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parallel : adding tool for parallel transformer inference

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This commit is contained in:
Georgi Gerganov 2022-10-29 09:27:08 +03:00
parent c565c569e7
commit 72e9cdd6bf
5 changed files with 495 additions and 27 deletions
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3
examples/parallel/CMakeLists.txt Normal file
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@ -0,0 +1,3 @@
set(TARGET parallel)
add_executable(${TARGET} parallel.cpp)
target_link_libraries(${TARGET} PRIVATE whisper ${CMAKE_THREAD_LIBS_INIT})

3
examples/parallel/README.md Normal file
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@ -0,0 +1,3 @@
# parallel
TODO

422
examples/parallel/parallel.cpp Normal file
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@ -0,0 +1,422 @@
#include "whisper.h"
// third-party utilities
// use your favorite implementations
#define DR_WAV_IMPLEMENTATION
#include "dr_wav.h"
#include <cmath>
#include <fstream>
#include <cstdio>
#include <string>
#include <thread>
#include <vector>
// Terminal color map. 10 colors grouped in ranges [0.0, 0.1, ..., 0.9]
// Lowest is red, middle is yellow, highest is green.
const std::vector<std::string> k_colors = {
"\033[38;5;196m", "\033[38;5;202m", "\033[38;5;208m", "\033[38;5;214m", "\033[38;5;220m",
"\033[38;5;226m", "\033[38;5;190m", "\033[38;5;154m", "\033[38;5;118m", "\033[38;5;82m",
};
// 500 -> 00:05.000
// 6000 -> 01:00.000
std::string to_timestamp(int64_t t, bool comma = false) {
int64_t msec = t * 10;
int64_t hr = msec / (1000 * 60 * 60);
msec = msec - hr * (1000 * 60 * 60);
int64_t min = msec / (1000 * 60);
msec = msec - min * (1000 * 60);
int64_t sec = msec / 1000;
msec = msec - sec * 1000;
char buf[32];
snprintf(buf, sizeof(buf), "%02d:%02d:%02d%s%03d", (int) hr, (int) min, (int) sec, comma ? "," : ".", (int) msec);
return std::string(buf);
}
// command-line parameters
struct whisper_params {
int32_t seed = -1; // RNG seed, not used currently
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t offset_t_ms = 0;
int32_t offset_n = 0;
bool verbose = false;
bool translate = false;
bool output_txt = false;
bool output_vtt = false;
bool output_srt = false;
bool print_special_tokens = false;
bool print_colors = false;
bool no_timestamps = false;
std::string language = "en";
std::string model = "models/ggml-base.en.bin";
std::vector<std::string> fname_inp = {};
};
void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
for (int i = 1; i < argc; i++) {
std::string arg = argv[i];
if (arg[0] != '-') {
params.fname_inp.push_back(arg);
continue;
}
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 == "-ot" || arg == "--offset-t") {
params.offset_t_ms = std::stoi(argv[++i]);
} else if (arg == "-on" || arg == "--offset-n") {
params.offset_n = std::stoi(argv[++i]);
} else if (arg == "-v" || arg == "--verbose") {
params.verbose = true;
} else if (arg == "--translate") {
params.translate = true;
} else if (arg == "-l" || arg == "--language") {
params.language = argv[++i];
if (whisper_lang_id(params.language.c_str()) == -1) {
fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
}
} else if (arg == "-otxt" || arg == "--output-txt") {
params.output_txt = true;
} else if (arg == "-ovtt" || arg == "--output-vtt") {
params.output_vtt = true;
} else if (arg == "-osrt" || arg == "--output-srt") {
params.output_srt = true;
} else if (arg == "-ps" || arg == "--print_special") {
params.print_special_tokens = true;
} else if (arg == "-pc" || arg == "--print_colors") {
params.print_colors = true;
} else if (arg == "-nt" || arg == "--no_timestamps") {
params.no_timestamps = true;
} else if (arg == "-m" || arg == "--model") {
params.model = argv[++i];
} else if (arg == "-f" || arg == "--file") {
params.fname_inp.push_back(argv[++i]);
