examples : utils -> common

diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt
index 19857fda81072c01d209fe25a3126586c6f647ff..96df13967aa04bdfd36ca986b958f2abd229faf2 100644 (file)
--- a/examples/CMakeLists.txt
+++ b/examples/CMakeLists.txt
@@ -1,5 +1,8 @@
-add_library(ggml_utils STATIC utils.cpp)
-target_include_directories(ggml_utils PUBLIC ${CMAKE_CURRENT_SOURCE_DIR})
+add_library(common STATIC common.cpp)
+target_include_directories(common PUBLIC ${CMAKE_CURRENT_SOURCE_DIR})
+
+add_library(common-ggml STATIC common-ggml.cpp)
+target_include_directories(common-ggml PUBLIC ${CMAKE_CURRENT_SOURCE_DIR})
 
 add_subdirectory(gpt-2)
 add_subdirectory(gpt-j)

diff --git a/examples/common-ggml.cpp b/examples/common-ggml.cpp
new file mode 100644 (file)
index 0000000..a6e4144
--- /dev/null
+++ b/examples/common-ggml.cpp
@@ -0,0 +1 @@
+#include "common-ggml.h"

diff --git a/examples/common-ggml.h b/examples/common-ggml.h
new file mode 100644 (file)
index 0000000..3f59c93
--- /dev/null
+++ b/examples/common-ggml.h
@@ -0,0 +1,2 @@
+#pragma once
+

