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Fix create ort value hardcoded memory info to CPU (#10510)

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* Fix create ort value hardcoded memory info to CPU

* Remove unneeded check

* Remove unneeded header

* Remove unneeded header

* Update ort_ops.cpp

* Update ort_ops.cpp

* Update ort_ops.cpp

* Update ort_ops.cpp

Co-authored-by: root <root@QTM-ANHNGUYEN-1.northamerica.corp.microsoft.com>
This commit is contained in:
Anh Nguyen 2022-02-15 10:40:44 -08:00 committed by GitHub
parent 1cdc23aba4
commit 0c3e88944d
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GPG key ID: 4AEE18F83AFDEB23
4 changed files with 32 additions and 12 deletions
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6
orttraining/orttraining/eager/ort_aten.cpp
View file

@ -129,11 +129,15 @@ OrtValue create_ort_value(
return impl->tensor();
}
OrtMemoryInfo *mem_info;
Ort::ThrowOnError(Ort::GetApi().CreateCpuMemoryInfo(OrtArenaAllocator, OrtMemTypeDefault, &mem_info));
OrtValue ort_tensor;
CreateMLValue(
tensor.data_ptr(),
ort_scalar_type_from_aten(tensor.scalar_type()),
tensor.sizes().vec(),
*mem_info,
&ort_tensor);
return ort_tensor;
}
@ -544,4 +548,4 @@ at::Tensor& add__Tensor(
//#pragma endregion
} // namespace eager
} // namespace torch_ort
} // namespace torch_ort

3
orttraining/orttraining/eager/ort_ops.cpp
View file

@ -26,7 +26,8 @@ void createInplaceOutputValue(OrtValue& input, V<int64_t> shape, OrtValue* p_mlv
onnxruntime::ReshapeHelper helper(input.Get<onnxruntime::Tensor>().Shape(), target_shape);
onnxruntime::TensorShape new_shape(target_shape);
CreateMLValue(input_ort_tensor->MutableDataRaw(),
input_ort_tensor->DataType(), new_shape, p_mlvalue);
input_ort_tensor->DataType(), new_shape,
input_ort_tensor->Location(), p_mlvalue);
}
template void createInplaceOutputValue<c10::ArrayRef>(OrtValue& input, c10::ArrayRef<int64_t> shape, OrtValue* p_mlvalue);

20
orttraining/orttraining/eager/ort_util.cpp
View file

@ -25,22 +25,28 @@ void CreateMLValue(onnxruntime::AllocatorPtr alloc,
onnxruntime::DataTypeImpl::GetType<onnxruntime::Tensor>()->GetDeleteFunc());
}
void CreateMLValue(void* data_ptr, onnxruntime::MLDataType element_type, onnxruntime::TensorShape& shape, OrtValue* p_mlvalue){
OrtMemoryInfo *cpu_info;
Ort::ThrowOnError(Ort::GetApi().CreateCpuMemoryInfo(OrtArenaAllocator, OrtMemTypeDefault, &cpu_info));
void CreateMLValue(void* data_ptr,
onnxruntime::MLDataType element_type,
onnxruntime::TensorShape& shape,
const OrtMemoryInfo& memory_info,
OrtValue* p_mlvalue) {
std::unique_ptr<onnxruntime::Tensor> p_tensor = std::make_unique<onnxruntime::Tensor>(element_type,
shape,
data_ptr,
*cpu_info);
memory_info);
p_mlvalue->Init(p_tensor.release(),
onnxruntime::DataTypeImpl::GetType<onnxruntime::Tensor>(),
onnxruntime::DataTypeImpl::GetType<onnxruntime::Tensor>()->GetDeleteFunc());
}
void CreateMLValue(void* data_ptr, onnxruntime::MLDataType element_type, const std::vector<int64_t>& dims, OrtValue* p_mlvalue) {
void CreateMLValue(void* data_ptr,
onnxruntime::MLDataType element_type,
const std::vector<int64_t>& dims,
const OrtMemoryInfo& memory_info,
OrtValue* p_mlvalue) {
onnxruntime::TensorShape shape(dims);
CreateMLValue(data_ptr, element_type, shape, p_mlvalue);
CreateMLValue(data_ptr, element_type, shape, memory_info, p_mlvalue);
}
std::vector<int64_t> GetStrides(gsl::span<const int64_t> shape) {
@ -52,4 +58,4 @@ std::vector<int64_t> GetStrides(gsl::span<const int64_t> shape) {
}
} // namespace eager
} // namespace torch_ort
} // namespace torch_ort

15
orttraining/orttraining/eager/ort_util.h
View file

@ -15,8 +15,17 @@ void CreateMLValue(onnxruntime::AllocatorPtr alloc,
const std::vector<int64_t>& dims,
OrtValue* p_mlvalue);
void CreateMLValue(void* data_ptr, onnxruntime::MLDataType element_type, const std::vector<int64_t>& dims, OrtValue* p_mlvalue);
void CreateMLValue(void* data_ptr, onnxruntime::MLDataType element_type, onnxruntime::TensorShape& shape, OrtValue* p_mlvalue);
void CreateMLValue(void* data_ptr,
onnxruntime::MLDataType element_type,
const std::vector<int64_t>& dims,
const OrtMemoryInfo& memory_info,
OrtValue* p_mlvalue);
void CreateMLValue(void* data_ptr,
onnxruntime::MLDataType element_type,
onnxruntime::TensorShape& shape,
const OrtMemoryInfo& memory_info,
OrtValue* p_mlvalue);
template <typename T>
inline void CopyVectorToTensor(onnxruntime::ORTInvoker& invoker,
@ -57,4 +66,4 @@ inline void CopyVectorToTensor<bool>(onnxruntime::ORTInvoker& /*invoker*/,
std::vector<int64_t> GetStrides(gsl::span<const int64_t> shape);
} // namespace eager
} // namespace torch_ort
} // namespace torch_ort