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https://github.com/ggml-org/whisper.cpp.git
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3
.github/workflows/build.yml
vendored
3
.github/workflows/build.yml
vendored
@ -241,7 +241,8 @@ jobs:
|
||||
- name: Dependencies
|
||||
run: |
|
||||
brew update
|
||||
brew install sdl2 cmake
|
||||
cmake --version
|
||||
brew install sdl2
|
||||
|
||||
- name: Build
|
||||
run: |
|
||||
|
||||
@ -10,129 +10,6 @@
|
||||
#include <regex>
|
||||
#include <sstream>
|
||||
|
||||
// Function to check if the next argument exists
|
||||
static std::string get_next_arg(int& i, int argc, char** argv, const std::string& flag, gpt_params& params) {
|
||||
if (i + 1 < argc && argv[i + 1][0] != '-') {
|
||||
return argv[++i];
|
||||
} else {
|
||||
fprintf(stderr, "error: %s requires one argument.\n", flag.c_str());
|
||||
gpt_print_usage(argc, argv, params);
|
||||
exit(0);
|
||||
}
|
||||
}
|
||||
|
||||
bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
|
||||
for (int i = 1; i < argc; i++) {
|
||||
std::string arg = argv[i];
|
||||
|
||||
if (arg == "-s" || arg == "--seed") {
|
||||
params.seed = std::stoi(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "-t" || arg == "--threads") {
|
||||
params.n_threads = std::stoi(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "-p" || arg == "--prompt") {
|
||||
params.prompt = get_next_arg(i, argc, argv, arg, params);
|
||||
} else if (arg == "-n" || arg == "--n_predict") {
|
||||
params.n_predict = std::stoi(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "-np" || arg == "--n_parallel") {
|
||||
params.n_parallel = std::stoi(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "--top_k") {
|
||||
params.top_k = std::stoi(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "--top_p") {
|
||||
params.top_p = std::stof(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "--temp") {
|
||||
params.temp = std::stof(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "--repeat-last-n") {
|
||||
params.repeat_last_n = std::stoi(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "--repeat-penalty") {
|
||||
params.repeat_penalty = std::stof(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "-b" || arg == "--batch_size") {
|
||||
params.n_batch= std::stoi(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "-c" || arg == "--context") {
|
||||
params.n_ctx= std::stoi(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "-ngl" || arg == "--gpu-layers" || arg == "--n-gpu-layers") {
|
||||
params.n_gpu_layers = std::stoi(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "--ignore-eos") {
|
||||
params.ignore_eos = true;
|
||||
} else if (arg == "-m" || arg == "--model") {
|
||||
params.model = get_next_arg(i, argc, argv, arg, params);
|
||||
} else if (arg == "-i" || arg == "--interactive") {
|
||||
params.interactive = true;
|
||||
} else if (arg == "-ip" || arg == "--interactive-port") {
|
||||
params.interactive = true;
|
||||
params.interactive_port = std::stoi(get_next_arg(i, argc, argv, arg, params));
|
||||
} else if (arg == "-h" || arg == "--help") {
|
||||
gpt_print_usage(argc, argv, params);
|
||||
exit(0);
|
||||
} else if (arg == "-f" || arg == "--file") {
|
||||
get_next_arg(i, argc, argv, arg, params);
|
||||
std::ifstream file(argv[i]);
|
||||
if (!file) {
|
||||
fprintf(stderr, "error: failed to open file '%s'\n", argv[i]);
|
||||
break;
|
||||
}
|
||||
