参数设置
/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug/bin/main options: -h, --help [default] show this help message and exit -t N, --threads N [4 ] number of threads to use during computation -p N, --processors N [1 ] number of processors to use during computation -ot N, --offset-t N [0 ] time offset in milliseconds -on N, --offset-n N [0 ] segment index offset -d N, --duration N [0 ] duration of audio to process in milliseconds -mc N, --max-context N [-1 ] maximum number of text context tokens to store -ml N, --max-len N [0 ] maximum segment length in characters -sow, --split-on-word [false ] split on word rather than on token -bo N, --best-of N [5 ] number of best candidates to keep -bs N, --beam-size N [5 ] beam size for beam search -wt N, --word-thold N [0.01 ] word timestamp probability threshold -et N, --entropy-thold N [2.40 ] entropy threshold for decoder fail -lpt N, --logprob-thold N [-1.00 ] log probability threshold for decoder fail -debug, --debug-mode [false ] enable debug mode (eg. dump log_mel) -tr, --translate [false ] translate from source language to english -di, --diarize [false ] stereo audio diarization -tdrz, --tinydiarize [false ] enable tinydiarize (requires a tdrz model) -nf, --no-fallback [false ] do not use temperature fallback while decoding -otxt, --output-txt [false ] output result in a text file -ovtt, --output-vtt [false ] output result in a vtt file -osrt, --output-srt [false ] output result in a srt file -olrc, --output-lrc [false ] output result in a lrc file -owts, --output-words [false ] output script for generating karaoke video -fp, --font-path [/System/Library/Fonts/Supplemental/Courier New Bold.ttf] path to a monospace font for karaoke video -ocsv, --output-csv [false ] output result in a CSV file -oj, --output-json [false ] output result in a JSON file -ojf, --output-json-full [false ] include more information in the JSON file -of FNAME, --output-file FNAME [ ] output file path (without file extension) -ps, --print-special [false ] print special tokens -pc, --print-colors [false ] print colors -pp, --print-progress [false ] print progress -nt, --no-timestamps [false ] do not print timestamps -l LANG, --language LANG [en ] spoken language ('auto' for auto-detect) -dl, --detect-language [false ] exit after automatically detecting language --prompt PROMPT [ ] initial prompt -m FNAME, --model FNAME [models/ggml-base.en.bin] model path -f FNAME, --file FNAME [ ] input WAV file path -oved D, --ov-e-device DNAME [CPU ] the OpenVINO device used for encode inference -ls, --log-score [false ] log best decoder scores of tokens -ng, --no-gpu [false ] disable GPU 调试设置
项目依赖和CmakeLists.txt
set(TARGET main) add_executable(${TARGET} main.cpp) include(DefaultTargetOptions) target_link_libraries(${TARGET} PRIVATE common whisper ${CMAKE_THREAD_LIBS_INIT}) #include "common.h" #include "whisper.h" #include <cmath> #include <fstream> #include <cstdio> #include <string> #include <thread> #include <vector> #include <cstring> main
int main(int argc, char ** argv) { // 1.解析参数 whisper_params params; // 解析命令行参数，将结果保存到params中 if (whisper_params_parse(argc, argv, params) == false) {… } // 检查输入文件名是否为空 if (params.fname_inp.empty()) {… }// std::vector<std::string> fname_inp = {}; // 检查语言参数是否有效 if (params.language != "auto" && whisper_lang_id(params.language.c_str()) == -1) {… } // 检查两个布尔参数，如果同时为真，执行相应的错误处理代码 if (params.diarize && params.tinydiarize) {… } // whisper init struct whisper_context_params cparams; cparams.use_gpu = params.use_gpu; // 2.使用whisper初始化上下文，并根据给定的模型文件和参数进行配置 struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams); if (ctx == nullptr) { fprintf(stderr, "error: failed to initialize whisper context\n"); return 3; } // initialize openvino encoder. this has no effect on whisper.cpp builds that don't have OpenVINO configured // 初始化OpenVINO编码器，对于没有配置OpenVINO的whisper.cpp构建，此调用无效 whisper_ctx_init_openvino_encoder(ctx, nullptr, params.openvino_encode_device.c_str(), nullptr); // 3.对输入文件列表进行循环处理 for (int f = 0; f < (int) params.fname_inp.size(); ++f) {… } whisper_print_timings(ctx); // 打印whisper上下文的计时信息 whisper_free(ctx);// 释放whisper上下文占用的资源 return 0; } 1.解析参数
略2.使用whisper初始化上下文，并根据给定的模型文件和参数进行配置
webassembly003 whisper.cpp的main项目-2:根据给定的模型文件和参数进行配置3.对输入文件列表进行循环处理
3.1解析参数
const auto fname_inp = params.fname_inp[f]; // "/home/***/whisper.cpp-1.5.0/samples/jfk.wav" const auto fname_out = f < (int) params.fname_out.size() && !params.fname_out[f].empty() ? params.fname_out[f] : params.fname_inp[f]; // "/home/***/whisper.cpp-1.5.0/samples/jfk.wav" 3.2根据参数读取音频
std::vector<float> pcmf32; // mono-channel 单声道(音频只有一个声道) ,采样点类型为32位浮点数, `PCM` 表示脉冲编码调制 std::vector<std::vector<float>> pcmf32s; // stereo-channel 立体声，即音频有两个声道（左声道和右声道） // read_wav 定义在 common.cpp, 如果在函数调用之前使用::，并且没有指定任何命名空间，那么它会被解释为全局命名空间。 if (!::read_wav(fname_inp, pcmf32, pcmf32s, params.diarize)) { // if (!::read_wav(...))：使用 if 语句检查读取 WAV 文件的结果。! 表示逻辑取反，所以如果 read_wav 返回 false（表示读取失败），则执行下面的代码块。 fprintf(stderr, "error: failed to read WAV file '%s'\n", fname_inp.c_str()); continue; } 3.3print information
// print system information { fprintf(stderr, "\n"); fprintf(stderr, "system_info: n_threads = %d / %d | %s\n", params.n_threads*params.n_processors, 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__); } } if (params.detect_language) { params.language = "auto"; } fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, %d processors, %d beams + best of %d, lang = %s, task = %s, %stimestamps = %d ...\n", __func__, fname_inp.c_str(), int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE, params.n_threads, params.n_processors, params.beam_size, params.best_of, params.language.c_str(), params.translate ? "translate" : "transcribe", params.tinydiarize ? "tdrz = 1, " : "", params.no_timestamps ? 0 : 1); fprintf(stderr, "\n"); } 3.4run the inference
3.4.1解析参数
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY); wparams.strategy = params.beam_size > 1 ? WHISPER_SAMPLING_BEAM_SEARCH : WHISPER_SAMPLING_GREEDY; wparams.print_realtime = false; wparams.print_progress = params.print_progress; wparams.print_timestamps = !params.no_timestamps; wparams.print_special = params.print_special; wparams.translate = params.translate; wparams.language = params.language.c_str(); wparams.detect_language = params.detect_language; wparams.n_threads = params.n_threads; wparams.n_max_text_ctx = params.max_context >= 0 ? params.max_context : wparams.n_max_text_ctx; wparams.offset_ms = params.offset_t_ms; wparams.duration_ms = params.duration_ms; wparams.token_timestamps = params.output_wts || params.output_jsn_full || params.max_len > 0; wparams.thold_pt = params.word_thold; wparams.max_len = params.output_wts && params.max_len == 0 ? 60 : params.max_len; wparams.split_on_word = params.split_on_word; wparams.speed_up = params.speed_up; wparams.debug_mode = params.debug_mode; wparams.tdrz_enable = params.tinydiarize; // [TDRZ] wparams.initial_prompt = params.prompt.c_str(); wparams.greedy.best_of = params.best_of; wparams.beam_search.beam_size = params.beam_size; wparams.temperature_inc = params.no_fallback ? 0.0f : wparams.temperature_inc; wparams.entropy_thold = params.entropy_thold; wparams.logprob_thold = params.logprob_thold; whisper_print_user_data user_data = { ¶ms, &pcmf32s, 0 }; // 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 = &user_data; } if (wparams.print_progress) { wparams.progress_callback = whisper_print_progress_callback; wparams.progress_callback_user_data = &user_data; } whisper_print_segment_callback:获取片段的推理结果并打印的回调函数