diff --git a/examples/common.cpp b/examples/common.cpp
new file mode 100644 (file)
index 0000000..fc45999
--- /dev/null
+++ b/examples/common.cpp
@@ -0,0 +1,481 @@
+#include "common.h"
+
+// third-party utilities
+// use your favorite implementations
+#define DR_WAV_IMPLEMENTATION
+#include "dr_wav.h"
+
+#include <cmath>
+#include <fstream>
+#include <regex>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+
+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(argv[++i]);
+        } else if (arg == "-t" || arg == "--threads") {
+            params.n_threads = std::stoi(argv[++i]);
+        } else if (arg == "-p" || arg == "--prompt") {
+            params.prompt = argv[++i];
+        } else if (arg == "-n" || arg == "--n_predict") {
+            params.n_predict = std::stoi(argv[++i]);
+        } else if (arg == "--top_k") {
+            params.top_k = std::stoi(argv[++i]);
+        } else if (arg == "--top_p") {
+            params.top_p = std::stof(argv[++i]);
+        } else if (arg == "--temp") {
+            params.temp = std::stof(argv[++i]);
+        } else if (arg == "-b" || arg == "--batch_size") {
+            params.n_batch = std::stoi(argv[++i]);
+        } else if (arg == "-m" || arg == "--model") {
+            params.model = argv[++i];
+        } else if (arg == "-h" || arg == "--help") {
+            gpt_print_usage(argc, argv, params);
+            exit(0);
+        } 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, "  -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, "  -b N, --batch_size N  batch size for prompt processing (default: %d)\n", params.n_batch);
+    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";
+        default: return "To";
+    }
+
+    return "The";
+}
+
+std::string trim(const std::string & s) {
+    std::regex e("^\\s+|\\s+$");
+    return std::regex_replace(s, e, "");
+}
+
+std::string replace(const std::string & s, const std::string & from, const std::string & to) {
+    std::string result = s;
+    size_t pos = 0;
+    while ((pos = result.find(from, pos)) != std::string::npos) {
+        result.replace(pos, from.length(), to);
+        pos += to.length();
+    }
+    return result;
+}
+
+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;
+}
+
+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;
+        std::string pat = R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)";
+
+        std::regex re(pat);
+        std::smatch m;
+
+        while (std::regex_search(str, m, re)) {
+            for (auto x : m) {
+                words.push_back(x);
+            }
+            str = m.suffix();
+        }
+    }
+
+    // find the longest tokens that form the words:
+    std::vector<gpt_vocab::id> tokens;
+    for (const auto & word : words) {
+        if (word.size() == 0) continue;
+
+        int i = 0;
+        int n = word.size();
+        while (i < n) {
+            int j = n;
+            while (j > i) {
+                auto it = vocab.token_to_id.find(word.substr(i, j-i));
+                if (it != vocab.token_to_id.end()) {
+                    tokens.push_back(it->second);
+                    i = j;
+                    break;
+                }
+                --j;
+            }
+            if (i == n) {
+                break;
+            }
+            if (j == i) {
+                auto sub = word.substr(i, 1);
+                if (vocab.token_to_id.find(sub) != vocab.token_to_id.end()) {
+                    tokens.push_back(vocab.token_to_id.at(sub));
+                } else {
+                    fprintf(stderr, "%s: unknown token '%s'\n", __func__, sub.data());
+                }
+                ++i;
+            }
+        }
+    }
+
+    return tokens;
+}
+
+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,
+        int    top_k,
+        double top_p,
+        double temp,
+        std::mt19937 & rng) {
+    int n_logits = vocab.id_to_token.size();
+
+    std::vector<std::pair<double, gpt_vocab::id>> logits_id;
+    logits_id.reserve(n_logits);
+
+    {
+        const double scale = 1.0/temp;
+        for (int i = 0; i < n_logits; ++i) {
+            logits_id.push_back(std::make_pair(logits[i]*scale, i));
+        }
+    }
+
+    // find the top K tokens
+    std::partial_sort(
+            logits_id.begin(),
+            logits_id.begin() + top_k, logits_id.end(),
+            [](const std::pair<double, gpt_vocab::id> & a, const std::pair<double, gpt_vocab::id> & b) {
+        return a.first > b.first;
+    });
+
+    logits_id.resize(top_k);
+
+    double maxl = -INFINITY;
+    for (const auto & kv : logits_id) {
+        maxl = std::max(maxl, kv.first);
+    }
+
+    // compute probs for the top K tokens
+    std::vector<double> probs;
+    probs.reserve(logits_id.size());
+
+    double sum = 0.0;
+    for (const auto & kv : logits_id) {
+        double p = exp(kv.first - maxl);
+        probs.push_back(p);
+        sum += p;
+    }
+
+    // normalize the probs
+    for (auto & p : probs) {
+        p /= sum;
+    }
+
+    if (top_p < 1.0f) {
+        double cumsum = 0.0f;
+        for (int i = 0; i < top_k; i++) {
+            cumsum += probs[i];
+            if (cumsum >= top_p) {
+                top_k = i + 1;
+                probs.resize(top_k);
+                logits_id.resize(top_k);
+                break;
+            }
+        }
+
+        cumsum = 1.0/cumsum;
+        for (int i = 0; i < (int) probs.size(); i++) {
+            probs[i] *= cumsum;
+        }
+    }
+
+    //printf("\n");
+    //for (int i = 0; i < (int) probs.size(); i++) {
+    //    printf("%d: '%s' %f\n", i, vocab.id_to_token.at(logits_id[i].second).c_str(), probs[i]);
+    //}
+    //exit(0);
+
+    std::discrete_distribution<> dist(probs.begin(), probs.end());
+    int idx = dist(rng);
+
+    return logits_id[idx].second;
+}
+
+bool read_wav(const std::string & fname, std::vector<float>& pcmf32, std::vector<std::vector<float>>& pcmf32s, bool stereo) {
+    drwav wav;
+    std::vector<uint8_t> wav_data; // used for pipe input from stdin
+
+    if (fname == "-") {
+        {
+            uint8_t buf[1024];
+            while (true)
+            {
+                const size_t n = fread(buf, 1, sizeof(buf), stdin);
+                if (n == 0) {
+                    break;
+                }
+                wav_data.insert(wav_data.end(), buf, buf + n);
+            }
+        }
+
+        if (drwav_init_memory(&wav, wav_data.data(), wav_data.size(), nullptr) == false) {
+            fprintf(stderr, "error: failed to open WAV file from stdin\n");
+            return false;
+        }
+
+        fprintf(stderr, "%s: read %zu bytes from stdin\n", __func__, wav_data.size());
+    }
+    else if (drwav_init_file(&wav, fname.c_str(), nullptr) == false) {
+        fprintf(stderr, "error: failed to open '%s' as WAV file\n", fname.c_str());
+        return false;
+    }
+
+    if (wav.channels != 1 && wav.channels != 2) {
+        fprintf(stderr, "%s: WAV file '%s' must be mono or stereo\n", __func__, fname.c_str());
+        return false;
+    }
+
+    if (stereo && wav.channels != 2) {
+        fprintf(stderr, "%s: WAV file '%s' must be stereo for diarization\n", __func__, fname.c_str());
+        return false;
+    }
+
+    if (wav.sampleRate != COMMON_SAMPLE_RATE) {
+        fprintf(stderr, "%s: WAV file '%s' must be %i kHz\n", __func__, fname.c_str(), COMMON_SAMPLE_RATE/1000);
+        return false;
+    }
+
+    if (wav.bitsPerSample != 16) {
+        fprintf(stderr, "%s: WAV file '%s' must be 16-bit\n", __func__, fname.c_str());
+        return false;
+    }
+
+    const uint64_t n = wav_data.empty() ? wav.totalPCMFrameCount : wav_data.size()/(wav.channels*wav.bitsPerSample/8);
+
+    std::vector<int16_t> pcm16;
+    pcm16.resize(n*wav.channels);
+    drwav_read_pcm_frames_s16(&wav, n, pcm16.data());
+    drwav_uninit(&wav);
+
+    // convert to mono, float
+    pcmf32.resize(n);
+    if (wav.channels == 1) {
+        for (uint64_t i = 0; i < n; i++) {
+            pcmf32[i] = float(pcm16[i])/32768.0f;
+        }
+    } else {
+        for (uint64_t i = 0; i < n; i++) {
+            pcmf32[i] = float(pcm16[2*i] + pcm16[2*i + 1])/65536.0f;
+        }
+    }
+
+    if (stereo) {
+        // convert to stereo, float
+        pcmf32s.resize(2);
+
+        pcmf32s[0].resize(n);
+        pcmf32s[1].resize(n);
+        for (uint64_t i = 0; i < n; i++) {
+            pcmf32s[0][i] = float(pcm16[2*i])/32768.0f;
+            pcmf32s[1][i] = float(pcm16[2*i + 1])/32768.0f;
+        }
+    }
+
+    return true;
+}
+
+void high_pass_filter(std::vector<float> & data, float cutoff, float sample_rate) {
+    const float rc = 1.0f / (2.0f * M_PI * cutoff);
+    const float dt = 1.0f / sample_rate;
+    const float alpha = dt / (rc + dt);
+
+    float y = data[0];
+
+    for (size_t i = 1; i < data.size(); i++) {
+        y = alpha * (y + data[i] - data[i - 1]);
+        data[i] = y;
+    }
+}
+
+bool vad_simple(std::vector<float> & pcmf32, int sample_rate, int last_ms, float vad_thold, float freq_thold, bool verbose) {
+    const int n_samples      = pcmf32.size();
+    const int n_samples_last = (sample_rate * last_ms) / 1000;
+
+    if (n_samples_last >= n_samples) {
+        // not enough samples - assume no speech
+        return false;
+    }
+
+    if (freq_thold > 0.0f) {
+        high_pass_filter(pcmf32, freq_thold, sample_rate);
+    }
+
+    float energy_all  = 0.0f;
+    float energy_last = 0.0f;
+
+    for (int i = 0; i < n_samples; i++) {
+        energy_all += fabsf(pcmf32[i]);
+
+        if (i >= n_samples - n_samples_last) {
+            energy_last += fabsf(pcmf32[i]);
+        }
+    }
+
+    energy_all  /= n_samples;
+    energy_last /= n_samples_last;
+
+    if (verbose) {
+        fprintf(stderr, "%s: energy_all: %f, energy_last: %f, vad_thold: %f, freq_thold: %f\n", __func__, energy_all, energy_last, vad_thold, freq_thold);
+    }
+
+    if (energy_last > vad_thold*energy_all) {
+        return false;
+    }
+
+    return true;
+}