std::copy(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), back_inserter(params.prompt));
|
||||
if (params.prompt.back() == '\n') {
|
||||
params.prompt.pop_back();
|
||||
}
|
||||
} else if (arg == "-tt" || arg == "--token_test") {
|
||||
params.token_test = get_next_arg(i, argc, argv, arg, params);
|
||||
}
|
||||
else {
|
||||
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
|
||||
gpt_print_usage(argc, argv, params);
|
||||
exit(0);
|
||||
}
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
|
||||
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, " -s SEED, --seed SEED RNG seed (default: -1)\n");
|
||||
fprintf(stderr, " -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
|
||||
fprintf(stderr, " -p PROMPT, --prompt PROMPT\n");
|
||||
fprintf(stderr, " prompt to start generation with (default: random)\n");
|
||||
fprintf(stderr, " -f FNAME, --file FNAME\n");
|
||||
fprintf(stderr, " load prompt from a file\n");
|
||||
fprintf(stderr, " -tt TOKEN_TEST, --token_test TOKEN_TEST\n");
|
||||
fprintf(stderr, " test tokenization\n");
|
||||
fprintf(stderr, " -n N, --n_predict N number of tokens to predict (default: %d)\n", params.n_predict);
|
||||
fprintf(stderr, " --top_k N top-k sampling (default: %d)\n", params.top_k);
|
||||
fprintf(stderr, " --top_p N top-p sampling (default: %.1f)\n", params.top_p);
|
||||
fprintf(stderr, " --temp N temperature (default: %.1f)\n", params.temp);
|
||||
fprintf(stderr, " --repeat-last-n N last n tokens to consider for penalize (default: %d, 0 = disabled)\n", params.repeat_last_n);
|
||||
fprintf(stderr, " --repeat-penalty N penalize repeat sequence of tokens (default: %.2f, 1.0 = disabled)\n", (double)params.repeat_penalty);
|
||||
fprintf(stderr, " -b N, --batch_size N batch size for prompt processing (default: %d)\n", params.n_batch);
|
||||
fprintf(stderr, " -c N, --context N context / KV cache size (default: %d)\n", params.n_ctx);
|
||||
fprintf(stderr, " --ignore-eos ignore EOS token during generation\n");
|
||||
fprintf(stderr, " -ngl N, --gpu-layers N number of layers to offload to GPU on supported models (default: %d)\n", params.n_gpu_layers);
|
||||
fprintf(stderr, " -m FNAME, --model FNAME\n");
|
||||
fprintf(stderr, " model path (default: %s)\n", params.model.c_str());
|
||||
fprintf(stderr, "\n");
|
||||
}
|
||||
|
||||
std::string gpt_random_prompt(std::mt19937 & rng) {
|
||||
const int r = rng() % 10;
|
||||
switch (r) {
|
||||
case 0: return "So";
|
||||
case 1: return "Once upon a time";
|
||||
case 2: return "When";
|
||||
case 3: return "The";
|
||||
case 4: return "After";
|
||||
case 5: return "If";
|
||||
case 6: return "import";
|
||||
case 7: return "He";
|
||||
case 8: return "She";
|
||||
case 9: return "They";
|
||||
}
|
||||
|
||||
return "The";
|
||||
}
|
||||
|
||||
std::string trim(const std::string & s) {
|
||||
std::regex e("^\\s+|\\s+$");
|
||||
return std::regex_replace(s, e, "");
|
||||
@ -152,252 +29,6 @@ void gpt_vocab::add_special_token(const std::string & token) {
|
||||
special_tokens.push_back(token);
|
||||
}
|
||||
|
||||
std::map<std::string, int32_t> json_parse(const std::string & fname) {
|
||||
std::map<std::string, int32_t> result;
|
||||
|
||||
// read file into string
|
||||
std::string json;
|
||||
{
|
||||
std::ifstream ifs(fname);
|
||||
if (!ifs) {
|
||||
fprintf(stderr, "Failed to open %s\n", fname.c_str());
|
||||
exit(1);
|
||||
}
|
||||
|
||||