void whisper_print_segment_callback(struct whisper_context * ctx, struct whisper_state * /*state*/, int n_new, void * user_data) { const auto & params = *((whisper_print_user_data *) user_data)->params; const auto & pcmf32s = *((whisper_print_user_data *) user_data)->pcmf32s; const int n_segments = whisper_full_n_segments(ctx); std::string speaker = ""; int64_t t0 = 0; int64_t t1 = 0; // print the last n_new segments const int s0 = n_segments - n_new; if (s0 == 0) { printf("\n"); } for (int i = s0; i < n_segments; i++) { if (!params.no_timestamps || params.diarize) { t0 = whisper_full_get_segment_t0(ctx, i); t1 = whisper_full_get_segment_t1(ctx, i); } if (!params.no_timestamps) { printf("[%s --> %s] ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str()); } if (params.diarize && pcmf32s.size() == 2) { speaker = estimate_diarization_speaker(pcmf32s, t0, t1); } if (params.print_colors) { for (int j = 0; j < whisper_full_n_tokens(ctx, i); ++j) { if (params.print_special == 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() - 1, (int) (std::pow(p, 3)*float(k_colors.size())))); printf("%s%s%s%s", speaker.c_str(), k_colors[col].c_str(), text, "\033[0m"); } } else { const char * text = whisper_full_get_segment_text(ctx, i); printf("%s%s", speaker.c_str(), text); } if (params.tinydiarize) { if (whisper_full_get_segment_speaker_turn_next(ctx, i)) { printf("%s", params.tdrz_speaker_turn.c_str()); } } // with timestamps or speakers: each segment on new line if (!params.no_timestamps || params.diarize) { printf("\n"); } fflush(stdout); } } 3.4.2解析参数
// examples for abort mechanism // in examples below, we do not abort the processing, but we could if the flag is set to true // the callback is called before every encoder run - if it returns false, the processing is aborted { static bool is_aborted = false; // NOTE: this should be atomic to avoid data race wparams.encoder_begin_callback = [](struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, void * user_data) { bool is_aborted = *(bool*)user_data; return !is_aborted; }; wparams.encoder_begin_callback_user_data = &is_aborted; } // the callback is called before every computation - if it returns true, the computation is aborted { static bool is_aborted = false; // NOTE: this should be atomic to avoid data race wparams.abort_callback = [](void * user_data) { bool is_aborted = *(bool*)user_data; return is_aborted; }; wparams.abort_callback_user_data = &is_aborted; } 3.4.3 process whisper_full_parallel
if (whisper_full_parallel(ctx, wparams, pcmf32.data(), pcmf32.size(), params.n_processors) != 0) { fprintf(stderr, "%s: failed to process audio\n", argv[0]); return 10; } whisper_full_parallel
int whisper_full_parallel( struct whisper_context * ctx, struct whisper_full_params params, const float * samples, int n_samples, int n_processors) { if (n_processors == 1) { return whisper_full(ctx, params, samples, n_samples); } // 略 } whisper_full
int whisper_full( struct whisper_context * ctx, struct whisper_full_params params, const float * samples, int n_samples) { return whisper_full_with_state(ctx, ctx->state, params, samples, n_samples); } whisper_full_with_state(推理的关键代码800行)
//没细看，有空再看 int whisper_full_with_state( struct whisper_context * ctx, struct whisper_state * state, struct whisper_full_params params, const float * samples, int n_samples) { // clear old results auto & result_all = state->result_all; result_all.clear(); if (n_samples > 0) { // compute log mel spectrogram if (params.speed_up) { // TODO: Replace PV with more advanced algorithm WHISPER_LOG_ERROR("%s: failed to compute log mel spectrogram\n", __func__); return -1; } else { if (whisper_pcm_to_mel_with_state(ctx, state, samples, n_samples, params.n_threads) != 0) { WHISPER_LOG_ERROR("%s: failed to compute log mel spectrogram\n", __func__); return -2; } } } // auto-detect language if not specified if (params.language == nullptr || strlen(params.language) == 0 || strcmp(params.language, "auto") == 0 || params.detect_language) { std::vector<float> probs(whisper_lang_max_id() + 1, 0.0f); const auto lang_id = whisper_lang_auto_detect_with_state(ctx, state, 0, params.n_threads, probs.data()); if (lang_id < 0) { WHISPER_LOG_ERROR("%s: failed to auto-detect language\n", __func__); return -3; } state->lang_id = lang_id; params.language = whisper_lang_str(lang_id); WHISPER_LOG_INFO("%s: auto-detected language: %s (p = %f)\n", __func__, params.language, probs[whisper_lang_id(params.language)]); if (params.detect_language) { return 0; } } if (params.token_timestamps) { state->t_beg = 0; state->t_last = 0; state->tid_last = 0; if (n_samples > 0) { state->energy = get_signal_energy(samples, n_samples, 32); } } const int seek_start = params.offset_ms/10; const int seek_end = params.duration_ms == 0 ? whisper_n_len_from_state(state) : seek_start + params.duration_ms/10; // if length of spectrogram is less than 1.0s (100 frames), then return // basically don't process anything that is less than 1.0s // see issue #39: https://github.com/ggerganov/whisper.cpp/issues/39 if (seek_end < seek_start + (params.speed_up ? 50 : 100)) { return 0; } // a set of temperatures to use // [ t0, t0 + delta, t0 + 2*delta, ..., < 1.0f + 1e-6f ] std::vector<float> temperatures; if (params.temperature_inc > 0.0f) { for (float t = params.temperature; t < 1.0f + 1e-6f; t += params.temperature_inc) { temperatures.push_back(t); } } else { temperatures.push_back(params.temperature); } // initialize the decoders int n_decoders = 1; switch (params.strategy) { case WHISPER_SAMPLING_GREEDY: { n_decoders = params.greedy.best_of; } break; case WHISPER_SAMPLING_BEAM_SEARCH: { n_decoders = std::max(params.greedy.best_of, params.beam_search.beam_size); } break; }; n_decoders = std::max(1, n_decoders); if (n_decoders > WHISPER_MAX_DECODERS) { WHISPER_LOG_ERROR("%s: too many decoders requested (%d), max = %d\n", __func__, n_decoders, WHISPER_MAX_DECODERS); return -4; } // TAGS: WHISPER_DECODER_INIT for (int j = 1; j < n_decoders; j++) { auto & decoder = state->decoders[j]; decoder.sequence.tokens.reserve(state->decoders[0].sequence.tokens.capacity()); decoder.probs.resize (ctx->vocab.n_vocab); decoder.logits.resize (ctx->vocab.n_vocab); decoder.logprobs.resize(ctx->vocab.n_vocab); decoder.logits_id.reserve(ctx->model.hparams.n_vocab); decoder.rng = std::mt19937(0); } // the accumulated text context so far auto & prompt_past = state->prompt_past; if (params.no_context) { prompt_past.clear(); } // prepare prompt { std::vector<whisper_token> prompt_tokens; // initial prompt if (!params.prompt_tokens && params.initial_prompt) { prompt_tokens.resize(1024); prompt_tokens.resize(whisper_tokenize(ctx, params.initial_prompt, prompt_tokens.data(), prompt_tokens.size())); params.prompt_tokens = prompt_tokens.data(); params.prompt_n_tokens = prompt_tokens.size(); } // prepend the prompt tokens to the prompt_past if (params.prompt_tokens && params.prompt_n_tokens > 0) { // parse tokens from the pointer for (int i = 0; i < params.prompt_n_tokens; i++) { prompt_past.push_back(params.prompt_tokens[i]); } std::rotate(prompt_past.begin(), prompt_past.end() - params.prompt_n_tokens, prompt_past.end()); } } // overwrite audio_ctx, max allowed is hparams.n_audio_ctx if (params.audio_ctx > whisper_n_audio_ctx(ctx)) { WHISPER_LOG_ERROR("%s: audio_ctx is larger than the maximum allowed (%d > %d)\n", __func__, params.audio_ctx, whisper_n_audio_ctx(ctx)); return -5; } state->exp_n_audio_ctx = params.audio_ctx; // these tokens determine the task that will be performed std::vector<whisper_token> prompt_init = { whisper_token_sot(ctx), }; if (whisper_is_multilingual(ctx)) { const int lang_id = whisper_lang_id(params.language); state->lang_id = lang_id; prompt_init.push_back(whisper_token_lang(ctx, lang_id)); if (params.translate) { prompt_init.push_back(whisper_token_translate(ctx)); } else { prompt_init.push_back(whisper_token_transcribe(ctx)); } } // distilled models require the "no_timestamps" token { const bool is_distil = ctx->model.hparams.n_text_layer == 2; if (is_distil && !params.no_timestamps) { WHISPER_LOG_WARN("%s: using distilled model - forcing no_timestamps\n", __func__); params.no_timestamps = true; } } if (params.no_timestamps) { prompt_init.push_back(whisper_token_not(ctx)); } int seek = seek_start; std::vector<whisper_token> prompt; prompt.reserve(whisper_n_text_ctx(ctx)); struct beam_candidate { int decoder_idx; int seek_delta; bool has_ts; whisper_sequence sequence; whisper_grammar grammar; }; std::vector<std::vector<beam_candidate>> bc_per_dec(n_decoders); std::vector<beam_candidate> beam_candidates; // main loop while (true) { if (params.progress_callback) { const int progress_cur = (100*(seek - seek_start))/(seek_end - seek_start); params.progress_callback( ctx, ctx->state, progress_cur, params.progress_callback_user_data); } // of only 1 second left, then stop if (seek + 100 >= seek_end) { break; } if (params.encoder_begin_callback) { if (params.encoder_begin_callback(ctx, state, params.encoder_begin_callback_user_data) == false) { WHISPER_LOG_ERROR("%s: encoder_begin_callback returned false - aborting\n", __func__); break; } } // encode audio features starting at offset seek if (!whisper_encode_internal(*ctx, *state, seek, params.n_threads, params.abort_callback, params.abort_callback_user_data)) { WHISPER_LOG_ERROR("%s: failed to encode\n", __func__); return -6; } // if there is a very short audio segment left to process, we remove any past prompt since it tends // to confuse the decoder and often make it repeat or hallucinate stuff if (seek > seek_start && seek + 500 >= seek_end) { prompt_past.clear(); } int best_decoder_id = 0; for (int it = 0; it < (int) temperatures.size(); ++it) { const float t_cur = temperatures[it]; int n_decoders_cur = 1; switch (params.strategy) { case whisper_sampling_strategy::WHISPER_SAMPLING_GREEDY: { if (t_cur > 0.0f) { n_decoders_cur = params.greedy.best_of; } } break; case whisper_sampling_strategy::WHISPER_SAMPLING_BEAM_SEARCH: { if (t_cur > 0.0f) { n_decoders_cur = params.greedy.best_of; } else { n_decoders_cur = params.beam_search.beam_size; } } break; }; n_decoders_cur = std::max(1, n_decoders_cur); WHISPER_PRINT_DEBUG("\n%s: strategy = %d, decoding with %d decoders, temperature = %.2f\n", __func__, params.strategy, n_decoders_cur, t_cur); // TAGS: WHISPER_DECODER_INIT for (int j = 0; j < n_decoders_cur; ++j) { auto & decoder = state->decoders[j]; decoder.sequence.tokens.clear(); decoder.sequence.result_len = 0; decoder.sequence.sum_logprobs_all = 0.0; decoder.sequence.sum_logprobs = -INFINITY; decoder.sequence.avg_logprobs = -INFINITY; decoder.sequence.entropy = 0.0; decoder.sequence.score = -INFINITY; decoder.seek_delta = 100*WHISPER_CHUNK_SIZE; decoder.failed = false; decoder.completed = false; decoder.has_ts = false; if (params.grammar_rules != nullptr) { decoder.grammar = whisper_grammar_init(params.grammar_rules, params.n_grammar_rules, params.i_start_rule); } else { decoder.grammar = {}; } } // init prompt and kv cache for the current iteration // TODO: do not recompute the prompt if it is the same as previous time { prompt.clear(); // if we have already generated some text, use it as a prompt to condition the next generation if (!prompt_past.empty() && t_cur < 0.5f && params.n_max_text_ctx > 0) { int n_take = std::min(std::min(params.n_max_text_ctx, whisper_n_text_ctx(ctx)/2), int(prompt_past.size())); prompt = { whisper_token_prev(ctx) }; prompt.insert(prompt.begin() + 1, prompt_past.end() - n_take, prompt_past.end()); } // init new transcription with sot, language (opt) and task tokens prompt.insert(prompt.end(), prompt_init.begin(), prompt_init.end()); // print the prompt WHISPER_PRINT_DEBUG("\n\n"); for (int i = 0; i < (int) prompt.size(); i++) { WHISPER_PRINT_DEBUG("%s: prompt[%d] = %s\n", __func__, i, ctx->vocab.id_to_token.at(prompt[i]).c_str()); } WHISPER_PRINT_DEBUG("\n\n"); whisper_kv_cache_clear(state->kv_self); whisper_batch_prep_legacy(state->batch, prompt.data(), prompt.size(), 0, 0); if (!whisper_decode_internal(*ctx, *state, state->batch, params.n_threads, params.abort_callback, params.abort_callback_user_data)) { WHISPER_LOG_ERROR("%s: failed to decode\n", __func__); return -7; } { const int64_t t_start_sample_us = ggml_time_us(); state->decoders[0].i_batch = prompt.size() - 1; whisper_process_logits(*ctx, *state, state->decoders[0], params, t_cur); for (int j = 1; j < n_decoders_cur; ++j) { auto & decoder = state->decoders[j]; whisper_kv_cache_seq_cp(state->kv_self, 0, j, -1, -1); memcpy(decoder.probs.data(), state->decoders[0].probs.data(), decoder.probs.size()*sizeof(decoder.probs[0])); memcpy(decoder.logits.data(), state->decoders[0].logits.data(), decoder.logits.size()*sizeof(decoder.logits[0])); memcpy(decoder.logprobs.data(), state->decoders[0].logprobs.data(), decoder.logprobs.size()*sizeof(decoder.logprobs[0])); } state->t_sample_us += ggml_time_us() - t_start_sample_us; } } for (int i = 0, n_max = whisper_n_text_ctx(ctx)/2 - 4; i < n_max; ++i) { const int64_t t_start_sample_us = ggml_time_us(); if (params.strategy == whisper_sampling_strategy::WHISPER_SAMPLING_BEAM_SEARCH) { for (auto & bc : bc_per_dec) { bc.clear(); } } // sampling // TODO: avoid memory allocations, optimize, avoid threads? { std::atomic<int> j_cur(0); auto process = [&]() { while (true) { const int j = j_cur.fetch_add(1); if (j >= n_decoders_cur) { break; } auto & decoder = state->decoders[j]; if (decoder.completed || decoder.failed) { continue; } switch (params.strategy) { case whisper_sampling_strategy::WHISPER_SAMPLING_GREEDY: { if (t_cur < 1e-6f) { decoder.sequence.tokens.push_back(whisper_sample_token(*ctx, decoder, true)); } else { decoder.sequence.tokens.push_back(whisper_sample_token(*ctx, decoder, false)); } decoder.sequence.sum_logprobs_all += decoder.sequence.tokens.back().plog; } break; case whisper_sampling_strategy::WHISPER_SAMPLING_BEAM_SEARCH: { const auto tokens_new = whisper_sample_token_topk(*ctx, decoder, params.beam_search.beam_size); for (const auto & token : tokens_new) { bc_per_dec[j].push_back({ j, decoder.seek_delta, decoder.has_ts, decoder.sequence, decoder.grammar, }); bc_per_dec[j].back().sequence.tokens.push_back(token); bc_per_dec[j].back().sequence.sum_logprobs_all += token.plog; } } break; }; } }; const int n_threads = std::min(params.n_threads, n_decoders_cur); if (n_threads == 1) { process(); } else { std::vector<std::thread> threads(n_threads - 1); for (int t = 0; t < n_threads - 1; ++t) { threads[t] = std::thread(process); } process(); for (int t = 0; t < n_threads - 1; ++t) { threads[t].join(); } } } beam_candidates.clear(); for (const auto & bc : bc_per_dec) { beam_candidates.insert(beam_candidates.end(), bc.begin(), bc.end()); if (!bc.empty()) { state->n_sample += 1; } } // for beam-search, choose the top candidates and update the KV caches if (params.strategy == whisper_sampling_strategy::WHISPER_SAMPLING_BEAM_SEARCH) { std::sort( beam_candidates.begin(), beam_candidates.end(), [](const beam_candidate & a, const beam_candidate & b) { return a.sequence.sum_logprobs_all > b.sequence.sum_logprobs_all; }); uint32_t cur_c = 0; for (int j = 0; j < n_decoders_cur; ++j) { auto & decoder = state->decoders[j]; if (decoder.completed || decoder.failed) { continue; } if (cur_c >= beam_candidates.size()) { cur_c = 0; } auto & cur = beam_candidates[cur_c++]; while (beam_candidates.size() > cur_c && beam_candidates[cur_c].sequence.sum_logprobs_all == cur.sequence.sum_logprobs_all && i > 0) { ++cur_c; } decoder.seek_delta = cur.seek_delta; decoder.has_ts = cur.has_ts; decoder.sequence = cur.sequence; decoder.grammar = cur.grammar; whisper_kv_cache_seq_cp(state->kv_self, cur.decoder_idx, WHISPER_MAX_DECODERS + j, -1, -1); WHISPER_PRINT_DEBUG("%s: beam search: decoder %d: from decoder %d: token = %10s, plog = %8.5f, sum_logprobs = %8.5f\n", __func__, j, cur.decoder_idx, ctx->vocab.id_to_token.at(decoder.sequence.tokens.back().id).c_str(), decoder.sequence.tokens.back().plog, decoder.sequence.sum_logprobs_all); } for (int j = 0; j < n_decoders_cur; ++j) { auto & decoder = state->decoders[j]; if (decoder.completed || decoder.failed) { continue; } whisper_kv_cache_seq_rm(state->kv_self, j, -1, -1); whisper_kv_cache_seq_cp(state->kv_self, WHISPER_MAX_DECODERS + j, j, -1, -1); whisper_kv_cache_seq_rm(state->kv_self, WHISPER_MAX_DECODERS + j, -1, -1); } } // update the decoder state // - check if the sequence is completed // - check if the sequence is failed // - update sliding window based on timestamp tokens for (int j = 0; j < n_decoders_cur; ++j) { auto & decoder = state->decoders[j]; if (decoder.completed || decoder.failed) { continue; } auto & has_ts = decoder.has_ts; auto & failed = decoder.failed; auto & completed = decoder.completed; auto & seek_delta = decoder.seek_delta; auto & result_len = decoder.sequence.result_len; { const auto & token = decoder.sequence.tokens.back(); // timestamp token - update sliding window if (token.id > whisper_token_beg(ctx)) { const int seek_delta_new = 2*(token.id - whisper_token_beg(ctx)); // do not allow to go back in time if (has_ts && seek_delta > seek_delta_new && result_len < i) { failed = true; // TODO: maybe this is not a failure ? continue; } seek_delta = seek_delta_new; result_len = i + 1; has_ts = true; } whisper_grammar_accept_token(*ctx, decoder.grammar, token.id); #ifdef WHISPER_DEBUG { const auto tt = token.pt > 0.10 ? ctx->vocab.id_to_token.at(token.tid) : "[?]"; WHISPER_PRINT_DEBUG("%s: id = %3d, decoder = %d, token = %6d, p = %6.3f, ts = %10s, %6.3f, result_len = %4d '%s'\n", __func__, i, j, token.id, token.p, tt.c_str(), token.pt, result_len, ctx->vocab.id_to_token.at(token.id).c_str()); } #endif // end of segment if (token.id == whisper_token_eot(ctx) || // end of text token (params.max_tokens > 0 && i >= params.max_tokens) || // max tokens per segment reached (has_ts && seek + seek_delta + 100 >= seek_end) // end of audio reached ) { if (result_len == 0) { if (seek + seek_delta + 100 >= seek_end) { result_len = i + 1; } else { failed = true; continue; } } if (params.single_segment) { result_len = i + 1; seek_delta = 100*WHISPER_CHUNK_SIZE; } completed = true; continue; } // TESTS: if no tensors are loaded, it means we are running tests if (ctx->model.n_loaded == 0) { seek_delta = 100*WHISPER_CHUNK_SIZE; completed = true; continue; } } // sometimes, the decoding can get stuck in a repetition loop // this is an attempt to mitigate such cases - we flag the decoding as failed and use a fallback strategy if (i == n_max - 1 && (result_len == 0 || seek_delta < 100*WHISPER_CHUNK_SIZE/2)) { failed = true; continue; } } // check if all decoders have finished (i.e. completed or failed) { bool completed_all = true; for (int j = 0; j < n_decoders_cur; ++j) { auto & decoder = state->decoders[j]; if (decoder.completed || decoder.failed) { continue; } completed_all = false; } if (completed_all) { break; } } state->t_sample_us += ggml_time_us() - t_start_sample_us; // obtain logits for the next token { auto & batch = state->batch; batch.n_tokens = 0; const int n_past = prompt.size() + i; for (int j = 0; j < n_decoders_cur; ++j) { auto & decoder = state->decoders[j]; if (decoder.failed || decoder.completed) { continue; } //WHISPER_PRINT_DEBUG("%s: decoder %d: token %d, seek_delta %d\n", __func__, j, decoder.sequence.tokens.back().id, decoder.seek_delta); decoder.i_batch = batch.n_tokens; batch.token [batch.n_tokens] = decoder.sequence.tokens.back().id; batch.pos [batch.n_tokens] = n_past; batch.n_seq_id[batch.n_tokens] = 1; batch.seq_id [batch.n_tokens][0] = j; batch.logits [batch.n_tokens] = 1; batch.n_tokens++; } assert(batch.n_tokens > 0); if (!whisper_decode_internal(*ctx, *state, state->batch, params.n_threads, params.abort_callback, params.abort_callback_user_data)) { WHISPER_LOG_ERROR("%s: failed to decode\n", __func__); return -8; } const int64_t t_start_sample_us = ggml_time_us(); // TODO: avoid memory allocations, optimize, avoid threads? { std::atomic<int> j_cur(0); auto process = [&]() { while (true) { const int j = j_cur.fetch_add(1); if (j >= n_decoders_cur) { break; } auto & decoder = state->decoders[j]; if (decoder.failed || decoder.completed) { continue; } whisper_process_logits(*ctx, *state, decoder, params, t_cur); } }; const int n_threads = std::min(params.n_threads, n_decoders_cur); if (n_threads == 1) { process(); } else { std::vector<std::thread> threads(n_threads - 1); for (int t = 0; t < n_threads - 1; ++t) { threads[t] = std::thread(process); } process(); for (int t = 0; t < n_threads - 1; ++t) { threads[t].join(); } } } state->t_sample_us += ggml_time_us() - t_start_sample_us; } } // rank the resulting sequences and select the best one { double best_score = -INFINITY; for (int j = 0; j < n_decoders_cur; ++j) { auto & decoder = state->decoders[j]; if (decoder.failed) { continue; } decoder.sequence.tokens.resize(decoder.sequence.result_len); whisper_sequence_score(params, decoder.sequence); WHISPER_PRINT_DEBUG("%s: decoder %2d: score = %8.5f, result_len = %3d, avg_logprobs = %8.5f, entropy = %8.5f\n", __func__, j, decoder.sequence.score, decoder.sequence.result_len, decoder.sequence.avg_logprobs, decoder.sequence.entropy); if (decoder.sequence.result_len > 32 && decoder.sequence.entropy < params.entropy_thold) { WHISPER_PRINT_DEBUG("%s: decoder %2d: failed due to entropy %8.5f < %8.5f\n", __func__, j, decoder.sequence.entropy, params.entropy_thold); decoder.failed = true; state->n_fail_h++; continue; } if (best_score < decoder.sequence.score) { best_score = decoder.sequence.score; best_decoder_id = j; } } WHISPER_PRINT_DEBUG("%s: best decoder = %d\n", __func__, best_decoder_id); } // was the decoding successful for the current temperature? // do fallback only if: // - we are not at the last temperature // - we are not at the end of the audio (3 sec) if (it != (int) temperatures.size() - 1 && seek_end - seek > 10*WHISPER_CHUNK_SIZE) { bool success = true; const auto & decoder = state->decoders[best_decoder_id]; if (decoder.failed || decoder.sequence.avg_logprobs < params.logprob_thold) { success = false; state->n_fail_p++; } if (success) { //for (auto & token : ctx->decoders[best_decoder_id].sequence.tokens) { // WHISPER_PRINT_DEBUG("%s: token = %d, p = %6.3f, pt = %6.3f, ts = %s, str = %s\n", __func__, token.id, token.p, token.pt, ctx->vocab.id_to_token.at(token.tid).c_str(), ctx->vocab.id_to_token.at(token.id).c_str()); //} break; } } WHISPER_PRINT_DEBUG("\n%s: failed to decode with temperature = %.2f\n", __func__, t_cur); } // output results through a user-provided callback { const auto & best_decoder = state->decoders[best_decoder_id]; const auto seek_delta = best_decoder.seek_delta; const auto result_len = best_decoder.sequence.result_len; const auto & tokens_cur = best_decoder.sequence.tokens; //WHISPER_PRINT_DEBUG("prompt_init.size() = %d, prompt.size() = %d, result_len = %d, seek_delta = %d\n", prompt_init.size(), prompt.size(), result_len, seek_delta); // update prompt_past prompt_past.clear(); if (prompt.front() == whisper_token_prev(ctx)) { prompt_past.insert(prompt_past.end(), prompt.begin() + 1, prompt.end() - prompt_init.size()); } for (int i = 0; i < result_len; ++i) { prompt_past.push_back(tokens_cur[i].id); } if (!tokens_cur.empty() && ctx->model.n_loaded > 0) { int i0 = 0; auto t0 = seek + 2*(tokens_cur.front().tid - whisper_token_beg(ctx)); std::string text; bool speaker_turn_next = false; for (int i = 0; i < (int) tokens_cur.size(); i++) { //printf("%s: %18s %6.3f %18s %6.3f\n", __func__, // ctx->vocab.id_to_token[tokens_cur[i].id].c_str(), tokens_cur[i].p, // ctx->vocab.id_to_token[tokens_cur[i].tid].c_str(), tokens_cur[i].pt); if (params.print_special || tokens_cur[i].id < whisper_token_eot(ctx)) { text += whisper_token_to_str(ctx, tokens_cur[i].id); } // [TDRZ] record if speaker turn was predicted after current segment if (params.tdrz_enable && tokens_cur[i].id == whisper_token_solm(ctx)) { speaker_turn_next = true; } if (tokens_cur[i].id > whisper_token_beg(ctx) && !params.single_segment) { const auto t1 = seek + 2*(tokens_cur[i].tid - whisper_token_beg(ctx)); if (!text.empty()) { const auto tt0 = params.speed_up ? 2*t0 : t0; const auto tt1 = params.speed_up ? 2*t1 : t1; if (params.print_realtime) { if (params.print_timestamps) { printf("[%s --> %s] %s\n", to_timestamp(tt0).c_str(), to_timestamp(tt1).c_str(), text.c_str()); } else { printf("%s", text.c_str()); fflush(stdout); } } //printf("tt0 = %d, tt1 = %d, text = %s, token = %s, token_id = %d, tid = %d\n", tt0, tt1, text.c_str(), ctx->vocab.id_to_token[tokens_cur[i].id].c_str(), tokens_cur[i].id, tokens_cur[i].tid); result_all.push_back({ tt0, tt1, text, {}, speaker_turn_next }); for (int j = i0; j <= i; j++) { result_all.back().tokens.push_back(tokens_cur[j]); } int n_new = 1; if (params.token_timestamps) { whisper_exp_compute_token_level_timestamps( *ctx, *state, result_all.size() - 1, params.thold_pt, params.thold_ptsum); if (params.max_len > 0) { n_new = whisper_wrap_segment(*ctx, *state, params.max_len, params.split_on_word); } } if (params.new_segment_callback) { params.new_segment_callback(ctx, state, n_new, params.new_segment_callback_user_data); } } text = ""; while (i < (int) tokens_cur.size() && tokens_cur[i].id > whisper_token_beg(ctx)) { i++; } i--; t0 = t1; i0 = i + 1; speaker_turn_next = false; } } if (!text.empty()) { const auto t1 = seek + seek_delta; const auto tt0 = params.speed_up ? 2*t0 : t0; const auto tt1 = params.speed_up ? 2*t1 : t1; if (params.print_realtime) { if (params.print_timestamps) { printf("[%s --> %s] %s\n", to_timestamp(tt0).c_str(), to_timestamp(tt1).c_str(), text.c_str()); } else { printf("%s", text.c_str()); fflush(stdout); } } result_all.push_back({ tt0, tt1, text, {} , speaker_turn_next }); for (int j = i0; j < (int) tokens_cur.size(); j++) { result_all.back().tokens.push_back(tokens_cur[j]); } int n_new = 1; if (params.token_timestamps) { whisper_exp_compute_token_level_timestamps( *ctx, *state, result_all.size() - 1, params.thold_pt, params.thold_ptsum); if (params.max_len > 0) { n_new = whisper_wrap_segment(*ctx, *state, params.max_len, params.split_on_word); } } if (params.new_segment_callback) { params.new_segment_callback(ctx, state, n_new, params.new_segment_callback_user_data); } } } // update audio window seek += seek_delta; WHISPER_PRINT_DEBUG("seek = %d, seek_delta = %d\n", seek, seek_delta); } } return 0; } 3.5output stuff