diff --git a/examples/common.h b/examples/common.h
new file mode 100644 (file)
index 0000000..b08e576
--- /dev/null
+++ b/examples/common.h
@@ -0,0 +1,120 @@
+// Various helper functions and utilities
+
+#pragma once
+
+#include <string>
+#include <map>
+#include <vector>
+#include <random>
+#include <thread>
+
+#define COMMON_SAMPLE_RATE 16000
+
+//
+// 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
+
+    // sampling parameters
+    int32_t top_k = 40;
+    float   top_p = 0.9f;
+    float   temp  = 0.9f;
+
+    int32_t n_batch = 8; // batch size for prompt processing
+
+    std::string model = "models/gpt-2-117M/ggml-model.bin"; // model path
+    std::string prompt;
+};
+
+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
+//
+
+std::string trim(const std::string & s);
+
+std::string replace(
+        const std::string & s,
+        const std::string & from,
+        const std::string & to);
+
+struct gpt_vocab {
+    using id    = int32_t;
+    using token = std::string;
+
+    std::map<token, id> token_to_id;
+    std::map<id, token> id_to_token;
+};
+
+// poor-man's JSON parsing
+std::map<std::string, int32_t> json_parse(const std::string & fname);
+
+// 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);
+
+// 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
+//   - from them, consider only the top tokens with cumulative probability > P
+//
+// TODO: not sure if this implementation is correct
+// TODO: temperature is not implemented
+//
+gpt_vocab::id gpt_sample_top_k_top_p(
+        const gpt_vocab & vocab,
+        const float * logits,
+        int    top_k,
+        double top_p,
+        double temp,
+        std::mt19937 & rng);
+
+//
+// Audio utils
+//
+
+// Read WAV audio file and store the PCM data into pcmf32
+// The sample rate of the audio must be equal to COMMON_SAMPLE_RATE
+// If stereo flag is set and the audio has 2 channels, the pcmf32s will contain 2 channel PCM
+bool read_wav(
+        const std::string & fname,
+        std::vector<float> & pcmf32,
+        std::vector<std::vector<float>> & pcmf32s,
+        bool stereo);
+
+// Apply a high-pass frequency filter to PCM audio
+// Suppresses frequencies below cutoff Hz
+void high_pass_filter(
+        std::vector<float> & data,
+        float cutoff,
+        float sample_rate);
+
+// Basic voice activity detection (VAD) using audio energy adaptive threshold
+bool vad_simple(
+        std::vector<float> & pcmf32,
+        int   sample_rate,
+        int   last_ms,
+        float vad_thold,
+        float freq_thold,
+        bool  verbose);
+

