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@ -204,6 +204,10 @@ struct whisper_vocab {
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std::map<token, id> token_to_id;
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std::map<id, token> id_to_token;
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// used to avoid memory allocations during sampling
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// TODO: move to whisper_context in the future
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std::vector<std::pair<double, whisper_vocab::id>> probs_id;
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id token_eot = 50256;
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id token_sot = 50257;
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id token_prev = 50360;
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@ -551,6 +555,9 @@ static bool whisper_model_load(const std::string & fname, whisper_context & wctx
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std::string word;
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std::vector<char> tmp;
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tmp.reserve(128);
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for (int i = 0; i < n_vocab; i++) {
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uint32_t len;
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read_safe(fin, len);
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@ -603,6 +610,11 @@ static bool whisper_model_load(const std::string & fname, whisper_context & wctx
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vocab.id_to_token[i] = word;
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}
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}
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wctx.logits.reserve(vocab.n_vocab*model.hparams.n_text_ctx);
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wctx.probs.reserve(vocab.n_vocab*model.hparams.n_text_ctx);
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vocab.probs_id.reserve(n_vocab);
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}
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{
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@ -1849,7 +1861,7 @@ static bool whisper_decode(
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// the most basic sampling scheme - select the top token
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static whisper_token_data whisper_sample_best(
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const whisper_vocab & vocab,
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whisper_vocab & vocab,
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const float * probs,
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bool force_timestamp,
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bool is_initial) {
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@ -1857,11 +1869,11 @@ static whisper_token_data whisper_sample_best(
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0, 0, 0.0f, 0.0f, 0.0f, -1, -1, 0.0f,
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};
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int n_logits = vocab.id_to_token.size();
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const int n_logits = vocab.n_vocab;
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std::vector<std::pair<double, whisper_vocab::id>> probs_id;
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probs_id.reserve(n_logits);
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auto & probs_id = vocab.probs_id;
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probs_id.clear();
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for (int i = 0; i < n_logits; i++) {
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probs_id.emplace_back(probs[i], i);
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}
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@ -2001,6 +2013,9 @@ static void fft(const std::vector<float> & in, std::vector<float> & out) {
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std::vector<float> even;
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std::vector<float> odd;
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even.reserve(N/2);
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odd.reserve(N/2);
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for (int i = 0; i < N; i++) {
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if (i % 2 == 0) {
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even.push_back(in[i]);
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