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@ -210,9 +210,12 @@ struct whisper_vocab {
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}
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};
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struct whisper_result {
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int64_t t;
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whisper_token id;
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struct whisper_token_data {
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whisper_token id; // token id
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whisper_token tid; // forced timestamp token id
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float p; // probability of the token
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float pt; // probability of the timestamp token
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};
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struct whisper_segment {
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@ -220,6 +223,8 @@ struct whisper_segment {
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int64_t t1;
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std::string text;
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std::vector<whisper_token_data> tokens;
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};
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// medium
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@ -407,7 +412,7 @@ struct whisper_context {
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std::vector<float> probs;
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std::vector<float> logits;
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std::vector<whisper_result> result_cur;
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std::vector<whisper_token_data> tokens_cur;
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std::vector<whisper_segment> result_all;
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std::vector<whisper_token> prompt_past;
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@ -1786,9 +1791,11 @@ bool whisper_decode(
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}
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// the most basic sampling scheme - select the top token
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whisper_vocab::id whisper_sample_best(
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whisper_token_data whisper_sample_best(
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const whisper_vocab & vocab,
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const float * probs) {
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whisper_token_data result;
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int n_logits = vocab.id_to_token.size();
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std::vector<std::pair<double, whisper_vocab::id>> probs_id;
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@ -1798,24 +1805,33 @@ whisper_vocab::id whisper_sample_best(
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probs_id.push_back(std::make_pair(probs[i], i));
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}
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double sum_ts = 0.0;
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double max_tx = 0.0;
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{
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double sum_ts = 0.0;
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double max_ts = -1.0;
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double max_tx = -1.0;
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for (int i = 0; i < vocab.token_beg; i++) {
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max_tx = std::max(max_tx, probs_id[i].first);
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}
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for (int i = 0; i < vocab.token_beg; i++) {
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max_tx = std::max(max_tx, probs_id[i].first);
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}
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for (int i = vocab.token_beg; i < n_logits; i++) {
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sum_ts += probs_id[i].first;
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}
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for (int i = vocab.token_beg; i < n_logits; i++) {
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sum_ts += probs_id[i].first;
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if (probs_id[i].first > max_ts) {
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max_ts = probs_id[i].first;
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result.tid = probs_id[i].second;
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}
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}
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// if the probability sum of all timestamp tokesn is higher than the max probability of the text tokens - sample a
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// timestamp token
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if (sum_ts > max_tx) {
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// ref: https://github.com/openai/whisper/blob/0b1ba3d46ebf7fe6f953acfd8cad62a4f851b49f/whisper/decoding.py#L430-L438
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for (int i = 0; i < vocab.token_beg; i++) {
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probs_id[i].first = -INFINITY;
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// if the probability sum of all timestamp tokens is higher than the max probability of the text tokens - sample a
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// timestamp token
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if (sum_ts > max_tx) {
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// ref: https://github.com/openai/whisper/blob/0b1ba3d46ebf7fe6f953acfd8cad62a4f851b49f/whisper/decoding.py#L430-L438
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for (int i = 0; i < vocab.token_beg; i++) {
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probs_id[i].first = -INFINITY;
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}
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}
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result.pt = max_ts/(sum_ts + 1e-6);
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}
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// find the top K tokens
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@ -1843,7 +1859,10 @@ whisper_vocab::id whisper_sample_best(
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res++;
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}
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return probs_id[res].second;
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result.id = probs_id[res].second;
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result.p = probs_id[res].first;
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return result;
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}
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// samples only from the timestamps tokens
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@ -2178,7 +2197,7 @@ whisper_token whisper_sample_best(struct whisper_context * ctx) {
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ctx->t_sample_us += ggml_time_us() - t_start_sample_us;
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return res;
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return res.id;
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}
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whisper_token whisper_sample_timestamp(struct whisper_context * ctx) {
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@ -2343,7 +2362,7 @@ int whisper_full(
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int n_samples) {
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// clear old results
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auto & result_all = ctx->result_all;
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auto & result_cur = ctx->result_cur;
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auto & tokens_cur = ctx->tokens_cur;
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result_all.clear();
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@ -2430,7 +2449,7 @@ int whisper_full(
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// the accumulated transcription in the current interation
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int result_len = 0;
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result_cur.clear();
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tokens_cur.clear();
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for (int i = 0; i < whisper_n_text_ctx(ctx)/2 - 4; ++i) {
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if (whisper_decode(ctx, prompt.data(), prompt.size(), n_past, params.n_threads) != 0) {
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@ -2449,28 +2468,26 @@ int whisper_full(
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// feel free to experiment!