} else if (arg == "-h" || arg == "--help") {
whisper_print_usage(argc, argv, params);
exit(0);
} else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
}
}
return true;
}
void whisper_print_usage(int argc, char ** argv, const whisper_params & params) {
fprintf(stderr, "\n");
fprintf(stderr, "usage: %s [options] file0.wav file1.wav ...\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, " -ot N, --offset-t N time offset in milliseconds (default: %d)\n", params.offset_t_ms);
fprintf(stderr, " -on N, --offset-n N segment index offset (default: %d)\n", params.offset_n);
fprintf(stderr, " -v, --verbose verbose output\n");
fprintf(stderr, " --translate translate from source language to english\n");
fprintf(stderr, " -otxt, --output-txt output result in a text file\n");
fprintf(stderr, " -ovtt, --output-vtt output result in a vtt file\n");
fprintf(stderr, " -osrt, --output-srt output result in a srt file\n");
fprintf(stderr, " -ps, --print_special print special tokens\n");
fprintf(stderr, " -pc, --print_colors print colors\n");
fprintf(stderr, " -nt, --no_timestamps do not print timestamps\n");
fprintf(stderr, " -l LANG, --language LANG spoken language (default: %s)\n", params.language.c_str());
fprintf(stderr, " -m FNAME, --model FNAME model path (default: %s)\n", params.model.c_str());
fprintf(stderr, " -f FNAME, --file FNAME input WAV file path\n");
fprintf(stderr, "\n");
}
void whisper_print_segment_callback(struct whisper_context * ctx, void * user_data) {
const whisper_params & params = *(whisper_params *) user_data;
const int n_segments = whisper_full_n_segments(ctx);
// print the last segment
const int i = n_segments - 1;
if (i == 0) {
printf("\n");
}
if (params.no_timestamps) {
if (params.print_colors) {
for (int j = 0; j < whisper_full_n_tokens(ctx, i); ++j) {
if (params.print_special_tokens == false) {
const whisper_token id = whisper_full_get_token_id(ctx, i, j);
if (id >= whisper_token_eot(ctx)) {
continue;
}
}
const char * text = whisper_full_get_token_text(ctx, i, j);
const float p = whisper_full_get_token_p (ctx, i, j);
const int col = std::max(0, std::min((int) k_colors.size(), (int) (std::pow(p, 3)*float(k_colors.size()))));
printf("%s%s%s", k_colors[col].c_str(), text, "\033[0m");
}
} else {
const char * text = whisper_full_get_segment_text(ctx, i);
printf("%s", text);
}
fflush(stdout);
} else {
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
if (params.print_colors) {
printf("[%s --> %s] ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str());
for (int j = 0; j < whisper_full_n_tokens(ctx, i); ++j) {
if (params.print_special_tokens == false) {
const whisper_token id = whisper_full_get_token_id(ctx, i, j);
if (id >= whisper_token_eot(ctx)) {
continue;
}
}
const char * text = whisper_full_get_token_text(ctx, i, j);
const float p = whisper_full_get_token_p (ctx, i, j);
const int col = std::max(0, std::min((int) k_colors.size(), (int) (std::pow(p, 3)*float(k_colors.size()))));
printf("%s%s%s", k_colors[col].c_str(), text, "\033[0m");
}
printf("\n");
} else {
const char * text = whisper_full_get_segment_text(ctx, i);
printf("[%s --> %s] %s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), text);
}
}
}
bool output_txt(struct whisper_context * ctx, const char * fname) {
std::ofstream fout(fname);
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return false;
}
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
const int n_segments = whisper_full_n_segments(ctx);
for (int i = 0; i < n_segments; ++i) {
const char * text = whisper_full_get_segment_text(ctx, i);
fout << text;
}
return true;
}
bool output_vtt(struct whisper_context * ctx, const char * fname) {
std::ofstream fout(fname);
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return 9;
}
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
fout << "WEBVTT\n\n";
const int n_segments = whisper_full_n_segments(ctx);