diff --git a/examples/gpt-2/CMakeLists.txt b/examples/gpt-2/CMakeLists.txt
index 3b7ab5efe771f42a5f9b0c3fa9b2df42de48e35a..2624ae60a71e6144c3c8945a5cc786a03b2e49e0 100644 (file)
--- a/examples/gpt-2/CMakeLists.txt
+++ b/examples/gpt-2/CMakeLists.txt
@@ -3,11 +3,11 @@
 
 set(TEST_TARGET gpt-2)
 add_executable(${TEST_TARGET} main.cpp)
-target_link_libraries(${TEST_TARGET} PRIVATE ggml ggml_utils)
+target_link_libraries(${TEST_TARGET} PRIVATE ggml common)
 
 #
 # gpt-2-quantize
 
 set(TEST_TARGET gpt-2-quantize)
 add_executable(${TEST_TARGET} quantize.cpp)
-target_link_libraries(${TEST_TARGET} PRIVATE ggml ggml_utils)
+target_link_libraries(${TEST_TARGET} PRIVATE ggml common)

diff --git a/examples/gpt-2/main.cpp b/examples/gpt-2/main.cpp
index c52cae1bc0be8e65cdcfab47ed54e36d340f9fd3..60975383a7d645f799fa2abec83c394510ae6899 100644 (file)
--- a/examples/gpt-2/main.cpp
+++ b/examples/gpt-2/main.cpp
@@ -1,6 +1,6 @@
 #include "ggml/ggml.h"
 
-#include "utils.h"
+#include "common.h"
 
 #include <cassert>
 #include <cmath>

diff --git a/examples/gpt-2/quantize.cpp b/examples/gpt-2/quantize.cpp
index fd9a22d5017679b249f2606d739a3a5010914870..28867d7295f42c32db7ef670675c8e9bb9c5e103 100644 (file)
--- a/examples/gpt-2/quantize.cpp
+++ b/examples/gpt-2/quantize.cpp
@@ -1,6 +1,6 @@
 #include "ggml/ggml.h"
 
-#include "utils.h"
+#include "common.h"
 
 #include <cassert>
 #include <cmath>

diff --git a/examples/gpt-j/CMakeLists.txt b/examples/gpt-j/CMakeLists.txt
index 390746d50e540af9fe5d546296a4519c9f8f3782..195e813c2d47c763aedd3b31bafa500896254208 100644 (file)
--- a/examples/gpt-j/CMakeLists.txt
+++ b/examples/gpt-j/CMakeLists.txt
@@ -3,11 +3,11 @@
 
 set(TEST_TARGET gpt-j)
 add_executable(${TEST_TARGET} main.cpp)
-target_link_libraries(${TEST_TARGET} PRIVATE ggml ggml_utils)
+target_link_libraries(${TEST_TARGET} PRIVATE ggml common)
 
 #
 # gpt-j-quantize
 
 set(TEST_TARGET gpt-j-quantize)
 add_executable(${TEST_TARGET} quantize.cpp)
-target_link_libraries(${TEST_TARGET} PRIVATE ggml ggml_utils)
+target_link_libraries(${TEST_TARGET} PRIVATE ggml common)

diff --git a/examples/gpt-j/main.cpp b/examples/gpt-j/main.cpp
index fbd7c3144138ac60ee14940bfc150bc9888eb8d0..57e0caf5459e206177fe3609ae9bf1bed5590d0f 100644 (file)
--- a/examples/gpt-j/main.cpp
+++ b/examples/gpt-j/main.cpp
@@ -1,6 +1,6 @@
 #include "ggml/ggml.h"
 
-#include "utils.h"
+#include "common.h"
 
 #include <cassert>
 #include <cmath>

diff --git a/examples/gpt-j/quantize.cpp b/examples/gpt-j/quantize.cpp
index 2fff95bd4de697bb3399c83e711a038a0fa15c0d..e706f3a95ba01b6b1452116f26e74456b3e91aed 100644 (file)
--- a/examples/gpt-j/quantize.cpp
+++ b/examples/gpt-j/quantize.cpp
@@ -1,6 +1,6 @@
 #include "ggml/ggml.h"
 
-#include "utils.h"
+#include "common.h"
 