// output stuff { printf("\n"); // output to text file if (params.output_txt) { const auto fname_txt = fname_out + ".txt"; output_txt(ctx, fname_txt.c_str(), params, pcmf32s); } // output to VTT file if (params.output_vtt) { const auto fname_vtt = fname_out + ".vtt"; output_vtt(ctx, fname_vtt.c_str(), params, pcmf32s); } // output to SRT file if (params.output_srt) { const auto fname_srt = fname_out + ".srt"; output_srt(ctx, fname_srt.c_str(), params, pcmf32s); } // output to WTS file if (params.output_wts) { const auto fname_wts = fname_out + ".wts"; output_wts(ctx, fname_wts.c_str(), fname_inp.c_str(), params, float(pcmf32.size() + 1000)/WHISPER_SAMPLE_RATE, pcmf32s); } // output to CSV file if (params.output_csv) { const auto fname_csv = fname_out + ".csv"; output_csv(ctx, fname_csv.c_str(), params, pcmf32s); } // output to JSON file if (params.output_jsn) { const auto fname_jsn = fname_out + ".json"; output_json(ctx, fname_jsn.c_str(), params, pcmf32s, params.output_jsn_full); } // output to LRC file if (params.output_lrc) { const auto fname_lrc = fname_out + ".lrc"; output_lrc(ctx, fname_lrc.c_str(), params, pcmf32s); } // output to score file if (params.log_score) { const auto fname_score = fname_out + ".score.txt"; output_score(ctx, fname_score.c_str(), params, pcmf32s); } } stream
stream的依赖
if (WHISPER_SDL2) # 需要set(WHISPER_SDL2 ON)#option(WHISPER_SDL2 "whisper: support for libSDL2" OFF) # stream set(TARGET stream) add_executable(${TARGET} stream.cpp) include(DefaultTargetOptions) target_link_libraries(${TARGET} PRIVATE common common-sdl whisper ${CMAKE_THREAD_LIBS_INIT}) endif () // Real-time speech recognition of input from a microphone // // A very quick-n-dirty implementation serving mainly as a proof of concept. // #include "common-sdl.h" // https://github1s.com/ggerganov/whisper.cpp/blob/d6b9be21d76b91a96bb987063b25e5b532140253/examples/common-sdl.h #include "common.h" #include "whisper.h" #include <cassert> #include <cstdio> #include <string> #include <thread> #include <vector> #include <fstream> [ 66%] Linking CXX static library libcommon.a gmake[2]: 离开目录“/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug” [ 66%] Built target common gmake[2]: 进入目录“/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug” gmake[2]: 进入目录“/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug” gmake[2]: 进入目录“/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug” Scanning dependencies of target stream gmake[2]: 离开目录“/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug” gmake[2]: 离开目录“/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug” gmake[2]: 进入目录“/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug” gmake[2]: 进入目录“/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug” gmake[2]: 离开目录“/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug” [ 72%] Building CXX object examples/main/CMakeFiles/main.dir/main.cpp.o gmake[2]: 进入目录“/home/pdd/le/whisper.cpp-1.5.0/cmake-build-debug” [ 77%] Building CXX object examples/quantize/CMakeFiles/quantize.dir/quantize.cpp.o [ 83%] Building CXX object examples/stream/CMakeFiles/stream.dir/stream.cpp.o In file included from /home/pdd/le/whisper.cpp-1.5.0/examples/stream/stream.cpp:5: /home/pdd/le/whisper.cpp-1.5.0/examples/common-sdl.h:3:10: fatal error: SDL.h: 没有那个文件或目录 3 | #include <SDL.h> | ^~~~~~~ compilation terminated. SDL安装
反正安装失败了，跟系统版本有关，各种依赖处理有点麻烦。
(base) pdd@pdd-Dell-G15-5511:~/le$ sudo apt install libsdl2-dev [sudo] pdd 的密码： 正在读取软件包列表... 完成 正在分析软件包的依赖关系树... 完成 正在读取状态信息... 完成 有一些软件包无法被安装。如果您用的是 unstable 发行版，这也许是 因为系统无法达到您要求的状态造成的。该版本中可能会有一些您需要的软件 包尚未被创建或是它们已被从新到(Incoming)目录移出。 下列信息可能会对解决问题有所帮助： 下列软件包有未满足的依赖关系： udev : 破坏: systemd (< 249.11-0ubuntu3.11) 破坏: systemd:i386 (< 249.11-0ubuntu3.11) 推荐: systemd-hwe-hwdb 但是它将不会被安装 E: 错误，pkgProblemResolver::Resolve 发生故障，这可能是有软件包被要求保持现状的缘故。 (base) pdd@pdd-Dell-G15-5511:~/le$ sudo apt-get install libsdl2-dev 正在读取软件包列表... 完成 正在分析软件包的依赖关系树... 完成 正在读取状态信息... 完成 有一些软件包无法被安装。如果您用的是 unstable 发行版，这也许是 因为系统无法达到您要求的状态造成的。该版本中可能会有一些您需要的软件 包尚未被创建或是它们已被从新到(Incoming)目录移出。 下列信息可能会对解决问题有所帮助： 下列软件包有未满足的依赖关系： udev : 破坏: systemd (< 249.11-0ubuntu3.11) 破坏: systemd:i386 (< 249.11-0ubuntu3.11) 推荐: systemd-hwe-hwdb 但是它将不会被安装 E: 错误，pkgProblemResolver::Resolve 发生故障，这可能是有软件包被要求保持现状的缘故。 (base) pdd@pdd-Dell-G15-5511:~/le$ sudo apt-get install libsdl2-2.0-0 正在读取软件包列表... 完成 正在分析软件包的依赖关系树... 完成 正在读取状态信息... 完成 下列软件包是自动安装的并且现在不需要了： fcitx-config-common fcitx-config-gtk fcitx-frontend-all fcitx-frontend-gtk2 fcitx-frontend-gtk3 fcitx-frontend-qt5 fcitx-module-dbus fcitx-module-kimpanel fcitx-module-lua fcitx-module-quickphrase-editor5 fcitx-module-x11 fcitx-modules fcitx-ui-classic g++-11 gir1.2-appindicator3-0.1 gir1.2-gst-plugins-base-1.0 gir1.2-gstreamer-1.0 gir1.2-keybinder-3.0 gir1.2-wnck-3.0 gnome-session-canberra libfcitx-config4 libfcitx-core0 libfcitx-gclient1 libfcitx-qt5-1 libfcitx-qt5-data libfcitx-utils0 libgettextpo0 libkeybinder-3.0-0 libpresage-data libpresage1v5 libtinyxml2.6.2v5 libwnck-3-0 libwnck-3-common presage python3-gi-cairo 使用'sudo apt autoremove'来卸载它(它们)。 将会同时安装下列软件： libsndio6.1 建议安装： sndiod 下列【新】软件包将被安装： libsdl2-2.0-0 libsndio6.1 升级了 0 个软件包，新安装了 2 个软件包，要卸载 0 个软件包，有 28 个软件包未被升级。 需要下载 366 kB 的归档。 解压缩后会消耗 1,227 kB 的额外空间。 您希望继续执行吗？ [Y/n] y 获取:1 http://dk.archive.ubuntu.com/ubuntu xenial/universe amd64 libsndio6.1 amd64 1.1.0-2 [23.2 kB] 获取:2 http://dk.archive.ubuntu.com/ubuntu xenial/universe amd64 libsdl2-2.0-0 amd64 2.0.4+dfsg1-2ubuntu2 [343 kB] 已下载 366 kB，耗时 4秒 (99.5 kB/s) 正在选中未选择的软件包 libsndio6.1:amd64。 (正在读取数据库 ... 系统当前共安装有 285392 个文件和目录。) 准备解压 .../libsndio6.1_1.1.0-2_amd64.deb ... 正在解压 libsndio6.1:amd64 (1.1.0-2) ... 正在选中未选择的软件包 libsdl2-2.0-0:amd64。 准备解压 .../libsdl2-2.0-0_2.0.4+dfsg1-2ubuntu2_amd64.deb ... 正在解压 libsdl2-2.0-0:amd64 (2.0.4+dfsg1-2ubuntu2) ... 正在设置 libsndio6.1:amd64 (1.1.0-2) ... 正在设置 libsdl2-2.0-0:amd64 (2.0.4+dfsg1-2ubuntu2) ... 正在处理用于 libc-bin (2.35-0ubuntu3.1) 的触发器 ... /sbin/ldconfig.real: /usr/local/cuda-11.4/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8 is not a symbolic link $ sudo aptitude install libsdl2-dev 下列“新”软件包将被安装。 libsdl2-dev{b} libsndio-dev{a} 下列软件包将被“删除”： fcitx-config-common{u} fcitx-config-gtk{u} fcitx-frontend-all{u} fcitx-frontend-gtk2{u} fcitx-frontend-gtk3{u} fcitx-frontend-qt5{u} fcitx-module-dbus{u} fcitx-module-kimpanel{u} fcitx-module-lua{u} fcitx-module-quickphrase-editor5{u} fcitx-module-x11{u} fcitx-modules{u} fcitx-ui-classic{u} g++-11{u} gir1.2-appindicator3-0.1{u} gir1.2-gst-plugins-base-1.0{u} gir1.2-gstreamer-1.0{u} gir1.2-keybinder-3.0{u} gir1.2-wnck-3.0{u} gnome-session-canberra{u} libfcitx-config4{u} libfcitx-core0{u} libfcitx-gclient1{u} libfcitx-qt5-1{u} libfcitx-qt5-data{u} libfcitx-utils0{u} libgettextpo0{u} libkeybinder-3.0-0{u} libpresage-data{u} libpresage1v5{u} libtinyxml2.6.2v5{u} libwnck-3-0{u} libwnck-3-common{u} presage{u} python3-gi-cairo{u} 0 个软件包被升级，新安装 2 个，35 个将被删除， 同时 28 个将不升级。 需要获取 627 kB 的存档。解包后将释放 49.2 MB。 下列软件包存在未满足的依赖关系： libsdl2-dev : 依赖: libasound2-dev 但它是不可安装的 依赖: libdbus-1-dev 但它是不可安装的 依赖: libgles2-mesa-dev 但它是不可安装的 依赖: libmirclient-dev 但它是不可安装的 依赖: libpulse-dev 但它是不可安装的 依赖: libudev-dev 但它是不可安装的 依赖: libxkbcommon-dev 但它是不可安装的 依赖: libxss-dev 但它是不可安装的 依赖: libxv-dev 但它是不可安装的 依赖: libxxf86vm-dev 但它是不可安装的 下列动作将解决这些依赖关系： 保持 下列软件包于其当前版本： 1) libsdl2-dev [未安装的] 是否接受该解决方案？