online-ctc-greedy-search-decoder.cc
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// sherpa-onnx/csrc/online-ctc-greedy-search-decoder.cc
//
// Copyright (c) 2023 Xiaomi Corporation
#include "sherpa-onnx/csrc/online-ctc-greedy-search-decoder.h"
#include <algorithm>
#include <utility>
#include <vector>
#include "sherpa-onnx/csrc/macros.h"
namespace sherpa_onnx {
void OnlineCtcGreedySearchDecoder::Decode(
Ort::Value log_probs, std::vector<OnlineCtcDecoderResult> *results) {
std::vector<int64_t> log_probs_shape =
log_probs.GetTensorTypeAndShapeInfo().GetShape();
if (log_probs_shape[0] != results->size()) {
SHERPA_ONNX_LOGE("Size mismatch! log_probs.size(0) %d, results.size(0): %d",
static_cast<int32_t>(log_probs_shape[0]),
static_cast<int32_t>(results->size()));
exit(-1);
}
int32_t batch_size = static_cast<int32_t>(log_probs_shape[0]);
int32_t num_frames = static_cast<int32_t>(log_probs_shape[1]);
int32_t vocab_size = static_cast<int32_t>(log_probs_shape[2]);
const float *p = log_probs.GetTensorData<float>();
for (int32_t b = 0; b != batch_size; ++b) {
auto &r = (*results)[b];
int32_t prev_id = -1;
for (int32_t t = 0; t != num_frames; ++t, p += vocab_size) {
int32_t y = static_cast<int32_t>(std::distance(
static_cast<const float *>(p),
std::max_element(static_cast<const float *>(p),
static_cast<const float *>(p) + vocab_size)));
if (y == blank_id_) {
r.num_trailing_blanks += 1;
} else {
r.num_trailing_blanks = 0;
}
if (y != blank_id_ && y != prev_id) {
r.tokens.push_back(y);
r.timestamps.push_back(t);
}
prev_id = y;
} // for (int32_t t = 0; t != num_frames; ++t) {
} // for (int32_t b = 0; b != batch_size; ++b)
}
} // namespace sherpa_onnx