 #include <cassert>
 #include <cmath>

diff --git a/examples/mnist/CMakeLists.txt b/examples/mnist/CMakeLists.txt
index 8df55a36d71220d6a1475123090282190bc4d18f..91b802ae5e0ea77093fd6d182d89eb7e258699d0 100644 (file)
--- a/examples/mnist/CMakeLists.txt
+++ b/examples/mnist/CMakeLists.txt
@@ -3,5 +3,5 @@
 
 set(TEST_TARGET mnist)
 add_executable(${TEST_TARGET} main.cpp)
-target_link_libraries(${TEST_TARGET} PRIVATE ggml ggml_utils)
+target_link_libraries(${TEST_TARGET} PRIVATE ggml common)
 

diff --git a/examples/mnist/main.cpp b/examples/mnist/main.cpp
index 3206f2d0e55e6df9fba060e3f09d7e9b178bcb8c..e2ae032940ffe40e00fb34186e09f35e04e041f1 100644 (file)
--- a/examples/mnist/main.cpp
+++ b/examples/mnist/main.cpp
@@ -1,6 +1,6 @@
 #include "ggml/ggml.h"
 
-#include "utils.h"
+#include "common.h"
 
 #include <cassert>
 #include <cmath>

diff --git a/examples/stablelm/CMakeLists.txt b/examples/stablelm/CMakeLists.txt
index b62b836d24d8b8ef99c2172cd498aa7b621b0b40..59e97a9e35b19edc38d1f9581fecfff22e655dbe 100644 (file)
--- a/examples/stablelm/CMakeLists.txt
+++ b/examples/stablelm/CMakeLists.txt
@@ -3,11 +3,11 @@
 
 set(TEST_TARGET stablelm)
 add_executable(${TEST_TARGET} main.cpp)
-target_link_libraries(${TEST_TARGET} PRIVATE ggml ggml_utils)
+target_link_libraries(${TEST_TARGET} PRIVATE ggml common)
 
 #
 # stablelm-quantize
 
 set(TEST_TARGET stablelm-quantize)
 add_executable(${TEST_TARGET} quantize.cpp)
-target_link_libraries(${TEST_TARGET} PRIVATE ggml ggml_utils)
+target_link_libraries(${TEST_TARGET} PRIVATE ggml common)

diff --git a/examples/stablelm/main.cpp b/examples/stablelm/main.cpp
index f415bffb1888a340e7323c9dfe5bb8e671febc19..879ba115589e623f0414279fab703bd558a6dd16 100644 (file)
--- a/examples/stablelm/main.cpp
+++ b/examples/stablelm/main.cpp
@@ -1,6 +1,6 @@
 #include "ggml/ggml.h"
 
-#include "utils.h"
+#include "common.h"
 
 #include <cassert>
 #include <cmath>

diff --git a/examples/stablelm/quantize.cpp b/examples/stablelm/quantize.cpp
index 25d96168df7272099ecfc90184cf509b56112f83..3c8ca5e7ad9c95fcf7b38791a2e4fb0eb7d1fac4 100644 (file)
--- a/examples/stablelm/quantize.cpp
+++ b/examples/stablelm/quantize.cpp
@@ -1,6 +1,6 @@
 #include "ggml/ggml.h"
 
-#include "utils.h"
+#include "common.h"
 