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//
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{
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whisper_token id = 0;
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whisper_token tid = whisper_token_beg(ctx);
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auto token = whisper_sample_best(ctx->vocab, ctx->probs.data() + (ctx->probs.size() - ctx->vocab.n_vocab));
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id = whisper_sample_best(ctx);
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if (i > 0) {
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tid = whisper_sample_timestamp(ctx);
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if (i == 0) {
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token.tid = whisper_token_beg(ctx);
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}
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// update sliding window
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if (id > whisper_token_beg(ctx)) {
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seek_delta = 2*(id - whisper_token_beg(ctx));
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// timestamp token - update sliding window
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if (token.id > whisper_token_beg(ctx)) {
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seek_delta = 2*(token.id - whisper_token_beg(ctx));
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result_len = i + 1;
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}
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// add it to the context
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prompt.push_back(id);
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result_cur.push_back({ seek + 2*(tid - whisper_token_beg(ctx)), id });
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prompt.push_back(token.id);
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tokens_cur.push_back(token);
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//printf("%s: %s\n", __func__, ctx->vocab.id_to_token[id].c_str());
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// end of text token
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if (id == whisper_token_eot(ctx)) {
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if (token.id == whisper_token_eot(ctx)) {
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if (result_len == 0) {
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if (seek + seek_delta + 100 >= whisper_n_len(ctx)) {
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result_len = i + 1;
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@ -2494,25 +2511,30 @@ int whisper_full(
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}
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}
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result_cur.resize(result_len);
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tokens_cur.resize(result_len);
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for (const auto & r : result_cur) {
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for (const auto & r : tokens_cur) {
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prompt_past.push_back(r.id);
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}
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// store the text from this iteration
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if (result_cur.size() > 0) {
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auto t0 = result_cur.front().t;
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if (tokens_cur.size() > 0) {
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int i0 = 0;
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auto t0 = 2*(tokens_cur.front().tid - whisper_token_beg(ctx));
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std::string text = "";
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for (int i = 0; i < (int) result_cur.size(); i++) {
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if (params.print_special_tokens == false && result_cur[i].id >= whisper_token_eot(ctx)) {
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for (int i = 0; i < (int) tokens_cur.size(); i++) {
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//printf("%s: %18s %6.3f %18s %6.3f\n", __func__,
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// ctx->vocab.id_to_token[tokens_cur[i].id].c_str(), tokens_cur[i].p,
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// ctx->vocab.id_to_token[tokens_cur[i].tid].c_str(), tokens_cur[i].pt);
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if (params.print_special_tokens == false && tokens_cur[i].id >= whisper_token_eot(ctx)) {
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} else {
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text += whisper_token_to_str(ctx, result_cur[i].id);
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text += whisper_token_to_str(ctx, tokens_cur[i].id);
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}
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if (result_cur[i].id > whisper_token_beg(ctx)) {
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const auto t1 = result_cur[i].t;
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if (tokens_cur[i].id > whisper_token_beg(ctx)) {
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const auto t1 = 2*(tokens_cur[i].tid - whisper_token_beg(ctx));
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if (!text.empty()) {
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if (params.print_realtime) {
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if (params.print_timestamps) {
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@ -2523,14 +2545,18 @@ int whisper_full(
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}
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}
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result_all.push_back({ t0, t1, text });
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result_all.push_back({ t0, t1, text, {} });
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for (int j = i0; j <= i; j++) {
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result_all.back().tokens.push_back(tokens_cur[j]);
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}
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}
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text = "";
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while (i < (int) result_cur.size() && result_cur[i].id > whisper_token_beg(ctx)) {
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while (i < (int) tokens_cur.size() && tokens_cur[i].id > whisper_token_beg(ctx)) {
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i++;
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}
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i--;
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t0 = result_cur[i].t;
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t0 = t1;
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i0 = i + 1;
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}
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}
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@ -2546,7 +2572,10 @@ int whisper_full(
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}
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}
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result_all.push_back({ t0, t1, text });
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result_all.push_back({ t0, t1, text, {} });
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for (int j = i0; j < (int) tokens_cur.size(); j++) {
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result_all.back().tokens.push_back(tokens_cur[j]);
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}
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}
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}
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@ -2571,3 +2600,15 @@ int64_t whisper_full_get_segment_t1(struct whisper_context * ctx, int i_segment)
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const char * whisper_full_get_segment_text(struct whisper_context * ctx, int i_segment) {
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return ctx->result_all[i_segment].text.c_str();
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}
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int whisper_full_n_tokens(struct whisper_context * ctx, int i_segment) {
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return ctx->result_all[i_segment].tokens.size();
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}
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const char * whisper_full_get_token_text(struct whisper_context * ctx, int i_segment, int i_token) {
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return ctx->vocab.id_to_token[ctx->result_all[i_segment].tokens[i_token].id].c_str();
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}
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float whisper_full_get_token_p(struct whisper_context * ctx, int i_segment, int i_token) {
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return ctx->result_all[i_segment].tokens[i_token].p;
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}
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