[Y/n/q/?] y 下列软件包将被“删除”： fcitx-config-common{u} fcitx-config-gtk{u} fcitx-frontend-all{u} fcitx-frontend-gtk2{u} fcitx-frontend-gtk3{u} fcitx-frontend-qt5{u} fcitx-module-dbus{u} fcitx-module-kimpanel{u} fcitx-module-lua{u} fcitx-module-quickphrase-editor5{u} fcitx-module-x11{u} fcitx-modules{u} fcitx-ui-classic{u} g++-11{u} gir1.2-appindicator3-0.1{u} gir1.2-gst-plugins-base-1.0{u} gir1.2-gstreamer-1.0{u} gir1.2-keybinder-3.0{u} gir1.2-wnck-3.0{u} gnome-session-canberra{u} libfcitx-config4{u} libfcitx-core0{u} libfcitx-gclient1{u} libfcitx-qt5-1{u} libfcitx-qt5-data{u} libfcitx-utils0{u} libgettextpo0{u} libkeybinder-3.0-0{u} libpresage-data{u} libpresage1v5{u} libtinyxml2.6.2v5{u} libwnck-3-0{u} libwnck-3-common{u} presage{u} python3-gi-cairo{u} 0 个软件包被升级，新安装 0 个，35 个将被删除， 同时 28 个将不升级。 需要获取 0 B 的存档。解包后将释放 53.1 MB。 您要继续吗？[Y/n/?] y (正在读取数据库 ... 系统当前共安装有 285406 个文件和目录。) 正在卸载 fcitx-config-gtk (0.4.10-3) ... 正在卸载 fcitx-config-common (0.4.10-3) ... 正在卸载 fcitx-frontend-all (1:4.2.9.8-5) ... 正在卸载 fcitx-frontend-gtk2 (1:4.2.9.8-5) ... 正在卸载 fcitx-frontend-gtk3 (1:4.2.9.8-5) ... 正在卸载 fcitx-frontend-qt5:amd64 (1.2.7-1.2build1) ... 正在卸载 fcitx-module-kimpanel (1:4.2.9.8-5) ... 正在卸载 fcitx-module-dbus (1:4.2.9.8-5) ... 正在卸载 fcitx-module-lua (1:4.2.9.8-5) ... 正在卸载 fcitx-module-quickphrase-editor5:amd64 (1.2.7-1.2build1) ... 正在卸载 fcitx-ui-classic (1:4.2.9.8-5) ... 正在卸载 fcitx-module-x11 (1:4.2.9.8-5) ... 正在卸载 fcitx-modules (1:4.2.9.8-5) ... 正在卸载 g++-11 (11.3.0-1ubuntu1~22.04) ... 正在卸载 gir1.2-appindicator3-0.1 (12.10.1+20.10.20200706.1-0ubuntu1) ... 正在卸载 gir1.2-gst-plugins-base-1.0:amd64 (1.20.1-1) ... 正在卸载 gir1.2-gstreamer-1.0:amd64 (1.20.3-0ubuntu1) ... 正在卸载 gir1.2-keybinder-3.0 (0.3.2-1.1) ... 正在卸载 gir1.2-wnck-3.0:amd64 (40.1-1) ... 正在卸载 gnome-session-canberra (0.30-10ubuntu1) ... 正在卸载 libfcitx-qt5-1:amd64 (1.2.7-1.2build1) ... 正在卸载 libfcitx-core0:amd64 (1:4.2.9.8-5) ... 正在卸载 libfcitx-config4:amd64 (1:4.2.9.8-5) ... 正在卸载 libfcitx-gclient1:amd64 (1:4.2.9.8-5) ... 正在卸载 libfcitx-qt5-data (1.2.7-1.2build1) ... 正在卸载 libfcitx-utils0:amd64 (1:4.2.9.8-5) ... 正在卸载 libgettextpo0:amd64 (0.21-4ubuntu4) ... 正在卸载 libkeybinder-3.0-0:amd64 (0.3.2-1.1) ... 正在卸载 presage (0.9.1-2.2ubuntu1) ... 正在卸载 libpresage1v5:amd64 (0.9.1-2.2ubuntu1) ... 正在卸载 libpresage-data (0.9.1-2.2ubuntu1) ... 正在卸载 libtinyxml2.6.2v5:amd64 (2.6.2-6) ... 正在卸载 libwnck-3-0:amd64 (40.1-1) ... 正在卸载 libwnck-3-common (40.1-1) ... 正在卸载 python3-gi-cairo (3.42.1-0ubuntu1) ... 正在处理用于 mate-menus (1.26.0-2ubuntu2) 的触发器 ... 正在处理用于 libgtk-3-0:amd64 (3.24.33-1ubuntu2) 的触发器 ... 正在处理用于 libgtk2.0-0:amd64 (2.24.33-2ubuntu2) 的触发器 ... 正在处理用于 libc-bin (2.35-0ubuntu3.1) 的触发器 ... /sbin/ldconfig.real: /usr/local/cuda-11.4/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8 is not a symbolic link 正在处理用于 man-db (2.10.2-1) 的触发器 ... 正在处理用于 mailcap (3.70+nmu1ubuntu1) 的触发器 ... 正在处理用于 desktop-file-utils (0.26-1ubuntu3) 的触发器 ... 编译安装 https://wiki.libsdl.org/SDL2/Installation
make
git clone https://github.com/libsdl-org/SDL.git -b SDL2 cd SDL mkdir build cd build ../configure make sudo make install cmake
git clone https://github.com/libsdl-org/SDL cd SDL mkdir build cd build cmake .. -DCMAKE_BUILD_TYPE=Release cmake --build . --config Release --parallel #CMake >= 3.15 sudo cmake --install . --config Release #CMake <= 3.14 sudo make install ~/mysdl/SDL2-2.28.5/build$ sudo cmake --install . --config Release [sudo] pdd 的密码： -- Installing: /usr/local/lib/libSDL2-2.0.so.0.2800.5 -- Installing: /usr/local/lib/libSDL2-2.0.so.0 -- Installing: /usr/local/lib/libSDL2-2.0.so -- Installing: /usr/local/lib/libSDL2main.a -- Installing: /usr/local/lib/libSDL2.a -- Installing: /usr/local/lib/libSDL2_test.a -- Installing: /usr/local/lib/cmake/SDL2/SDL2Targets.cmake -- Installing: /usr/local/lib/cmake/SDL2/SDL2Targets-release.cmake -- Installing: /usr/local/lib/cmake/SDL2/SDL2mainTargets.cmake -- Installing: /usr/local/lib/cmake/SDL2/SDL2mainTargets-release.cmake -- Installing: /usr/local/lib/cmake/SDL2/SDL2staticTargets.cmake -- Installing: /usr/local/lib/cmake/SDL2/SDL2staticTargets-release.cmake -- Installing: /usr/local/lib/cmake/SDL2/SDL2testTargets.cmake -- Installing: /usr/local/lib/cmake/SDL2/SDL2testTargets-release.cmake -- Installing: /usr/local/lib/cmake/SDL2/SDL2Config.cmake -- Installing: /usr/local/lib/cmake/SDL2/SDL2ConfigVersion.cmake -- Installing: /usr/local/lib/cmake/SDL2/sdlfind.cmake -- Installing: /usr/local/include/SDL2/SDL.h -- Installing: /usr/local/include/SDL2/SDL_assert.h -- Installing: /usr/local/include/SDL2/SDL_atomic.h -- Installing: /usr/local/include/SDL2/SDL_audio.h -- Installing: /usr/local/include/SDL2/SDL_bits.h -- Installing: /usr/local/include/SDL2/SDL_blendmode.h -- Installing: /usr/local/include/SDL2/SDL_clipboard.h -- Installing: /usr/local/include/SDL2/SDL_copying.h -- Installing: /usr/local/include/SDL2/SDL_cpuinfo.h -- Installing: /usr/local/include/SDL2/SDL_egl.h -- Installing: /usr/local/include/SDL2/SDL_endian.h -- Installing: /usr/local/include/SDL2/SDL_error.h -- Installing: /usr/local/include/SDL2/SDL_events.h -- Installing: /usr/local/include/SDL2/SDL_filesystem.h -- Installing: /usr/local/include/SDL2/SDL_gamecontroller.h -- Installing: /usr/local/include/SDL2/SDL_gesture.h -- Installing: /usr/local/include/SDL2/SDL_guid.h -- Installing: /usr/local/include/SDL2/SDL_haptic.h -- Installing: /usr/local/include/SDL2/SDL_hidapi.h -- Installing: /usr/local/include/SDL2/SDL_hints.h -- Installing: /usr/local/include/SDL2/SDL_joystick.h -- Installing: /usr/local/include/SDL2/SDL_keyboard.h -- Installing: /usr/local/include/SDL2/SDL_keycode.h -- Installing: /usr/local/include/SDL2/SDL_loadso.h -- Installing: /usr/local/include/SDL2/SDL_locale.h -- Installing: /usr/local/include/SDL2/SDL_log.h -- Installing: /usr/local/include/SDL2/SDL_main.h -- Installing: /usr/local/include/SDL2/SDL_messagebox.h -- Installing: /usr/local/include/SDL2/SDL_metal.h -- Installing: /usr/local/include/SDL2/SDL_misc.h -- Installing: /usr/local/include/SDL2/SDL_mouse.h -- Installing: /usr/local/include/SDL2/SDL_mutex.h -- Installing: /usr/local/include/SDL2/SDL_name.h -- Installing: /usr/local/include/SDL2/SDL_opengl.h -- Installing: /usr/local/include/SDL2/SDL_opengl_glext.h -- Installing: /usr/local/include/SDL2/SDL_opengles.h -- Installing: /usr/local/include/SDL2/SDL_opengles2.h -- Installing: /usr/local/include/SDL2/SDL_opengles2_gl2.h -- Installing: /usr/local/include/SDL2/SDL_opengles2_gl2ext.h -- Installing: /usr/local/include/SDL2/SDL_opengles2_gl2platform.h -- Installing: /usr/local/include/SDL2/SDL_opengles2_khrplatform.h -- Installing: /usr/local/include/SDL2/SDL_pixels.h -- Installing: /usr/local/include/SDL2/SDL_platform.h -- Installing: /usr/local/include/SDL2/SDL_power.h -- Installing: /usr/local/include/SDL2/SDL_quit.h -- Installing: /usr/local/include/SDL2/SDL_rect.h -- Installing: /usr/local/include/SDL2/SDL_render.h -- Installing: /usr/local/include/SDL2/SDL_rwops.h -- Installing: /usr/local/include/SDL2/SDL_scancode.h -- Installing: /usr/local/include/SDL2/SDL_sensor.h -- Installing: /usr/local/include/SDL2/SDL_shape.h -- Installing: /usr/local/include/SDL2/SDL_stdinc.h -- Installing: /usr/local/include/SDL2/SDL_surface.h -- Installing: /usr/local/include/SDL2/SDL_system.h -- Installing: /usr/local/include/SDL2/SDL_syswm.h -- Installing: /usr/local/include/SDL2/SDL_test.h -- Installing: /usr/local/include/SDL2/SDL_test_assert.h -- Installing: /usr/local/include/SDL2/SDL_test_common.h -- Installing: /usr/local/include/SDL2/SDL_test_compare.h -- Installing: /usr/local/include/SDL2/SDL_test_crc32.h -- Installing: /usr/local/include/SDL2/SDL_test_font.h -- Installing: /usr/local/include/SDL2/SDL_test_fuzzer.h -- Installing: /usr/local/include/SDL2/SDL_test_harness.h -- Installing: /usr/local/include/SDL2/SDL_test_images.h -- Installing: /usr/local/include/SDL2/SDL_test_log.h -- Installing: /usr/local/include/SDL2/SDL_test_md5.h -- Installing: /usr/local/include/SDL2/SDL_test_memory.h -- Installing: /usr/local/include/SDL2/SDL_test_random.h -- Installing: /usr/local/include/SDL2/SDL_thread.h -- Installing: /usr/local/include/SDL2/SDL_timer.h -- Installing: /usr/local/include/SDL2/SDL_touch.h -- Installing: /usr/local/include/SDL2/SDL_types.h -- Installing: /usr/local/include/SDL2/SDL_version.h -- Installing: /usr/local/include/SDL2/SDL_video.h -- Installing: /usr/local/include/SDL2/SDL_vulkan.h -- Installing: /usr/local/include/SDL2/begin_code.h -- Installing: /usr/local/include/SDL2/close_code.h -- Installing: /usr/local/include/SDL2/SDL_revision.h -- Installing: /usr/local/include/SDL2/SDL_config.h -- Installing: /usr/local/share/licenses/SDL2/LICENSE.txt -- Installing: /usr/local/lib/pkgconfig/sdl2.pc -- Installing: /usr/local/lib/libSDL2.so -- Installing: /usr/local/bin/sdl2-config -- Installing: /usr/local/share/aclocal/sdl2.m4
CG
static const std::map<std::string, std::pair<int, std::string>> g_lang = { { "en", { 0, "english", } }, { "zh", { 1, "chinese", } }, { "de", { 2, "german", } }, { "es", { 3, "spanish", } }, { "ru", { 4, "russian", } }, { "ko", { 5, "korean", } }, { "fr", { 6, "french", } }, { "ja", { 7, "japanese", } }, { "pt", { 8, "portuguese", } }, { "tr", { 9, "turkish", } }, { "pl", { 10, "polish", } }, { "ca", { 11, "catalan", } }, { "nl", { 12, "dutch", } }, { "ar", { 13, "arabic", } }, { "sv", { 14, "swedish", } }, { "it", { 15, "italian", } }, { "id", { 16, "indonesian", } }, { "hi", { 17, "hindi", } }, { "fi", { 18, "finnish", } }, { "vi", { 19, "vietnamese", } }, { "he", { 20, "hebrew", } }, { "uk", { 21, "ukrainian", } }, { "el", { 22, "greek", } }, { "ms", { 23, "malay", } }, { "cs", { 24, "czech", } }, { "ro", { 25, "romanian", } }, { "da", { 26, "danish", } }, { "hu", { 27, "hungarian", } }, { "ta", { 28, "tamil", } }, { "no", { 29, "norwegian", } }, { "th", { 30, "thai", } }, { "ur", { 31, "urdu", } }, { "hr", { 32, "croatian", } }, { "bg", { 33, "bulgarian", } }, { "lt", { 34, "lithuanian", } }, { "la", { 35, "latin", } }, { "mi", { 36, "maori", } }, { "ml", { 37, "malayalam", } }, { "cy", { 38, "welsh", } }, { "sk", { 39, "slovak", } }, { "te", { 40, "telugu", } }, { "fa", { 41, "persian", } }, { "lv", { 42, "latvian", } }, { "bn", { 43, "bengali", } }, { "sr", { 44, "serbian", } }, { "az", { 45, "azerbaijani", } }, { "sl", { 46, "slovenian", } }, { "kn", { 47, "kannada", } }, { "et", { 48, "estonian", } }, { "mk", { 49, "macedonian", } }, { "br", { 50, "breton", } }, { "eu", { 51, "basque", } }, { "is", { 52, "icelandic", } }, { "hy", { 53, "armenian", } }, { "ne", { 54, "nepali", } }, { "mn", { 55, "mongolian", } }, { "bs", { 56, "bosnian", } }, { "kk", { 57, "kazakh", } }, { "sq", { 58, "albanian", } }, { "sw", { 59, "swahili", } }, { "gl", { 60, "galician", } }, { "mr", { 61, "marathi", } }, { "pa", { 62, "punjabi", } }, { "si", { 63, "sinhala", } }, { "km", { 64, "khmer", } }, { "sn", { 65, "shona", } }, { "yo", { 66, "yoruba", } }, { "so", { 67, "somali", } }, { "af", { 68, "afrikaans", } }, { "oc", { 69, "occitan", } }, { "ka", { 70, "georgian", } }, { "be", { 71, "belarusian", } }, { "tg", { 72, "tajik", } }, { "sd", { 73, "sindhi", } }, { "gu", { 74, "gujarati", } }, { "am", { 75, "amharic", } }, { "yi", { 76, "yiddish", } }, { "lo", { 77, "lao", } }, { "uz", { 78, "uzbek", } }, { "fo", { 79, "faroese", } }, { "ht", { 80, "haitian creole", } }, { "ps", { 81, "pashto", } }, { "tk", { 82, "turkmen", } }, { "nn", { 83, "nynorsk", } }, { "mt", { 84, "maltese", } }, { "sa", { 85, "sanskrit", } }, { "lb", { 86, "luxembourgish", } }, { "my", { 87, "myanmar", } }, { "bo", { 88, "tibetan", } }, { "tl", { 89, "tagalog", } }, { "mg", { 90, "malagasy", } }, { "as", { 91, "assamese", } }, { "tt", { 92, "tatar", } }, { "haw", { 93, "hawaiian", } }, { "ln", { 94, "lingala", } }, { "ha", { 95, "hausa", } }, { "ba", { 96, "bashkir", } }, { "jw", { 97, "javanese", } }, { "su", { 98, "sundanese", } }, { "yue", { 99, "cantonese", } }, }; (base) pdd@pdd-Dell-G15-5511:~/le$ git clone http://github.com/hogelog/whispercppapp.git --recurse-submodules 正克隆到 'whispercppapp'... warning: 重定向到 https://github.com/hogelog/whispercppapp.git/ remote: Enumerating objects: 411, done. remote: Counting objects: 100% (411/411), done. remote: Compressing objects: 100% (245/245), done. remote: Total 411 (delta 150), reused 368 (delta 113), pack-reused 0 接收对象中: 100% (411/411), 454.29 KiB | 161.00 KiB/s, 完成. 处理 delta 中: 100% (150/150), 完成. 子模组 'whisper.cpp'（https://github.com/ggerganov/whisper.cpp.git）已对路径 'whisper.cpp' 注册 正克隆到 '/home/pdd/le/whispercppapp/whisper.cpp'... remote: Enumerating objects: 6590, done. remote: Counting objects: 100% (1812/1812), done. remote: Compressing objects: 100% (192/192), done. error: RPC 失败。curl 16 Error in the HTTP2 framing layer error: 预期仍然需要 5253 个字节的正文 fetch-pack: unexpected disconnect while reading sideband packet fatal: 过早的文件结束符（EOF） fatal: fetch-pack：无效的 index-pack 输出 fatal: 无法克隆 'https://github.com/ggerganov/whisper.cpp.git' 到子模组路径 '/home/pdd/le/whispercppapp/whisper.cpp' 克隆 'whisper.cpp' 失败。按计划重试 正克隆到 '/home/pdd/le/whispercppapp/whisper.cpp'... remote: Enumerating objects: 6590, done. remote: Counting objects: 100% (1807/1807), done. remote: Compressing objects: 100% (191/191), done. remote: Total 6590 (delta 1699), reused 1651 (delta 1613), pack-reused 4783 接收对象中: 100% (6590/6590), 9.99 MiB | 209.00 KiB/s, 完成. 处理 delta 中: 100% (4244/4244), 完成. 子模组路径 'whisper.cpp'：检出 'ad1389003d3f8bd47b8ca7d4c21b4764cc3844fc' 子模组 'bindings/ios'（https://github.com/ggerganov/whisper.spm）已对路径 'whisper.cpp/bindings/ios' 注册 正克隆到 '/home/pdd/le/whispercppapp/whisper.cpp/bindings/ios'... remote: Enumerating objects: 357, done. remote: Counting objects: 100% (151/151), done. remote: Compressing objects: 100% (71/71), done. remote: Total 357 (delta 104), reused 104 (delta 80), pack-reused 206 接收对象中: 100% (357/357), 1.11 MiB | 163.00 KiB/s, 完成. 处理 delta 中: 100% (197/197), 完成. 子模组路径 'whisper.cpp/bindings/ios'：检出 '92d4c5c9a07b726e35c20dc513532789919e00c4' 子模组路径 'whisper.cpp'：检出 'ad1389003d3f8bd47b8ca7d4c21b4764cc3844fc' 
