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webassembly003 whisper.cpp的main项目-1

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

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 = { &params, &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

ERROR: Couldn’t initialize SDL: dsp: No such audio device

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'

更新时间 2024-06-28