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Fix inconsistent dimension data type in C-API (#726)

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* update dimension type

* update dimension type for items added after 0.2.1

* fix gpu build
This commit is contained in:
Ahmad El Husseini 2019-03-29 00:23:25 -07:00 committed by Changming Sun
parent 165657ee1a
commit e643ce0e08
6 changed files with 25 additions and 25 deletions
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4
include/onnxruntime/core/session/onnxruntime_c_api.h
View file

@ -289,7 +289,7 @@ ORT_API(void, OrtRunOptionsSetTerminate, _In_ OrtRunOptions*, _In_ int flag);
* \param type must be one of TENSOR_ELEMENT_DATA_TYPE_xxxx
*/
ORT_API_STATUS(OrtCreateTensorAsOrtValue, _Inout_ OrtAllocator* allocator,
_In_ const size_t* shape, size_t shape_len, ONNXTensorElementDataType type,
_In_ const int64_t* shape, size_t shape_len, ONNXTensorElementDataType type,
_Out_ OrtValue** out);
/**
@ -298,7 +298,7 @@ ORT_API_STATUS(OrtCreateTensorAsOrtValue, _Inout_ OrtAllocator* allocator,
* \param out Should be freed by calling OrtReleaseValue
*/
ORT_API_STATUS(OrtCreateTensorWithDataAsOrtValue, _In_ const OrtAllocatorInfo* info,
_Inout_ void* p_data, size_t p_data_len, _In_ const size_t* shape, size_t shape_len,
_Inout_ void* p_data, size_t p_data_len, _In_ const int64_t* shape, size_t shape_len,
ONNXTensorElementDataType type, _Out_ OrtValue** out);
// This function doesn't work with string tensor

4
include/onnxruntime/core/session/onnxruntime_cxx_api.h
View file

@ -129,13 +129,13 @@ class SessionOptionsWrapper {
}
#endif
};
inline OrtValue* OrtCreateTensorAsOrtValue(_Inout_ OrtAllocator* env, const std::vector<size_t>& shape, ONNXTensorElementDataType type) {
inline OrtValue* OrtCreateTensorAsOrtValue(_Inout_ OrtAllocator* env, const std::vector<int64_t>& shape, ONNXTensorElementDataType type) {
OrtValue* ret;
ORT_THROW_ON_ERROR(::OrtCreateTensorAsOrtValue(env, shape.data(), shape.size(), type, &ret));
return ret;
}
inline OrtValue* OrtCreateTensorWithDataAsOrtValue(_In_ const OrtAllocatorInfo* info, _In_ void* p_data, size_t p_data_len, const std::vector<size_t>& shape, ONNXTensorElementDataType type) {
inline OrtValue* OrtCreateTensorWithDataAsOrtValue(_In_ const OrtAllocatorInfo* info, _In_ void* p_data, size_t p_data_len, const std::vector<int64_t>& shape, ONNXTensorElementDataType type) {
OrtValue* ret;
ORT_THROW_ON_ERROR(::OrtCreateTensorWithDataAsOrtValue(info, p_data, p_data_len, shape.data(), shape.size(), type, &ret));
return ret;