for (int i = 0; i < n_segments; ++i) {
const char * text = whisper_full_get_segment_text(ctx, i);
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
fout << to_timestamp(t0) << " --> " << to_timestamp(t1) << "\n";
fout << text << "\n\n";
}
return true;
}
bool output_srt(struct whisper_context * ctx, const char * fname, const whisper_params & params) {
std::ofstream fout(fname);
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return false;
}
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
const int n_segments = whisper_full_n_segments(ctx);
for (int i = 0; i < n_segments; ++i) {
const char * text = whisper_full_get_segment_text(ctx, i);
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
fout << i + 1 + params.offset_n << "\n";
fout << to_timestamp(t0, true) << " --> " << to_timestamp(t1, true) << "\n";
fout << text << "\n\n";
}
return true;
}
int main(int argc, char ** argv) {
whisper_params params;
if (whisper_params_parse(argc, argv, params) == false) {
return 1;
}
if (params.seed < 0) {
params.seed = time(NULL);
}
if (params.fname_inp.empty()) {
fprintf(stderr, "error: no input files specified\n");
whisper_print_usage(argc, argv, params);
return 2;
}
// whisper init
struct whisper_context * ctx = whisper_init(params.model.c_str());
if (ctx == nullptr) {
fprintf(stderr, "error: failed to initialize whisper context\n");
return 3;
}
for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
const auto fname_inp = params.fname_inp[f];
// WAV input
std::vector<float> pcmf32;
{
drwav wav;
if (!drwav_init_file(&wav, fname_inp.c_str(), NULL)) {
fprintf(stderr, "%s: failed to open WAV file '%s' - check your input\n", argv[0], fname_inp.c_str());
whisper_print_usage(argc, argv, {});
return 4;
}
if (wav.channels != 1 && wav.channels != 2) {
fprintf(stderr, "%s: WAV file '%s' must be mono or stereo\n", argv[0], fname_inp.c_str());
return 5;
}
if (wav.sampleRate != WHISPER_SAMPLE_RATE) {
fprintf(stderr, "%s: WAV file '%s' must be 16 kHz\n", argv[0], fname_inp.c_str());
return 6;
}
if (wav.bitsPerSample != 16) {
fprintf(stderr, "%s: WAV file '%s' must be 16-bit\n", argv[0], fname_inp.c_str());
return 7;
}
int n = wav.totalPCMFrameCount;
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 (int i = 0; i < n; i++) {
pcmf32[i] = float(pcm16[i])/32768.0f;
}
} else {
for (int i = 0; i < n; i++) {
pcmf32[i] = float(pcm16[2*i] + pcm16[2*i + 1])/65536.0f;
}
}
}
// print system information
{
fprintf(stderr, "\n");
fprintf(stderr, "system_info: n_threads = %d / %d | %s\n", params.n_threads, std::thread::hardware_concurrency(), whisper_print_system_info());
}
// print some info about the processing
{
fprintf(stderr, "\n");
if (!whisper_is_multilingual(ctx)) {
if (params.language != "en" || params.translate) {
params.language = "en";
params.translate = false;
fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
}
}
fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, lang = %s, task = %s, timestamps = %d ...\n",
__func__, fname_inp.c_str(), int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE, params.n_threads,
params.language.c_str(),
params.translate ? "translate" : "transcribe",
params.no_timestamps ? 0 : 1);
fprintf(stderr, "\n");
}
// run the inference
{
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
wparams.print_realtime = false;
wparams.print_progress = false;
wparams.print_timestamps = !params.no_timestamps;
wparams.print_special_tokens = params.print_special_tokens;
wparams.translate = params.translate;
wparams.language = params.language.c_str();
wparams.n_threads = params.n_threads;
wparams.offset_ms = params.offset_t_ms;
// this callback is called on each new segment
if (!wparams.print_realtime) {
wparams.new_segment_callback = whisper_print_segment_callback;
wparams.new_segment_callback_user_data = &params;
}
if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
