EngineX-Iluvatar/enginex_bi_series-sherpa-onnx
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Use deep copy in Clone() (#66)

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This commit is contained in:
Fangjun Kuang
2023-02-26 14:54:01 +08:00
committed by GitHub
parent 475caf22f9
commit 5a8c3a6d10
7 changed files with 41 additions and 24 deletions
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2
sherpa-onnx/csrc/cat.cc
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@@ -37,7 +37,7 @@ template <typename T /*=float*/>
Ort::Value Cat(OrtAllocator *allocator,
const std::vector<const Ort::Value *> &values, int32_t dim) {
if (values.size() == 1u) {
return Clone(values[0]);
return Clone(allocator, values[0]);
}
std::vector<int64_t> v0_shape =

4
sherpa-onnx/csrc/online-transducer-greedy-search-decoder.cc
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@@ -100,8 +100,8 @@ void OnlineTransducerGreedySearchDecoder::Decode(
for (int32_t t = 0; t != num_frames; ++t) {
Ort::Value cur_encoder_out = GetFrame(&encoder_out, t);
cur_encoder_out = Repeat(model_->Allocator(), &cur_encoder_out, batch_size);
Ort::Value logit =
model_->RunJoiner(std::move(cur_encoder_out), Clone(&decoder_out));
Ort::Value logit = model_->RunJoiner(
std::move(cur_encoder_out), Clone(model_->Allocator(), &decoder_out));
const float *p_logit = logit.GetTensorData<float>();
bool emitted = false;

44
sherpa-onnx/csrc/onnx-utils.cc
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@@ -53,7 +53,7 @@ void PrintModelMetadata(std::ostream &os, const Ort::ModelMetadata &meta_data) {
}
}
Ort::Value Clone(const Ort::Value *v) {
Ort::Value Clone(OrtAllocator *allocator, const Ort::Value *v) {
auto type_and_shape = v->GetTensorTypeAndShapeInfo();
std::vector<int64_t> shape = type_and_shape.GetShape();
@@ -61,21 +61,33 @@ Ort::Value Clone(const Ort::Value *v) {
Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
switch (type_and_shape.GetElementType()) {
case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32:
return Ort::Value::CreateTensor(
memory_info,
const_cast<Ort::Value *>(v)->GetTensorMutableData<int32_t>(),
type_and_shape.GetElementCount(), shape.data(), shape.size());
case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64:
return Ort::Value::CreateTensor(
memory_info,
const_cast<Ort::Value *>(v)->GetTensorMutableData<int64_t>(),
type_and_shape.GetElementCount(), shape.data(), shape.size());
case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT:
return Ort::Value::CreateTensor(
memory_info,
const_cast<Ort::Value *>(v)->GetTensorMutableData<float>(),
type_and_shape.GetElementCount(), shape.data(), shape.size());
case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32: {
Ort::Value ans = Ort::Value::CreateTensor<int32_t>(
allocator, shape.data(), shape.size());
const int32_t *start = v->GetTensorData<int32_t>();
const int32_t *end = start + type_and_shape.GetElementCount();
int32_t *dst = ans.GetTensorMutableData<int32_t>();
std::copy(start, end, dst);
return ans;
}
case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64: {
Ort::Value ans = Ort::Value::CreateTensor<int64_t>(
allocator, shape.data(), shape.size());
const int64_t *start = v->GetTensorData<int64_t>();
const int64_t *end = start + type_and_shape.GetElementCount();
int64_t *dst = ans.GetTensorMutableData<int64_t>();
std::copy(start, end, dst);
return ans;
}
case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT: {
Ort::Value ans = Ort::Value::CreateTensor<float>(allocator, shape.data(),
shape.size());
const float *start = v->GetTensorData<float>();
const float *end = start + type_and_shape.GetElementCount();
float *dst = ans.GetTensorMutableData<float>();
std::copy(start, end, dst);
return ans;
}
default:
fprintf(stderr, "Unsupported type: %d\n",
static_cast<int32_t>(type_and_shape.GetElementType()));

4
sherpa-onnx/csrc/onnx-utils.h
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@@ -60,8 +60,8 @@ void GetOutputNames(Ort::Session *sess, std::vector<std::string> *output_names,
void PrintModelMetadata(std::ostream &os,
const Ort::ModelMetadata &meta_data); // NOLINT
// Return a shallow copy of v
Ort::Value Clone(const Ort::Value *v);
// Return a deep copy of v
Ort::Value Clone(OrtAllocator *allocator, const Ort::Value *v);
// Print a 1-D tensor to stderr
void Print1D(Ort::Value *v);

2
sherpa-onnx/csrc/unbind.cc
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@@ -26,7 +26,7 @@ std::vector<Ort::Value> Unbind(OrtAllocator *allocator, const Ort::Value *value,
int32_t n = static_cast<int32_t>(shape[dim]);
if (n == 1) {
std::vector<Ort::Value> ans;
ans.push_back(Clone(value));
ans.push_back(Clone(allocator, value));
return ans;
}