offline-transducer-greedy-search-decoder.cc
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// sherpa-onnx/csrc/offline-transducer-greedy-search-decoder.cc
//
// Copyright (c) 2023 Xiaomi Corporation
#include "sherpa-onnx/csrc/offline-transducer-greedy-search-decoder.h"
#include <algorithm>
#include <iterator>
#include <utility>
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/packed-sequence.h"
#include "sherpa-onnx/csrc/slice.h"
namespace sherpa_onnx {
std::vector<OfflineTransducerDecoderResult>
OfflineTransducerGreedySearchDecoder::Decode(Ort::Value encoder_out,
Ort::Value encoder_out_length) {
PackedSequence packed_encoder_out = PackPaddedSequence(
model_->Allocator(), &encoder_out, &encoder_out_length);
int32_t batch_size =
static_cast<int32_t>(packed_encoder_out.sorted_indexes.size());
int32_t vocab_size = model_->VocabSize();
int32_t context_size = model_->ContextSize();
std::vector<OfflineTransducerDecoderResult> ans(batch_size);
for (auto &r : ans) {
// 0 is the ID of the blank token
r.tokens.resize(context_size, 0);
}
auto decoder_input = model_->BuildDecoderInput(ans, ans.size());
Ort::Value decoder_out = model_->RunDecoder(std::move(decoder_input));
int32_t start = 0;
int32_t t = 0;
for (auto n : packed_encoder_out.batch_sizes) {
Ort::Value cur_encoder_out = packed_encoder_out.Get(start, n);
Ort::Value cur_decoder_out = Slice(model_->Allocator(), &decoder_out, 0, n);
start += n;
Ort::Value logit = model_->RunJoiner(std::move(cur_encoder_out),
std::move(cur_decoder_out));
const float *p_logit = logit.GetTensorData<float>();
bool emitted = false;
for (int32_t i = 0; i != n; ++i) {
auto y = static_cast<int32_t>(std::distance(
static_cast<const float *>(p_logit),
std::max_element(static_cast<const float *>(p_logit),
static_cast<const float *>(p_logit) + vocab_size)));
p_logit += vocab_size;
if (y != 0) {
ans[i].tokens.push_back(y);
ans[i].timestamps.push_back(t);
emitted = true;
}
}
if (emitted) {
Ort::Value decoder_input = model_->BuildDecoderInput(ans, n);
decoder_out = model_->RunDecoder(std::move(decoder_input));
}
++t;
}
for (auto &r : ans) {
r.tokens = {r.tokens.begin() + context_size, r.tokens.end()};
}
std::vector<OfflineTransducerDecoderResult> unsorted_ans(batch_size);
for (int32_t i = 0; i != batch_size; ++i) {
unsorted_ans[packed_encoder_out.sorted_indexes[i]] = std::move(ans[i]);
}
return unsorted_ans;
}
} // namespace sherpa_onnx