fprintf(stderr, "%s: failed to process audio\n", argv[0]);
return 8;
}
printf("\n");
// output to text file
if (params.output_txt) {
const auto fname_txt = fname_inp + ".txt";
output_txt(ctx, fname_txt.c_str());
}
// output to VTT file
if (params.output_vtt) {
const auto fname_vtt = fname_inp + ".vtt";
output_vtt(ctx, fname_vtt.c_str());
}
// output to SRT file
if (params.output_srt) {
const auto fname_srt = fname_inp + ".srt";
output_srt(ctx, fname_srt.c_str(), params);
}
}
}
whisper_print_timings(ctx);
whisper_free(ctx);
return 0;
}

91
whisper.cpp
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@ -413,7 +413,6 @@ struct whisper_context {
std::vector<float> probs;
std::vector<float> logits;
std::vector<whisper_token_data> tokens_cur;
std::vector<whisper_segment> result_all;
std::vector<whisper_token> prompt_past;
@ -430,7 +429,7 @@ struct whisper_context {
//
// see the convert-pt-to-ggml.py script for details
//
bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
bool whisper_model_load(const std::string & fname, const int n_processors, whisper_context & wctx) {
fprintf(stderr, "%s: loading model from '%s'\n", __func__, fname.c_str());
auto & model = wctx.model;
@ -700,11 +699,11 @@ bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
ctx_size += n_text_layer*( n_text_state*ggml_type_size(GGML_TYPE_F32)); // cross_attn_ln_1_b
}
ctx_size += n_text_layer*n_text_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_k
ctx_size += n_text_layer*n_text_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_v
ctx_size += n_processors*n_text_layer*n_text_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_k
ctx_size += n_processors*n_text_layer*n_text_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_v
ctx_size += n_text_layer*n_audio_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_cross_k
ctx_size += n_text_layer*n_audio_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_cross_v
ctx_size += n_processors*n_text_layer*n_audio_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_cross_k
ctx_size += n_processors*n_text_layer*n_audio_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_cross_v
ctx_size += (15 + 15*n_audio_layer + 24*n_text_layer)*256; // object overhead
@ -934,7 +933,7 @@ bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
// key/value memory for the self-attention layer
{
const int n_mem = n_text_layer*n_text_ctx;
const int n_elements = n_text_state*n_mem;
const int n_elements = n_text_state*n_mem*n_processors;
model.memory_k = ggml_new_tensor_1d(ctx, GGML_TYPE_F16, n_elements);
model.memory_v = ggml_new_tensor_1d(ctx, GGML_TYPE_F16, n_elements);
@ -945,7 +944,7 @@ bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
const int n_audio_ctx = hparams.n_audio_ctx;
const int n_mem = n_text_layer*n_audio_ctx;
const int n_elements = n_text_state*n_mem;
const int n_elements = n_text_state*n_mem*n_processors;
model.memory_cross_k = ggml_new_tensor_1d(ctx, GGML_TYPE_F16, n_elements);
model.memory_cross_v = ggml_new_tensor_1d(ctx, GGML_TYPE_F16, n_elements);
@ -955,7 +954,7 @@ bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
ggml_nbytes(model.memory_k) + ggml_nbytes(model.memory_v) +
ggml_nbytes(model.memory_cross_k) + ggml_nbytes(model.memory_cross_v);
fprintf(stderr, "%s: memory size = %8.2f MB \n", __func__, memory_size/1024.0/1024.0);
fprintf(stderr, "%s: memory size = %8.2f MB (%d processors)\n", __func__, memory_size/1024.0/1024.0, n_processors);
}
// load weights
@ -1046,7 +1045,8 @@ bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
bool whisper_encode(
whisper_context & wctx,
const int n_threads,
const int mel_offset) {
const int mel_offset,
const int processor_id) {
const auto & model = wctx.model;
const auto & mel_inp = wctx.mel;
const auto & hparams = model.hparams;
@ -1400,8 +1400,11 @@ bool whisper_encode(
Vcross),
Vcross);
