EngineX-Iluvatar/enginex-mr_series-sherpa-onnx
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Add address sanitizer and undefined behavior sanitizer (#951)

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This commit is contained in:
Fangjun Kuang
2024-05-31 13:17:01 +08:00
committed by GitHub
parent a38881817c
commit f1cff83ef9
56 changed files with 354 additions and 132 deletions
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22
sherpa-onnx/csrc/online-zipformer2-transducer-model.cc
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@@ -34,8 +34,8 @@ namespace sherpa_onnx {
OnlineZipformer2TransducerModel::OnlineZipformer2TransducerModel(
const OnlineModelConfig &config)
: env_(ORT_LOGGING_LEVEL_WARNING),
config_(config),
sess_opts_(GetSessionOptions(config)),
config_(config),
allocator_{} {
{
auto buf = ReadFile(config.transducer.encoder);
@@ -179,7 +179,6 @@ void OnlineZipformer2TransducerModel::InitJoiner(void *model_data,
std::vector<Ort::Value> OnlineZipformer2TransducerModel::StackStates(
const std::vector<std::vector<Ort::Value>> &states) const {
int32_t batch_size = static_cast<int32_t>(states.size());
int32_t num_encoders = static_cast<int32_t>(num_encoder_layers_.size());
std::vector<const Ort::Value *> buf(batch_size);
@@ -255,10 +254,9 @@ OnlineZipformer2TransducerModel::UnStackStates(
const std::vector<Ort::Value> &states) const {
int32_t m = std::accumulate(num_encoder_layers_.begin(),
num_encoder_layers_.end(), 0);
assert(states.size() == m * 6 + 2);
assert(static_cast<int32_t>(states.size()) == m * 6 + 2);
int32_t batch_size = states[0].GetTensorTypeAndShapeInfo().GetShape()[1];
int32_t num_encoders = num_encoder_layers_.size();
std::vector<std::vector<Ort::Value>> ans;
ans.resize(batch_size);
@@ -266,7 +264,7 @@ OnlineZipformer2TransducerModel::UnStackStates(
for (int32_t i = 0; i != m; ++i) {
{
auto v = Unbind(allocator_, &states[i * 6], 1);
assert(v.size() == batch_size);
assert(static_cast<int32_t>(v.size()) == batch_size);
for (int32_t n = 0; n != batch_size; ++n) {
ans[n].push_back(std::move(v[n]));
@@ -274,7 +272,7 @@ OnlineZipformer2TransducerModel::UnStackStates(
}
{
auto v = Unbind(allocator_, &states[i * 6 + 1], 1);
assert(v.size() == batch_size);
assert(static_cast<int32_t>(v.size()) == batch_size);
for (int32_t n = 0; n != batch_size; ++n) {
ans[n].push_back(std::move(v[n]));
@@ -282,7 +280,7 @@ OnlineZipformer2TransducerModel::UnStackStates(
}
{
auto v = Unbind(allocator_, &states[i * 6 + 2], 1);
assert(v.size() == batch_size);
assert(static_cast<int32_t>(v.size()) == batch_size);
for (int32_t n = 0; n != batch_size; ++n) {
ans[n].push_back(std::move(v[n]));
@@ -290,7 +288,7 @@ OnlineZipformer2TransducerModel::UnStackStates(
}
{
auto v = Unbind(allocator_, &states[i * 6 + 3], 1);
assert(v.size() == batch_size);
assert(static_cast<int32_t>(v.size()) == batch_size);
for (int32_t n = 0; n != batch_size; ++n) {
ans[n].push_back(std::move(v[n]));
@@ -298,7 +296,7 @@ OnlineZipformer2TransducerModel::UnStackStates(
}
{
auto v = Unbind(allocator_, &states[i * 6 + 4], 0);
assert(v.size() == batch_size);
assert(static_cast<int32_t>(v.size()) == batch_size);
for (int32_t n = 0; n != batch_size; ++n) {
ans[n].push_back(std::move(v[n]));
@@ -306,7 +304,7 @@ OnlineZipformer2TransducerModel::UnStackStates(
}
{
auto v = Unbind(allocator_, &states[i * 6 + 5], 0);
assert(v.size() == batch_size);
assert(static_cast<int32_t>(v.size()) == batch_size);
for (int32_t n = 0; n != batch_size; ++n) {
ans[n].push_back(std::move(v[n]));
@@ -316,7 +314,7 @@ OnlineZipformer2TransducerModel::UnStackStates(
{
auto v = Unbind(allocator_, &states[m * 6], 0);
assert(v.size() == batch_size);
assert(static_cast<int32_t>(v.size()) == batch_size);
for (int32_t n = 0; n != batch_size; ++n) {
ans[n].push_back(std::move(v[n]));
@@ -324,7 +322,7 @@ OnlineZipformer2TransducerModel::UnStackStates(
}
{
auto v = Unbind<int64_t>(allocator_, &states[m * 6 + 1], 0);
assert(v.size() == batch_size);
assert(static_cast<int32_t>(v.size()) == batch_size);
for (int32_t n = 0; n != batch_size; ++n) {
ans[n].push_back(std::move(v[n]));