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Support batch greedy search decoding (#30)

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This commit is contained in:
Fangjun Kuang
2023-02-19 15:04:24 +08:00
committed by GitHub
parent ebc3b47fb8
commit 8acc059b3f
5 changed files with 181 additions and 68 deletions
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52
sherpa-onnx/csrc/online-recognizer.cc
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@@ -6,6 +6,7 @@
#include <assert.h>
#include <algorithm>
#include <memory>
#include <sstream>
#include <utility>
@@ -64,39 +65,50 @@ class OnlineRecognizer::Impl {
}
void DecodeStreams(OnlineStream **ss, int32_t n) {
if (n != 1) {
fprintf(stderr, "only n == 1 is implemented\n");
exit(-1);
}
OnlineStream *s = ss[0];
assert(IsReady(s));
int32_t chunk_size = model_->ChunkSize();
int32_t chunk_shift = model_->ChunkShift();
int32_t feature_dim = s->FeatureDim();
int32_t feature_dim = ss[0]->FeatureDim();
std::array<int64_t, 3> x_shape{1, chunk_size, feature_dim};
std::vector<OnlineTransducerDecoderResult> results(n);
std::vector<float> features_vec(n * chunk_size * feature_dim);
std::vector<std::vector<Ort::Value>> states_vec(n);
for (int32_t i = 0; i != n; ++i) {
std::vector<float> features =
ss[i]->GetFrames(ss[i]->GetNumProcessedFrames(), chunk_size);
ss[i]->GetNumProcessedFrames() += chunk_shift;
std::copy(features.begin(), features.end(),
features_vec.data() + i * chunk_size * feature_dim);
results[i] = std::move(ss[i]->GetResult());
states_vec[i] = std::move(ss[i]->GetStates());
}
auto memory_info =
Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
std::vector<float> features =
s->GetFrames(s->GetNumProcessedFrames(), chunk_size);
std::array<int64_t, 3> x_shape{n, chunk_size, feature_dim};
s->GetNumProcessedFrames() += chunk_shift;
Ort::Value x = Ort::Value::CreateTensor(memory_info, features_vec.data(),
features_vec.size(), x_shape.data(),
x_shape.size());
Ort::Value x =
Ort::Value::CreateTensor(memory_info, features.data(), features.size(),
x_shape.data(), x_shape.size());
auto states = model_->StackStates(states_vec);
auto pair = model_->RunEncoder(std::move(x), s->GetStates());
s->SetStates(std::move(pair.second));
std::vector<OnlineTransducerDecoderResult> results = {s->GetResult()};
auto pair = model_->RunEncoder(std::move(x), states);
decoder_->Decode(std::move(pair.first), &results);
s->SetResult(results[0]);
std::vector<std::vector<Ort::Value>> next_states =
model_->UnStackStates(pair.second);
for (int32_t i = 0; i != n; ++i) {
ss[i]->SetResult(results[i]);
ss[i]->SetStates(std::move(next_states[i]));
}
}
OnlineRecognizerResult GetResult(OnlineStream *s) {