 #include <cassert>
 #include <cmath>

diff --git a/examples/utils.cpp b/examples/utils.cpp
deleted file mode 100644 (file)
index 30057b7..0000000
--- a/examples/utils.cpp
+++ /dev/null
@@ -1,330 +0,0 @@
-#include "utils.h"
-
-#include <fstream>
-#include <regex>
-
-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(argv[++i]);
-        } else if (arg == "-t" || arg == "--threads") {
-            params.n_threads = std::stoi(argv[++i]);
-        } else if (arg == "-p" || arg == "--prompt") {
-            params.prompt = argv[++i];
-        } else if (arg == "-n" || arg == "--n_predict") {
-            params.n_predict = std::stoi(argv[++i]);
-        } else if (arg == "--top_k") {
-            params.top_k = std::stoi(argv[++i]);
-        } else if (arg == "--top_p") {
-            params.top_p = std::stof(argv[++i]);
-        } else if (arg == "--temp") {
-            params.temp = std::stof(argv[++i]);
-        } else if (arg == "-b" || arg == "--batch_size") {
-            params.n_batch = std::stoi(argv[++i]);
-        } else if (arg == "-m" || arg == "--model") {
-            params.model = argv[++i];
-        } else if (arg == "-h" || arg == "--help") {
-            gpt_print_usage(argc, argv, params);
-            exit(0);
-        } 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, "  -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, "  -b N, --batch_size N  batch size for prompt processing (default: %d)\n", params.n_batch);
-    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";
-        default: return "To";
-    }
-
-    return "The";
-}
-
-void replace(std::string & str, const std::string & needle, const std::string & replacement) {
-    size_t pos = 0;
-    while ((pos = str.find(needle, pos)) != std::string::npos) {
-        str.replace(pos, needle.length(), replacement);
-        pos += replacement.length();
-    }
-}
-
-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;
-                    }
-
-                    ::replace(str_key, "\\u0120", " " ); // \u0120 -> space
-                    ::replace(str_key, "\\u010a", "\n"); // \u010a -> new line
-                    ::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;
-}
-
-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;
-        std::string pat = R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)";
-
-        std::regex re(pat);
-        std::smatch m;
-
-        while (std::regex_search(str, m, re)) {
-            for (auto x : m) {
-                words.push_back(x);
-            }
-            str = m.suffix();
-        }
-    }
-
-    // find the longest tokens that form the words:
-    std::vector<gpt_vocab::id> tokens;
-    for (const auto & word : words) {
-        if (word.size() == 0) continue;
-
-        int i = 0;
-        int n = word.size();
-        while (i < n) {
-            int j = n;
-            while (j > i) {
-                auto it = vocab.token_to_id.find(word.substr(i, j-i));
-                if (it != vocab.token_to_id.end()) {
-                    tokens.push_back(it->second);
-                    i = j;
-                    break;
-                }
-                --j;
-            }
-            if (i == n) {
-                break;
-            }
-            if (j == i) {
-                auto sub = word.substr(i, 1);
-                if (vocab.token_to_id.find(sub) != vocab.token_to_id.end()) {
-                    tokens.push_back(vocab.token_to_id.at(sub));
-                } else {
-                    fprintf(stderr, "%s: unknown token '%s'\n", __func__, sub.data());
-                }
-                ++i;
-            }
-        }
-    }
-
-    return tokens;
-}
-
-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,
-        int    top_k,
-        double top_p,
-        double temp,
-        std::mt19937 & rng) {
-    int n_logits = vocab.id_to_token.size();
-
-    std::vector<std::pair<double, gpt_vocab::id>> logits_id;
-    logits_id.reserve(n_logits);
-
-    {
-        const double scale = 1.0/temp;
-        for (int i = 0; i < n_logits; ++i) {
-            logits_id.push_back(std::make_pair(logits[i]*scale, i));
-        }
-    }
-
-    // find the top K tokens
-    std::partial_sort(
-            logits_id.begin(),
-            logits_id.begin() + top_k, logits_id.end(),
-            [](const std::pair<double, gpt_vocab::id> & a, const std::pair<double, gpt_vocab::id> & b) {
-        return a.first > b.first;
-    });
-
-    logits_id.resize(top_k);
-
-    double maxl = -INFINITY;
-    for (const auto & kv : logits_id) {
-        maxl = std::max(maxl, kv.first);
-    }
-
-    // compute probs for the top K tokens
-    std::vector<double> probs;
-    probs.reserve(logits_id.size());
-
-    double sum = 0.0;
-    for (const auto & kv : logits_id) {
-        double p = exp(kv.first - maxl);
-        probs.push_back(p);
-        sum += p;
-    }
-
-    // normalize the probs
-    for (auto & p : probs) {
-        p /= sum;
-    }
-
-    if (top_p < 1.0f) {
-        double cumsum = 0.0f;
-        for (int i = 0; i < top_k; i++) {
-            cumsum += probs[i];
-            if (cumsum >= top_p) {
-                top_k = i + 1;
-                probs.resize(top_k);
-                logits_id.resize(top_k);
-                break;
-            }
-        }
-
-        cumsum = 1.0/cumsum;
-        for (int i = 0; i < (int) probs.size(); i++) {
-            probs[i] *= cumsum;
-        }
-    }
-
-    //printf("\n");
-    //for (int i = 0; i < (int) probs.size(); i++) {
-    //    printf("%d: '%s' %f\n", i, vocab.id_to_token.at(logits_id[i].second).c_str(), probs[i]);
-    //}
-    //exit(0);
-
-    std::discrete_distribution<> dist(probs.begin(), probs.end());
-    int idx = dist(rng);
-
-    return logits_id[idx].second;
-}

diff --git a/examples/utils.h b/examples/utils.h
deleted file mode 100644 (file)
index b61173f..0000000
--- a/examples/utils.h
+++ /dev/null
@@ -1,83 +0,0 @@
-// Various helper functions and utilities
-
-#pragma once
-
-#include <string>
-#include <map>
-#include <vector>
-#include <random>
-#include <thread>
-
-//
-// 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
-
-    // sampling parameters
-    int32_t top_k = 40;
-    float   top_p = 0.9f;
-    float   temp  = 0.9f;
-
-    int32_t n_batch = 8; // batch size for prompt processing
-
-    std::string model = "models/gpt-2-117M/ggml-model.bin"; // model path
-    std::string prompt;
-};
-
-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
-//
-
-struct gpt_vocab {
-    using id    = int32_t;
-    using token = std::string;
-
-    std::map<token, id> token_to_id;
-    std::map<id, token> id_to_token;
-};
-
-void replace(std::string & str, const std::string & needle, const std::string & replacement);
-
-// poor-man's JSON parsing
-std::map<std::string, int32_t> json_parse(const std::string & fname);
-
-// 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);
-
-// 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
-//   - from them, consider only the top tokens with cumulative probability > P
-//
-// TODO: not sure if this implementation is correct
-// TODO: temperature is not implemented
-//
-gpt_vocab::id gpt_sample_top_k_top_p(
-        const gpt_vocab & vocab,
-        const float * logits,
-        int    top_k,
-        double top_p,
-        double temp,
-        std::mt19937 & rng);