json = std::string((std::istreambuf_iterator<char>(ifs)),
|
||||
(std::istreambuf_iterator<char>()));
|
||||
}
|
||||
|
||||
if (json[0] != '{') {
|
||||
return result;
|
||||
}
|
||||
|
||||
// parse json
|
||||
{
|
||||
bool has_key = false;
|
||||
bool in_token = false;
|
||||
|
||||
std::string str_key = "";
|
||||
std::string str_val = "";
|
||||
|
||||
int n = json.size();
|
||||
for (int i = 1; i < n; ++i) {
|
||||
if (!in_token) {
|
||||
if (json[i] == ' ') continue;
|
||||
if (json[i] == '"') {
|
||||
in_token = true;
|
||||
continue;
|
||||
}
|
||||
} else {
|
||||
if (json[i] == '\\' && i+1 < n) {
|
||||
if (has_key == false) {
|
||||
str_key += json[i];
|
||||
} else {
|
||||
str_val += json[i];
|
||||
}
|
||||
++i;
|
||||
} else if (json[i] == '"') {
|
||||
if (has_key == false) {
|
||||
has_key = true;
|
||||
++i;
|
||||
while (json[i] == ' ') ++i;
|
||||
++i; // :
|
||||
while (json[i] == ' ') ++i;
|
||||
if (json[i] != '\"') {
|
||||
while (json[i] != ',' && json[i] != '}') {
|
||||
str_val += json[i++];
|
||||
}
|
||||
has_key = false;
|
||||
} else {
|
||||
in_token = true;
|
||||
continue;
|
||||
}
|
||||
} else {
|
||||
has_key = false;
|
||||
}
|
||||
|
||||
str_key = ::replace(str_key, "\\u0120", " " ); // \u0120 -> space
|
||||
str_key = ::replace(str_key, "\\u010a", "\n"); // \u010a -> new line
|
||||
str_key = ::replace(str_key, "\\\"", "\""); // \\\" -> "
|
||||
|
||||
try {
|
||||
result[str_key] = std::stoi(str_val);
|
||||
} catch (...) {
|
||||
//fprintf(stderr, "%s: ignoring key '%s' with value '%s'\n", fname.c_str(), str_key.c_str(), str_val.c_str());
|
||||
|
||||
}
|
||||
str_key = "";
|
||||
str_val = "";
|
||||
in_token = false;
|
||||
continue;
|
||||
}
|
||||
if (has_key == false) {
|
||||
str_key += json[i];
|
||||
} else {
|
||||
str_val += json[i];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
void gpt_split_words(std::string str, std::vector<std::string>& words) {
|
||||
const std::string pattern = R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)";
|
||||
const std::regex re(pattern);
|
||||
std::smatch m;
|
||||
|
||||
while (std::regex_search(str, m, re)) {
|
||||
for (auto x : m) {
|
||||
words.push_back(x);
|
||||
}
|
||||
str = m.suffix();
|
||||
}
|
||||
}
|
||||
|
||||
std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::string & text) {
|
||||
std::vector<std::string> words;
|
||||
|
||||
// first split the text into words
|
||||
{
|
||||
std::string str = text;
|
||||
|
||||
// Generate the subpattern from the special_tokens vector if it's not empty
|
||||
if (!vocab.special_tokens.empty()) {
|
||||
const std::regex escape(R"([\[\\\^\$\.\|\?\*\+\(\)\{\}])");
|
||||
std::string special_tokens_subpattern;
|
||||
for (const auto & token : vocab.special_tokens) {
|
||||
if (!special_tokens_subpattern.empty()) {
|
||||
special_tokens_subpattern += "|";
|
||||
}
|
||||
special_tokens_subpattern += std::regex_replace(token, escape, R"(\$&)");
|
||||
}
|
||||
|
||||
std::regex re(special_tokens_subpattern);
|
||||
std::smatch m;
|
||||
// Split the text by special tokens.
|
||||
while (std::regex_search(str, m, re)) {
|
||||
// Split the substrings in-between special tokens into words.
|
||||
gpt_split_words(m.prefix(), words);
|
||||
// Add matched special tokens as words.
|
||||
for (auto x : m) {
|
||||
words.push_back(x);
|
||||
}
|
||||
str = m.suffix();
|
||||
}
|
||||
// Remaining text without special tokens will be handled below.