16
onnxruntime/core/session/onnxruntime_c_api.cc
View file

@ -167,7 +167,7 @@ ORT_API_STATUS_IMPL(OrtFillStringTensor, _In_ OrtValue* value, _In_ const char*
}
template <typename T>
OrtStatus* CreateTensorImpl(const size_t* shape, size_t shape_len, OrtAllocator* allocator,
OrtStatus* CreateTensorImpl(const int64_t* shape, size_t shape_len, OrtAllocator* allocator,
std::unique_ptr<Tensor>* out) {
std::vector<int64_t> shapes(shape_len);
for (size_t i = 0; i != shape_len; ++i) {
@ -183,7 +183,7 @@ OrtStatus* CreateTensorImpl(const size_t* shape, size_t shape_len, OrtAllocator*
* this function will create a copy of the allocator info
*/
template <typename T>
OrtStatus* CreateTensorImpl(const size_t* shape, size_t shape_len, const OrtAllocatorInfo* info,
OrtStatus* CreateTensorImpl(const int64_t* shape, size_t shape_len, const OrtAllocatorInfo* info,
void* p_data, size_t p_data_len, std::unique_ptr<Tensor>* out) {
size_t elem_count = 1;
std::vector<int64_t> shapes(shape_len);
@ -209,7 +209,7 @@ OrtStatus* CreateTensorImpl(const size_t* shape, size_t shape_len, const OrtAllo
* this function will create a copy of the allocator info
*/
ORT_API_STATUS_IMPL(OrtCreateTensorWithDataAsOrtValue, _In_ const OrtAllocatorInfo* info,
_Inout_ void* p_data, size_t p_data_len, _In_ const size_t* shape, size_t shape_len,
_Inout_ void* p_data, size_t p_data_len, _In_ const int64_t* shape, size_t shape_len,
ONNXTensorElementDataType type, _Out_ OrtValue** out) {
API_IMPL_BEGIN
std::unique_ptr<Tensor> tensor;
@ -275,7 +275,7 @@ ORT_API_STATUS_IMPL(OrtCreateTensorWithDataAsOrtValue, _In_ const OrtAllocatorIn
}
ORT_API_STATUS_IMPL(OrtCreateTensorAsOrtValue, _Inout_ OrtAllocator* allocator,
_In_ const size_t* shape, size_t shape_len, ONNXTensorElementDataType type,
_In_ const int64_t* shape, size_t shape_len, ONNXTensorElementDataType type,
_Out_ OrtValue** out) {
API_IMPL_BEGIN
std::unique_ptr<Tensor> tensor;
@ -796,7 +796,7 @@ OrtStatus* OrtGetValueImplSeqOfPrimitives(const MLValue* p_ml_value, int index,
using ElemType = typename T::value_type;
auto& data = p_ml_value->Get<T>();
auto& data_elem = data.at(index);
std::vector<size_t> dims = {1};
std::vector<int64_t> dims = {1};
OrtStatus* st = OrtCreateTensorAsOrtValue(allocator, dims.data(), dims.size(),
GetONNXTensorElementDataType<ElemType>(), out);
return st ? st : PopulateTensorWithData<ElemType>(*out, &data_elem, 1);
@ -830,7 +830,7 @@ static OrtStatus* OrtGetValueImplMapHelper(const MLValue* p_ml_value, int index,
using TKey = typename T::key_type;
using TVal = typename T::mapped_type;
auto& data = p_ml_value->Get<T>();
size_t num_kv_pairs = data.size();
int64_t num_kv_pairs = data.size();
switch (index) {
case 0: { // user is requesting keys
std::vector<TKey> vec;
@ -838,7 +838,7 @@ static OrtStatus* OrtGetValueImplMapHelper(const MLValue* p_ml_value, int index,
for (const auto& kv : data) {
vec.push_back(kv.first);
}
std::vector<size_t> dims{num_kv_pairs};
std::vector<int64_t> dims{num_kv_pairs};
OrtStatus* st = OrtCreateTensorAsOrtValue(allocator, dims.data(), dims.size(),
GetONNXTensorElementDataType<TKey>(), out);
return st ? st : PopulateTensorWithData<TKey>(*out, vec.data(), num_kv_pairs);
@ -849,7 +849,7 @@ static OrtStatus* OrtGetValueImplMapHelper(const MLValue* p_ml_value, int index,
for (const auto& kv : data) {
vec.push_back(kv.second);
}
std::vector<size_t> dims{num_kv_pairs};
std::vector<int64_t> dims{num_kv_pairs};
OrtStatus* st = OrtCreateTensorAsOrtValue(allocator, dims.data(), dims.size(),
GetONNXTensorElementDataType<TVal>(), out);
return st ? st : PopulateTensorWithData<TVal>(*out, vec.data(), num_kv_pairs);

2
onnxruntime/test/shared_lib/fns_candy_style_transfer.c
View file

@ -147,7 +147,7 @@ int run_inference(OrtSession* session, const char* input_file, const char* outpu
}
OrtAllocatorInfo* allocator_info;
ORT_ABORT_ON_ERROR(OrtCreateCpuAllocatorInfo(OrtArenaAllocator, OrtMemTypeDefault, &allocator_info));
const size_t input_shape[] = {1, 3, 720, 720};
const int64_t input_shape[] = {1, 3, 720, 720};
const size_t input_shape_len = sizeof(input_shape) / sizeof(input_shape[0]);
const size_t model_input_len = model_input_ele_count * sizeof(float);