diff --git a/examples/whisper/CMakeLists.txt b/examples/whisper/CMakeLists.txt
index c7f5ff54ea0f9e5b2d9d2c51c13965761b180c39..67500672e584e712f4d6b2000bc5fdf2e52ca9a3 100644 (file)
--- a/examples/whisper/CMakeLists.txt
+++ b/examples/whisper/CMakeLists.txt
@@ -10,8 +10,8 @@ target_link_libraries(whisper-cpp PRIVATE
     )
 
 set(TEST_TARGET whisper)
-add_executable(${TEST_TARGET} main.cpp common.cpp)
-target_link_libraries(${TEST_TARGET} PRIVATE whisper-cpp)
+add_executable(${TEST_TARGET} main.cpp)
+target_link_libraries(${TEST_TARGET} PRIVATE whisper-cpp common)
 target_include_directories(${TEST_TARGET} PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/..)
 
 #
@@ -19,4 +19,4 @@ target_include_directories(${TEST_TARGET} PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/..
 
 set(TEST_TARGET whisper-quantize)
 add_executable(${TEST_TARGET} quantize.cpp)
-target_link_libraries(${TEST_TARGET} PRIVATE ggml ggml_utils)
+target_link_libraries(${TEST_TARGET} PRIVATE ggml common)

diff --git a/examples/whisper/common.cpp b/examples/whisper/common.cpp
deleted file mode 100644 (file)
index 194ef0e..0000000
--- a/examples/whisper/common.cpp
+++ /dev/null
@@ -1,162 +0,0 @@
-#include "common.h"
-
-// third-party utilities
-// use your favorite implementations
-#define DR_WAV_IMPLEMENTATION
-#include "dr_wav.h"
-
-#include <cmath>
-#include <regex>
-
-#ifndef M_PI
-#define M_PI 3.14159265358979323846
-#endif
-
-std::string trim(const std::string & s) {
-    std::regex e("^\\s+|\\s+$");
-    return std::regex_replace(s, e, "");
-}
-
-std::string replace(const std::string & s, const std::string & from, const std::string & to) {
-    std::string result = s;
-    size_t pos = 0;
-    while ((pos = result.find(from, pos)) != std::string::npos) {
-        result.replace(pos, from.length(), to);
-        pos += to.length();
-    }
-    return result;
-}
-
-bool read_wav(const std::string & fname, std::vector<float>& pcmf32, std::vector<std::vector<float>>& pcmf32s, bool stereo) {
-    drwav wav;
-    std::vector<uint8_t> wav_data; // used for pipe input from stdin
-
-    if (fname == "-") {
-        {
-            uint8_t buf[1024];
-            while (true)
-            {
-                const size_t n = fread(buf, 1, sizeof(buf), stdin);
-                if (n == 0) {
-                    break;
-                }
-                wav_data.insert(wav_data.end(), buf, buf + n);
-            }
-        }
-
-        if (drwav_init_memory(&wav, wav_data.data(), wav_data.size(), nullptr) == false) {
-            fprintf(stderr, "error: failed to open WAV file from stdin\n");
-            return false;
-        }
-
-        fprintf(stderr, "%s: read %zu bytes from stdin\n", __func__, wav_data.size());
-    }
-    else if (drwav_init_file(&wav, fname.c_str(), nullptr) == false) {
-        fprintf(stderr, "error: failed to open '%s' as WAV file\n", fname.c_str());
-        return false;
-    }
-
-    if (wav.channels != 1 && wav.channels != 2) {
-        fprintf(stderr, "%s: WAV file '%s' must be mono or stereo\n", __func__, fname.c_str());
-        return false;
-    }
-
-    if (stereo && wav.channels != 2) {
-        fprintf(stderr, "%s: WAV file '%s' must be stereo for diarization\n", __func__, fname.c_str());
-        return false;
-    }
-
-    if (wav.sampleRate != COMMON_SAMPLE_RATE) {
-        fprintf(stderr, "%s: WAV file '%s' must be %i kHz\n", __func__, fname.c_str(), COMMON_SAMPLE_RATE/1000);
-        return false;
-    }
-
-    if (wav.bitsPerSample != 16) {
-        fprintf(stderr, "%s: WAV file '%s' must be 16-bit\n", __func__, fname.c_str());
-        return false;
-    }
-
-    const uint64_t n = wav_data.empty() ? wav.totalPCMFrameCount : wav_data.size()/(wav.channels*wav.bitsPerSample/8);
-
-    std::vector<int16_t> pcm16;
-    pcm16.resize(n*wav.channels);
-    drwav_read_pcm_frames_s16(&wav, n, pcm16.data());
-    drwav_uninit(&wav);
-
-    // convert to mono, float
-    pcmf32.resize(n);
-    if (wav.channels == 1) {
-        for (uint64_t i = 0; i < n; i++) {
-            pcmf32[i] = float(pcm16[i])/32768.0f;
-        }
-    } else {
-        for (uint64_t i = 0; i < n; i++) {
-            pcmf32[i] = float(pcm16[2*i] + pcm16[2*i + 1])/65536.0f;
-        }
-    }
-
-    if (stereo) {
-        // convert to stereo, float
-        pcmf32s.resize(2);
-
-        pcmf32s[0].resize(n);
-        pcmf32s[1].resize(n);
-        for (uint64_t i = 0; i < n; i++) {
-            pcmf32s[0][i] = float(pcm16[2*i])/32768.0f;
-            pcmf32s[1][i] = float(pcm16[2*i + 1])/32768.0f;
-        }
-    }
-
-    return true;
-}
-
-void high_pass_filter(std::vector<float> & data, float cutoff, float sample_rate) {
-    const float rc = 1.0f / (2.0f * M_PI * cutoff);
-    const float dt = 1.0f / sample_rate;
-    const float alpha = dt / (rc + dt);
-
-    float y = data[0];
-
-    for (size_t i = 1; i < data.size(); i++) {
-        y = alpha * (y + data[i] - data[i - 1]);
-        data[i] = y;
-    }
-}
-
-bool vad_simple(std::vector<float> & pcmf32, int sample_rate, int last_ms, float vad_thold, float freq_thold, bool verbose) {
-    const int n_samples      = pcmf32.size();
-    const int n_samples_last = (sample_rate * last_ms) / 1000;
-
-    if (n_samples_last >= n_samples) {
-        // not enough samples - assume no speech
-        return false;
-    }
-
-    if (freq_thold > 0.0f) {
-        high_pass_filter(pcmf32, freq_thold, sample_rate);
-    }
-
-    float energy_all  = 0.0f;
-    float energy_last = 0.0f;
-
-    for (int i = 0; i < n_samples; i++) {
-        energy_all += fabsf(pcmf32[i]);
-
-        if (i >= n_samples - n_samples_last) {
-            energy_last += fabsf(pcmf32[i]);
-        }
-    }
-
-    energy_all  /= n_samples;
-    energy_last /= n_samples_last;
-
-    if (verbose) {
-        fprintf(stderr, "%s: energy_all: %f, energy_last: %f, vad_thold: %f, freq_thold: %f\n", __func__, energy_all, energy_last, vad_thold, freq_thold);
-    }
-
-    if (energy_last > vad_thold*energy_all) {
-        return false;
-    }
-
-    return true;
-}

