std::vector all_lines; + + if (!file.is_open()) { + printf("can not open file: %s\n", filename.c_str()); + return all_lines; + } + + std::string line; + while (std::getline(file, line)) { + all_lines.push_back(line); + } + + file.close(); + return all_lines; +} + +std::vector> read_expected_tokenids(const std::string& filename) { + std::ifstream file(filename); + std::vector> all_numbers; + + if (!file.is_open()) { + printf("can not open file: %s\n", filename.c_str()); + return all_numbers; + } + + + std::string line; + while (std::getline(file, line)) { + std::vector line_numbers; + std::istringstream iss(line); + std::string number_str; + + while (std::getline(iss, number_str, ',')) { + line_numbers.push_back(std::stoi(number_str)); + } + + all_numbers.push_back(line_numbers); + } + + file.close(); + return all_numbers; +} + +void tokenizer_test(bert_ctx * ctx, const std::string& input, const bert_tokens& expected) { + int N = bert_n_max_tokens(ctx); + bert_tokens result = bert_tokenize(ctx, input, N); + int n_tokens; + + if (result != expected) { + printf("tokenizer test failed: '%.*s'\n", 16000, input.data()); + + printf("["); + for (auto& tok : result) { + printf("%d, ", tok); + } + printf("]\n"); + + for (size_t i = 0; i < result.size(); i++) { + bert_token a = expected[std::min(i, expected.size()-1)]; + bert_token b = result[i]; + const char *color_start = (a == b) ? ANSI_COLOR_GREEN : ANSI_COLOR_RED; + const char *color_end = ANSI_COLOR_RESET; + + printf("%s%d -> %s : %d -> %s%s\n", color_start, a, bert_vocab_id_to_token(ctx, a), b, bert_vocab_id_to_token(ctx, b), color_end); + } + } else { + printf("Success '%.*s...'\n", 16, input.data()); + } + assert(result == expected); + } + + +struct bert_params +{ + int32_t n_threads = 6; + const char* model = "models/all-MiniLM-L6-v2/ggml-model-q4_0.bin"; + const char* prompt = "test prompt"; + int32_t batch_size = 32; + bool use_cpu = false; +}; + +void bert_print_usage(char **argv, const bert_params ¶ms) { + fprintf(stderr, "usage: %s [options]\n", argv[0]); + fprintf(stderr, "\n"); + fprintf(stderr, "options:\n"); + fprintf(stderr, " -h, --help show this help message and exit\n"); + fprintf(stderr, " -m FNAME, --model FNAME\n"); + fprintf(stderr, " model path (default: %s)\n", params.model); + fprintf(stderr, " batch size to use when executing model\n"); + fprintf(stderr, " -c, --cpu use CPU backend (default: use CUDA if available)\n"); + fprintf(stderr, "\n"); +} + +bool bert_params_parse(int argc, char **argv, bert_params ¶ms) { + for (int i = 1; i < argc; i++) + { + std::string arg = argv[i]; + + if (arg == "-m" || arg == "--model") { + params.model = argv[++i]; + } else if (arg == "-c" || arg == "--cpu") { + params.use_cpu = true; + } else if (arg == "-h" || arg == "--help") { + bert_print_usage(argv, params); + exit(0); + } else { + fprintf(stderr, "error: unknown argument: %s\n", arg.c_str()); + bert_print_usage(argv, params); + exit(0); + } + } + + return true; +} + +int main(int argc, char ** argv) { + + bert_params params; + params.model = "models/all-MiniLM-L6-v2/ggml-model-q4_0.bin"; + + if (bert_params_parse(argc, argv, params) == false) { + return 1; + } + + + bert_ctx * bctx; + + // load the model + { + if ((bctx = bert_load_from_file(params.model, params.use_cpu)) == nullptr) { + fprintf(stderr, "%s: failed to load model from '%s'\n", __func__, params.model); + return 1; + } + } + std::string dir = params.model; + std::size_t i = dir.rfind("/models/"); + if (i != std::string::npos) { + dir.resize(i); + } else { + dir = "."; + } + + auto expected = read_expected_tokenids(dir + "/tests/hf_tokenized_ids.txt"); + auto prompts = txt2list(dir + "/tests/test_prompts.txt"); + + if (expected.size() == 0 || prompts.size() == 0) { + printf("failed to read test data\n"); + return 1; + } + + if (expected.size() != prompts.size()) { + printf("test data size mismatch\n"); + return 1; + } + + // tokenizer tests: + for (size_t i = 0; i < prompts.size(); i++) { + tokenizer_test(bctx, prompts[i], expected[i]); + } + + // tokenizer_test(bctx, "1231 2431431", {101, 13138, 2487, 22884, 16932, 21486, 102}); + // tokenizer_test(bctx, "Québec", {101, 5447, 102}); + // tokenizer_test(bctx, "syömme \t täällä tänään", {101, 25353, 5358, 4168, 11937, 25425, 9092, 14634, 102}); + // tokenizer_test(bctx, "I'm going to the store to buy 3 apples and a banana! You're welcome to come along if you'd like. The time is 2:30 p.m. and it's partly cloudy outside. I'll be back soon, so don't go anywhere.", {101, 1045, 1005, 1049, 2183, 2000, 1996, 3573, 2000, 4965, 1017, 18108, 1998, 1037, 15212, 999, 2017, 1005, 2128, 6160, 2000, 2272, 2247, 2065, 2017, 1005, 1040, 2066, 1012, 1996, 2051, 2003, 1016, 1024, 2382, 1052, 1012, 1049, 1012, 1998, 2009, 1005, 1055, 6576, 24706, 2648, 1012, 1045, 1005, 2222, 2022, 2067, 2574, 1010, 2061, 2123, 1005, 1056, 2175, 5973, 1012, 102}); + // tokenizer_test(bctx, "\"5 2 + 3 * 4 -\"; int stack[1000], top = -1; int calculate(int a, int b, char operator) { return operator == '+' ? a + b : operator == '-' ? a - b : operator == '*' ? a * b : a / b; } void push(int x) { stack[++top] = x; } int pop() { return stack[top--]; } int evaluatePostfix(char* expression) { for (int i = 0; expression[i]; i++) { if (isdigit(expression[i])) push(expression[i] - '0'); else { int a = pop(), b = pop(); push(calculate(b, a, expression[i])); } } return pop(); } int result = evaluatePostfix(input);", {101, 1000, 1019, 1016, 1009, 1017, 1008, 1018, 1011, 1000, 1025, 20014, 9991, 1031, 6694, 1033, 1010, 2327, 1027, 1011, 1015, 1025, 20014, 18422, 1006, 20014, 1037, 1010, 20014, 1038, 1010, 25869, 6872, 1007, 1063, 2709, 6872, 1027, 1027, 1005, 1009, 1005, 1029, 1037, 1009, 1038, 1024, 6872, 1027, 1027, 1005, 1011, 1005, 1029, 1037, 1011, 1038, 1024, 6872, 1027, 1027, 1005, 1008, 1005, 1029, 1037, 1008, 1038, 1024, 1037, 1013, 1038, 1025, 1065, 11675, 5245, 1006, 20014, 1060, 1007, 1063, 9991, 1031, 1009, 1009, 2327, 1033, 1027, 1060, 1025, 1065, 20014, 3769, 1006, 1007, 1063, 2709, 9991, 1031, 2327, 1011, 1011, 1033, 1025, 1065, 20014, 16157, 19894, 8873, 2595, 1006, 25869, 1008, 3670, 1007, 1063, 2005, 1006, 20014, 1045, 1027, 1014, 1025, 3670, 1031, 1045, 1033, 1025, 1045, 1009, 1009, 1007, 1063, 2065, 1006, 2003, 4305, 23806, 1006, 3670, 1031, 1045, 1033, 1007, 1007, 5245, 1006, 3670, 1031, 1045, 1033, 1011, 1005, 1014, 1005, 1007, 1025, 2842, 1063, 20014, 1037, 1027, 3769, 1006, 1007, 1010, 1038, 1027, 3769, 1006, 1007, 1025, 5245, 1006, 18422, 1006, 1038, 1010, 1037, 1010, 3670, 1031, 1045, 1033, 1007, 1007, 1025, 1065, 1065, 2709, 3769, 1006, 1007, 1025, 1065, 20014, 2765, 1027, 16157, 19894, 8873, 2595, 1006, 7953, 1007, 1025, 102}); + + // tokenizer_test(bctx, "Hello world!", {101, 7592, 2088, 999, 102}); + // tokenizer_test(bctx, "你好，世界！", {101, 100, 100, 1989, 1745, 100, 1986, 102}); + // tokenizer_test(bctx, "こんにちは、世界！", {101, 1655, 30217, 30194, 30188, 30198, 1635, 1745, 100, 1986, 102}); +}