18
onnxruntime/test/shared_lib/test_inference.cc
View file

@ -14,7 +14,7 @@
using namespace onnxruntime;
void RunSession(OrtAllocator* env, OrtSession* session_object,
const std::vector<size_t>& dims_x,
const std::vector<int64_t>& dims_x,
const std::vector<float>& values_x,
const std::vector<int64_t>& dims_y,
const std::vector<float>& values_y,
@ -59,7 +59,7 @@ void RunSession(OrtAllocator* env, OrtSession* session_object,
template <typename T>
void TestInference(OrtEnv* env, T model_uri,
const std::vector<size_t>& dims_x,
const std::vector<int64_t>& dims_x,
const std::vector<float>& values_x,
const std::vector<int64_t>& expected_dims_y,
const std::vector<float>& expected_values_y,
@ -110,9 +110,9 @@ void TestInference(OrtEnv* env, T model_uri,
std::unique_ptr<OrtValue, decltype(&OrtReleaseValue)> value_y(nullptr, OrtReleaseValue);
{
std::vector<OrtValue*> allocated_outputs(1);
std::vector<size_t> dims_y(expected_dims_y.size());
std::vector<int64_t> dims_y(expected_dims_y.size());
for (size_t i = 0; i != expected_dims_y.size(); ++i) {
dims_y[i] = static_cast<size_t>(expected_dims_y[i]);
dims_y[i] = expected_dims_y[i];
}
allocated_outputs[0] =
@ -141,7 +141,7 @@ class CApiTestWithProvider : public CApiTest,
TEST_P(CApiTestWithProvider, simple) {
// simple inference test
// prepare inputs
std::vector<size_t> dims_x = {3, 2};
std::vector<int64_t> dims_x = {3, 2};
std::vector<float> values_x = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f};
// prepare expected inputs and outputs
@ -227,7 +227,7 @@ struct MyCustomOp : OrtCustomOp {
TEST_F(CApiTest, custom_op_handler) {
std::cout << "Running custom op inference" << std::endl;
std::vector<size_t> dims_x = {3, 2};
std::vector<int64_t> dims_x = {3, 2};
std::vector<float> values_x = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f};
// prepare expected inputs and outputs
@ -253,7 +253,7 @@ TEST_F(CApiTest, create_session_without_session_option) {
#endif
TEST_F(CApiTest, create_tensor) {
const char* s[] = {"abc", "kmp"};
size_t expected_len = 2;
int64_t expected_len = 2;
std::unique_ptr<MockedOrtAllocator> default_allocator(std::make_unique<MockedOrtAllocator>());
{
std::unique_ptr<OrtValue, decltype(&OrtReleaseValue)> tensor(
@ -266,7 +266,7 @@ TEST_F(CApiTest, create_tensor) {
ORT_THROW_ON_ERROR(OrtGetTensorShapeAndType(tensor.get(), &shape_info_ptr));
shape_info.reset(shape_info_ptr);
}
size_t len = static_cast<size_t>(OrtGetTensorShapeElementCount(shape_info.get()));
int64_t len = OrtGetTensorShapeElementCount(shape_info.get());
ASSERT_EQ(len, expected_len);
std::vector<int64_t> shape_array(len);
@ -284,7 +284,7 @@ TEST_F(CApiTest, create_tensor_with_data) {
constexpr size_t values_length = sizeof(values) / sizeof(values[0]);
OrtAllocatorInfo* info;
ORT_THROW_ON_ERROR(OrtCreateAllocatorInfo("Cpu", OrtDeviceAllocator, 0, OrtMemTypeDefault, &info));
std::vector<size_t> dims = {4};
std::vector<int64_t> dims = {4};
std::unique_ptr<OrtValue, decltype(&OrtReleaseValue)> tensor(
OrtCreateTensorWithDataAsOrtValue(info, values, values_length * sizeof(float), dims, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT), OrtReleaseValue);
OrtReleaseAllocatorInfo(info);

6
onnxruntime/test/shared_lib/test_nontensor_types.cc
View file

@ -40,7 +40,7 @@ TEST_F(CApiTest, CreateGetVectorOfMapsInt64Float) { // support zipmap output ty
const int NUM_KV_PAIRS = 4;
std::vector<OrtValue*> in(N);
std::vector<int64_t> keys{3, 1, 2, 0};
std::vector<size_t> dims = {4};
std::vector<int64_t> dims = {4};
std::vector<float> values{3.0f, 1.0f, 2.f, 0.f};
for (int i = 0; i < N; ++i) {
// create key tensor
@ -147,11 +147,11 @@ TEST_F(CApiTest, CreateGetVectorOfMapsStringFloat) { // support zipmap output t
RelAllocations<OrtStatus> rels(&OrtReleaseStatus);
const int N = 3;
const size_t NUM_KV_PAIRS = 4;
const int64_t NUM_KV_PAIRS = 4;
std::vector<OrtValue*> in(N);
const char* keys_arr[NUM_KV_PAIRS] = {"abc", "def", "ghi", "jkl"};
std::vector<std::string> keys{keys_arr, keys_arr + NUM_KV_PAIRS};
std::vector<size_t> dims = {NUM_KV_PAIRS};
std::vector<int64_t> dims = {NUM_KV_PAIRS};
std::vector<float> values{3.0f, 1.0f, 2.f, 0.f};
for (int i = 0; i < N; ++i) {
// create key tensor