struct ggml_tensor * k = ggml_view_1d(ctx0, model.memory_cross_k, n_state*n_ctx, (ggml_element_size(model.memory_cross_k)*n_state)*(il*n_ctx));
struct ggml_tensor * v = ggml_view_1d(ctx0, model.memory_cross_v, n_state*n_ctx, (ggml_element_size(model.memory_cross_v)*n_state)*(il*n_ctx));
const size_t offset_k = processor_id*(ggml_element_size(model.memory_cross_k)*n_state)*(model.hparams.n_text_layer*n_ctx);
const size_t offset_v = processor_id*(ggml_element_size(model.memory_cross_v)*n_state)*(model.hparams.n_text_layer*n_ctx);
struct ggml_tensor * k = ggml_view_1d(ctx0, model.memory_cross_k, n_state*n_ctx, offset_k + (ggml_element_size(model.memory_cross_k)*n_state)*(il*n_ctx));
struct ggml_tensor * v = ggml_view_1d(ctx0, model.memory_cross_v, n_state*n_ctx, offset_v + (ggml_element_size(model.memory_cross_v)*n_state)*(il*n_ctx));
ggml_build_forward_expand(&gf, ggml_cpy(ctx0, Kcross, k));
ggml_build_forward_expand(&gf, ggml_cpy(ctx0, Vcross, v));
@ -1434,7 +1437,8 @@ bool whisper_decode(
const int n_threads,
const whisper_token * tokens,
const int n_tokens,
const int n_past) {
const int n_past,
const int processor_id) {
const auto & model = wctx.model;
const auto & hparams = model.hparams;
@ -1529,10 +1533,13 @@ bool whisper_decode(
Vcur),
Vcur);
const size_t offset_k = processor_id*(ggml_element_size(model.memory_k)*n_state)*(n_layer*n_ctx);
const size_t offset_v = processor_id*(ggml_element_size(model.memory_v)*n_state)*(n_layer*n_ctx);
// store key and value to memory
{
struct ggml_tensor * k = ggml_view_1d(ctxL, model.memory_k, N*n_state, (ggml_element_size(model.memory_k)*n_state)*(il*n_ctx + n_past));
struct ggml_tensor * v = ggml_view_1d(ctxL, model.memory_v, N*n_state, (ggml_element_size(model.memory_v)*n_state)*(il*n_ctx + n_past));
struct ggml_tensor * k = ggml_view_1d(ctxL, model.memory_k, N*n_state, offset_k + (ggml_element_size(model.memory_k)*n_state)*(il*n_ctx + n_past));
struct ggml_tensor * v = ggml_view_1d(ctxL, model.memory_v, N*n_state, offset_v + (ggml_element_size(model.memory_v)*n_state)*(il*n_ctx + n_past));
ggml_build_forward_expand(&gf, ggml_cpy(ctxL, Kcur, k));
ggml_build_forward_expand(&gf, ggml_cpy(ctxL, Vcur, v));
@ -1550,7 +1557,7 @@ bool whisper_decode(
struct ggml_tensor * K =
ggml_permute(ctxL,
ggml_reshape_3d(ctxL,
ggml_view_1d(ctxL, model.memory_k, (n_past + N)*n_state, il*n_ctx*ggml_element_size(model.memory_k)*n_state),
ggml_view_1d(ctxL, model.memory_k, (n_past + N)*n_state, offset_k + il*n_ctx*ggml_element_size(model.memory_k)*n_state),
n_state/n_head, n_head, n_past + N),
0, 2, 1, 3);
@ -1570,7 +1577,7 @@ bool whisper_decode(
struct ggml_tensor * V_trans =
ggml_permute(ctxL,
ggml_reshape_3d(ctxL,
ggml_view_1d(ctxL, model.memory_v, (n_past + N)*n_state, il*n_ctx*ggml_element_size(model.memory_v)*n_state),
ggml_view_1d(ctxL, model.memory_v, (n_past + N)*n_state, offset_v + il*n_ctx*ggml_element_size(model.memory_v)*n_state),
n_state/n_head, n_head, n_past + N),
1, 2, 0, 3);
@ -1622,15 +1629,18 @@ bool whisper_decode(
Qcur = ggml_scale(ctxL, Qcur, ggml_new_f32(ctxL, pow(float(n_state)/n_head, -0.25)));
const size_t offset_k = processor_id*(ggml_element_size(model.memory_cross_k)*n_state)*(n_layer*M);
const size_t offset_v = processor_id*(ggml_element_size(model.memory_cross_v)*n_state)*(n_layer*M);
// Kcross is already scaled
struct ggml_tensor * Kcross =
ggml_reshape_3d(ctxL,
ggml_view_1d(ctxL, model.memory_cross_k, M*n_state, il*M*ggml_element_size(model.memory_cross_k)*n_state),
ggml_view_1d(ctxL, model.memory_cross_k, M*n_state, offset_k + il*M*ggml_element_size(model.memory_cross_k)*n_state),
n_state/n_head, n_head, M);
struct ggml_tensor * Vcross =
ggml_reshape_3d(ctxL,
ggml_view_1d(ctxL, model.memory_cross_v, M*n_state, il*M*ggml_element_size(model.memory_cross_v)*n_state),
ggml_view_1d(ctxL, model.memory_cross_v, M*n_state, offset_v + il*M*ggml_element_size(model.memory_cross_v)*n_state),