|
||||
}
|
||||
|
||||
gpt_split_words(str, words);
|
||||
}
|
||||
|
||||
// find the longest token that forms each word in words:
|
||||
std::vector<gpt_vocab::id> tokens;
|
||||
for (const auto & word : words) {
|
||||
for (int i = 0; i < (int) word.size(); ){
|
||||
for (int j = word.size() - 1; j >= i; j--){
|
||||
auto cand = word.substr(i, j-i+1);
|
||||
auto it = vocab.token_to_id.find(cand);
|
||||
if (it != vocab.token_to_id.end()){ // word.substr(i, j-i+1) in vocab
|
||||
tokens.push_back(it->second);
|
||||
i = j + 1;
|
||||
break;
|
||||
}
|
||||
else if (j == i){ // word.substr(i, 1) has no matching
|
||||
fprintf(stderr, "%s: unknown token '%s'\n", __func__, word.substr(i, 1).data());
|
||||
i++;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return tokens;
|
||||
}
|
||||
|
||||
static std::vector<gpt_vocab::id> parse_tokens_from_string(const std::string& input, char delimiter) {
|
||||
std::vector<gpt_vocab::id> output;
|
||||
std::stringstream ss(input);
|
||||
std::string token;
|
||||
|
||||
while (std::getline(ss, token, delimiter)) {
|
||||
output.push_back(std::stoi(token));
|
||||
}
|
||||
|
||||
return output;
|
||||
}
|
||||
|
||||
static std::map<std::string, std::vector<gpt_vocab::id>> extract_tests_from_file(const std::string & fpath_test){
|
||||
if (fpath_test.empty()){
|
||||
fprintf(stderr, "%s : No test file found.\n", __func__);
|
||||
return std::map<std::string, std::vector<gpt_vocab::id>>();
|
||||
}
|
||||
|
||||
std::map<std::string, std::vector<gpt_vocab::id>> tests;
|
||||
|
||||
auto fin = std::ifstream(fpath_test, std::ios_base::in);
|
||||
const char * delimeter = " => ";
|
||||
const char del_tok = ',';
|
||||
std::string line;
|
||||
while (std::getline(fin, line)) {
|
||||
size_t delimiterPos = line.find(delimeter);
|
||||
if (delimiterPos != std::string::npos) {
|
||||
std::string text = line.substr(0, delimiterPos);
|
||||
std::string s_tokens = line.substr(delimiterPos + std::strlen(delimeter));
|
||||
tests[text] = parse_tokens_from_string(s_tokens, del_tok);
|
||||
}
|
||||
}
|
||||
return tests;
|
||||
}
|
||||
|
||||
void test_gpt_tokenizer(gpt_vocab & vocab, const std::string & fpath_test){
|
||||
std::map<std::string, std::vector<gpt_vocab::id>> tests = extract_tests_from_file(fpath_test);
|
||||
|
||||
size_t n_fails = 0;
|
||||
|
||||
for (const auto & test : tests) {
|
||||
std::vector<gpt_vocab::id> tokens = gpt_tokenize(vocab, test.first);
|
||||
|
||||
if (tokens != test.second){
|
||||
n_fails++;
|
||||
|
||||
// print out failure cases
|
||||
fprintf(stderr, "%s : failed test: '%s'\n", __func__, test.first.c_str());
|
||||
fprintf(stderr, "%s : tokens in hf: ", __func__);
|
||||
for (const auto & t : test.second) {
|
||||
fprintf(stderr, "%s(%d), ", vocab.id_to_token[t].c_str(), t);
|
||||
}
|
||||
fprintf(stderr, "\n");
|
||||
fprintf(stderr, "%s : tokens in ggml: ", __func__);
|
||||
for (const auto & t : tokens) {
|
||||
fprintf(stderr, "%s(%d), ", vocab.id_to_token[t].c_str(), t);
|
||||
}
|
||||
fprintf(stderr, "\n");
|
||||
}
|
||||
}
|
||||
|
||||
fprintf(stderr, "%s : %zu tests failed out of %zu tests.\n", __func__, n_fails, tests.size());
|
||||
}
|
||||
|
||||
bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab) {
|
||||
printf("%s: loading vocab from '%s'\n", __func__, fname.c_str());
|
||||
|
||||
vocab.token_to_id = ::json_parse(fname);
|
||||
|
||||
for (const auto & kv : vocab.token_to_id) {
|
||||
vocab.id_to_token[kv.second] = kv.first;
|
||||
}
|
||||
|
||||
printf("%s: vocab size = %d\n", __func__, (int) vocab.token_to_id.size());