diff --git a/examples/whisper/common.h b/examples/whisper/common.h
deleted file mode 100644 (file)
index 04dd7cb..0000000
--- a/examples/whisper/common.h
+++ /dev/null
@@ -1,40 +0,0 @@
-#pragma once
-
-// needs to match WHISPER_SAMPLE_RATE
-#define COMMON_SAMPLE_RATE 16000
-
-#include <vector>
-#include <string>
-
-std::string trim(const std::string & s);
-
-std::string replace(
-        const std::string & s,
-        const std::string & from,
-        const std::string & to);
-
-// Read WAV audio file and store the PCM data into pcmf32
-// The sample rate of the audio must be equal to COMMON_SAMPLE_RATE
-// If stereo flag is set and the audio has 2 channels, the pcmf32s will contain 2 channel PCM
-bool read_wav(
-        const std::string & fname,
-        std::vector<float> & pcmf32,
-        std::vector<std::vector<float>> & pcmf32s,
-        bool stereo);
-
-// Apply a high-pass frequency filter to PCM audio
-// Suppresses frequencies below cutoff Hz
-void high_pass_filter(
-        std::vector<float> & data,
-        float cutoff,
-        float sample_rate);
-
-// Basic voice activity detection (VAD) using audio energy adaptive threshold
-bool vad_simple(
-        std::vector<float> & pcmf32,
-        int   sample_rate,
-        int   last_ms,
-        float vad_thold,
-        float freq_thold,
-        bool  verbose);
-

diff --git a/examples/whisper/quantize.cpp b/examples/whisper/quantize.cpp
index ae3a5b8a9e3a4fcddd98c5932c91a6833948556a..2af2a0d0ffbfd93899b424beec3547ae21db93c8 100644 (file)
--- a/examples/whisper/quantize.cpp
+++ b/examples/whisper/quantize.cpp
@@ -1,6 +1,6 @@
 #include "ggml/ggml.h"
 
-#include "utils.h"
+#include "common.h"
 
 #include <cassert>
 #include <cmath>