n_state/n_head, n_head, M);
// ------
@ -2116,7 +2126,26 @@ struct whisper_context * whisper_init(const char * path_model) {
ctx->t_start_us = t_start_us;
if (!whisper_model_load(path_model, *ctx)) {
if (!whisper_model_load(path_model, 1, *ctx)) {
fprintf(stderr, "%s: failed to load model from '%s'\n", __func__, path_model);
return NULL;
}
ctx->t_load_us = ggml_time_us() - t_start_us;
return ctx;
}
struct whisper_context * whisper_init_parallel(const char * path_model, int n_processors) {
ggml_time_init();
whisper_context * ctx = new whisper_context;
const int64_t t_start_us = ggml_time_us();
ctx->t_start_us = t_start_us;
if (!whisper_model_load(path_model, n_processors, *ctx)) {
fprintf(stderr, "%s: failed to load model from '%s'\n", __func__, path_model);
return NULL;
}
@ -2167,7 +2196,7 @@ int whisper_set_mel(
int whisper_encode(struct whisper_context * ctx, int offset, int n_threads) {
const int64_t t_start_us = ggml_time_us();
if (!whisper_encode(*ctx, n_threads, offset)) {
if (!whisper_encode(*ctx, n_threads, offset, 0)) {
fprintf(stderr, "%s: failed to eval\n", __func__);
return -1;
}
@ -2180,7 +2209,7 @@ int whisper_encode(struct whisper_context * ctx, int offset, int n_threads) {
int whisper_decode(struct whisper_context * ctx, const whisper_token * tokens, int n_tokens, int n_past, int n_threads) {
const int64_t t_start_us = ggml_time_us();
if (!whisper_decode(*ctx, n_threads, tokens, n_tokens, n_past)) {
if (!whisper_decode(*ctx, n_threads, tokens, n_tokens, n_past, 0)) {
fprintf(stderr, "%s: failed to eval\n", __func__);
return 1;
}
@ -2302,6 +2331,7 @@ struct whisper_full_params whisper_full_default_params(enum whisper_sampling_str
/*.n_threads =*/ std::min(4, (int32_t) std::thread::hardware_concurrency()),
/*.offset_ms =*/ 0,
/*.n_processors =*/ 1,
/*.translate =*/ false,
/*.no_context =*/ false,
@ -2333,6 +2363,7 @@ struct whisper_full_params whisper_full_default_params(enum whisper_sampling_str
/*.n_threads =*/ std::min(4, (int32_t) std::thread::hardware_concurrency()),
/*.offset_ms =*/ 0,
/*.n_processors =*/ 1,
/*.translate =*/ false,
/*.no_context =*/ false,
@ -2369,7 +2400,6 @@ int whisper_full(
int n_samples) {
// clear old results
auto & result_all = ctx->result_all;
auto & tokens_cur = ctx->tokens_cur;
result_all.clear();
@ -2379,10 +2409,12 @@ int whisper_full(
return -1;
}
const int seek_start = params.offset_ms/10;
// if length of spectrogram is less than 1s (100 samples), then return
// basically don't process anything that is less than 1s
// see issue #39: https://github.com/ggerganov/whisper.cpp/issues/39
if (whisper_n_len(ctx) < 100) {
if (whisper_n_len(ctx) < 100 + seek_start) {
return 0;
}
@ -2406,8 +2438,14 @@ int whisper_full(
int progress_prev = 0;
int progress_step = 5;
std::vector<whisper_token_data> tokens_cur;
tokens_cur.reserve(whisper_n_text_ctx(ctx));
std::vector<whisper_token> prompt;
prompt.reserve(whisper_n_text_ctx(ctx));
// main loop
int seek = params.offset_ms/10;
int seek = seek_start;
while (true) {
int progress_cur = (100*seek)/whisper_n_len(ctx);
while (progress_cur >= progress_prev + progress_step) {
@ -2427,9 +2465,8 @@ int whisper_full(
return 7;
}
std::vector<whisper_token> prompt;
int n_past = 0;
prompt.clear();
// if we have already generated some text, use it as a prompt to condition the next generation
if (prompt_past.size() > 0) {

3
whisper.h
View File

@ -72,6 +72,8 @@ extern "C" {
// Returns NULL on failure.
WHISPER_API struct whisper_context * whisper_init(const char * path_model);
WHISPER_API struct whisper_context * whisper_init_parallel(const char * path_model, int n_processors);
// Frees all memory allocated by the model.
WHISPER_API void whisper_free(struct whisper_context * ctx);
@ -170,6 +172,7 @@ extern "C" {
int n_threads;
int offset_ms;
int n_processors;
bool translate;
bool no_context;