|
||||
|
||||
// print the vocabulary
|
||||
//for (auto kv : vocab.token_to_id) {
|
||||
// printf("'%s' -> %d\n", kv.first.data(), kv.second);
|
||||
//}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
gpt_vocab::id gpt_sample_top_k_top_p(
|
||||
const gpt_vocab & vocab,
|
||||
const float * logits,
|
||||
|
||||
@ -11,42 +11,6 @@
|
||||
#include <fstream>
|
||||
#include <sstream>
|
||||
|
||||
//
|
||||
// GPT CLI argument parsing
|
||||
//
|
||||
|
||||
struct gpt_params {
|
||||
int32_t seed = -1; // RNG seed
|
||||
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
|
||||
int32_t n_predict = 200; // new tokens to predict
|
||||
int32_t n_parallel = 1; // number of parallel streams
|
||||
int32_t n_batch = 32; // batch size for prompt processing
|
||||
int32_t n_ctx = 2048; // context size (this is the KV cache max size)
|
||||
int32_t n_gpu_layers = 0; // number of layers to offlload to the GPU
|
||||
|
||||
bool ignore_eos = false; // ignore EOS token when generating text
|
||||
|
||||
// sampling parameters
|
||||
int32_t top_k = 40;
|
||||
float top_p = 0.9f;
|
||||
float temp = 0.9f;
|
||||
int32_t repeat_last_n = 64;
|
||||
float repeat_penalty = 1.00f;
|
||||
|
||||
std::string model = "models/gpt-2-117M/ggml-model.bin"; // model path
|
||||
std::string prompt = "";
|
||||
std::string token_test = "";
|
||||
|
||||
bool interactive = false;
|
||||
int32_t interactive_port = -1;
|
||||
};
|
||||
|
||||
bool gpt_params_parse(int argc, char ** argv, gpt_params & params);
|
||||
|
||||
void gpt_print_usage(int argc, char ** argv, const gpt_params & params);
|
||||
|
||||
std::string gpt_random_prompt(std::mt19937 & rng);
|
||||
|
||||
//
|
||||
// Vocab utils
|
||||
//
|
||||
@ -69,39 +33,6 @@ struct gpt_vocab {
|
||||
void add_special_token(const std::string & token);
|
||||
};
|
||||
|
||||
// poor-man's JSON parsing
|
||||
std::map<std::string, int32_t> json_parse(const std::string & fname);
|
||||
|
||||
std::string convert_to_utf8(const std::wstring & input);
|
||||
|
||||
std::wstring convert_to_wstring(const std::string & input);
|
||||
|
||||
void gpt_split_words(std::string str, std::vector<std::string>& words);
|
||||
|
||||
// split text into tokens
|
||||
//
|
||||
// ref: https://github.com/openai/gpt-2/blob/a74da5d99abaaba920de8131d64da2862a8f213b/src/encoder.py#L53
|
||||
//
|
||||
// Regex (Python):
|
||||
// r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""
|
||||
//
|
||||
// Regex (C++):
|
||||
// R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)"
|
||||
//
|
||||
std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::string & text);
|
||||
|
||||
// test outputs of gpt_tokenize
|
||||
//
|
||||
// - compare with tokens generated by the huggingface tokenizer
|
||||
// - test cases are chosen based on the model's main language (under 'prompt' directory)
|
||||
// - if all sentences are tokenized identically, print 'All tests passed.'
|
||||
// - otherwise, print sentence, huggingface tokens, ggml tokens
|
||||
//
|
||||
void test_gpt_tokenizer(gpt_vocab & vocab, const std::string & fpath_test);
|
||||
|
||||
// load the tokens from encoder.json
|
||||
bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab);
|
||||
|
||||
// sample next token given probabilities for each embedding
|
||||
//
|
||||
// - consider only the top K tokens
|
||||
|
||||
@ -119,12 +119,12 @@ fi
|
||||
|
||||
if [ -x "$(command -v wget2)" ]; then
|
||||
wget2 --no-config --progress bar -O ggml-"$model".bin $src/$pfx-"$model".bin
|
||||
elif [ -x "$(command -v wget)" ]; then
|
||||
wget --no-config --quiet --show-progress -O ggml-"$model".bin $src/$pfx-"$model".bin
|
||||
elif [ -x "$(command -v curl)" ]; then
|
||||
curl -L --output ggml-"$model".bin $src/$pfx-"$model".bin
|
||||
elif [ -x "$(command -v wget)" ]; then
|
||||
wget --no-config --quiet --show-progress -O ggml-"$model".bin $src/$pfx-"$model".bin
|
||||
else
|
||||
printf "Either wget or curl is required to download models.\n"
|
||||
printf "Either wget2, curl, or wget is required to download models.\n"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
|
||||
@ -64,8 +64,6 @@ while read c; do
|
||||
src/ggml* \
|
||||
include/ggml*.h \
|
||||
include/gguf*.h \
|
||||
examples/common.h \
|
||||
examples/common.cpp \
|
||||
examples/common-ggml.h \
|
||||
examples/common-ggml.cpp \
|
||||
LICENSE \
|
||||
|
||||
@ -11,8 +11,6 @@ cp -rpv ../ggml/src/ggml* ./ggml/src/
|
||||
cp -rpv ../ggml/include/ggml*.h ./ggml/include/
|
||||
cp -rpv ../ggml/include/gguf*.h ./ggml/include/
|
||||
|
||||
cp -rpv ../ggml/examples/common.h ./examples/common.h
|
||||
cp -rpv ../ggml/examples/common.cpp ./examples/common.cpp
|
||||
cp -rpv ../ggml/examples/common-ggml.h ./examples/common-ggml.h
|
||||
cp -rpv ../ggml/examples/common-ggml.cpp ./examples/common-ggml.cpp
|
||||
|
||||
|
||||
@ -93,6 +93,9 @@ set(VAD_TEST test-vad)
|
||||
add_executable(${VAD_TEST} ${VAD_TEST}.cpp)
|
||||
target_include_directories(${VAD_TEST} PRIVATE ../include ../ggml/include ../examples)
|
||||
target_link_libraries(${VAD_TEST} PRIVATE common)
|
||||
target_compile_definitions(${VAD_TEST} PRIVATE
|
||||
VAD_MODEL_PATH="${PROJECT_SOURCE_DIR}/models/for-tests-silero-v5.1.2-ggml.bin"
|
||||
SAMPLE_PATH="${PROJECT_SOURCE_DIR}/samples/jfk.wav")
|
||||
add_test(NAME ${VAD_TEST} COMMAND ${VAD_TEST})
|
||||
set_tests_properties(${VAD_TEST} PROPERTIES LABELS "unit")
|
||||
|
||||
@ -101,5 +104,9 @@ set(VAD_TEST test-vad-full)
|
||||
add_executable(${VAD_TEST} ${VAD_TEST}.cpp)
|
||||
target_include_directories(${VAD_TEST} PRIVATE ../include ../ggml/include ../examples)
|
||||
target_link_libraries(${VAD_TEST} PRIVATE common)
|
||||
target_compile_definitions(${VAD_TEST} PRIVATE
|
||||
WHISPER_MODEL_PATH="${PROJECT_SOURCE_DIR}/models/ggml-base.en.bin"
|
||||
VAD_MODEL_PATH="${PROJECT_SOURCE_DIR}/models/for-tests-silero-v5.1.2-ggml.bin"
|
||||
SAMPLE_PATH="${PROJECT_SOURCE_DIR}/samples/jfk.wav")
|
||||
add_test(NAME ${VAD_TEST} COMMAND ${VAD_TEST})
|
||||
set_tests_properties(${VAD_TARGET} PROPERTIES LABELS "base;en")
|
||||
set_tests_properties(${VAD_TEST} PROPERTIES LABELS "base;en")
|
||||
|
||||
@ -13,9 +13,9 @@
|
||||
#include <cassert>
|
||||
|
||||
int main() {
|
||||
std::string whisper_model_path = "../../models/ggml-base.en.bin";
|
||||
std::string vad_model_path = "../../models/for-tests-silero-v5.1.2-ggml.bin";
|
||||
std::string sample_path = "../../samples/jfk.wav";
|
||||
std::string whisper_model_path = WHISPER_MODEL_PATH;
|
||||
std::string vad_model_path = VAD_MODEL_PATH;
|
||||
std::string sample_path = SAMPLE_PATH;
|
||||
|
||||
// Load the sample audio file
|
||||
std::vector<float> pcmf32;
|
||||
|
||||
@ -48,8 +48,8 @@ struct whisper_vad_segments * test_detect_timestamps(
|
||||
}
|
||||
|
||||
int main() {
|
||||
std::string vad_model_path = "../../models/for-tests-silero-v5.1.2-ggml.bin";
|
||||
std::string sample_path = "../../samples/jfk.wav";
|
||||
std::string vad_model_path = VAD_MODEL_PATH;
|
||||
std::string sample_path = SAMPLE_PATH;
|
||||
|
||||
// Load the sample audio file
|
||||
std::vector<float> pcmf32;
|
||||
|
||||
Loading…
Reference in New Issue
Block a user