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[rn] Support UINT8 type for onnxruntime-react-native on iOS (#13210)

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### Description
<!-- Describe your changes. -->

As title.


### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->

Uint8 type might be required for some model used in sample application.
To match supported data types for onnxruntime-react-native for Android.

Co-authored-by: rachguo <rachguo@rachguos-Mac-mini.local>
Co-authored-by: rachguo <rachguo@rachguos-Mini.attlocal.net>
This commit is contained in:
Rachel Guo 2022-10-06 11:35:25 -07:00 committed by GitHub
parent b09dd11ece
commit 814e5cfa4c
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GPG key ID: 4AEE18F83AFDEB23
4 changed files with 24 additions and 2 deletions
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js/react_native/ios/OnnxruntimeModuleTest/Resources/test_types_uint8.ort Normal file
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16
js/react_native/ios/OnnxruntimeModuleTest/TensorHelperTest.mm
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@ -73,6 +73,14 @@ static void testCreateInputTensorT(const std::array<T, 3> &outValues, std::funct
testCreateInputTensorT<bool>(outValues, convert, ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL, JsTensorTypeBool);
}
- (void)testCreateInputTensorUInt8 {
std::array<uint8_t, 3> outValues{std::numeric_limits<uint8_t>::min(), 2, std::numeric_limits<uint8_t>::max()};
std::function<NSNumber *(uint8_t value)> convert = [](uint8_t value) {
return [NSNumber numberWithUnsignedChar:value];
};
testCreateInputTensorT<uint8_t>(outValues, convert, ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8, JsTensorTypeUnsignedByte);
}
- (void)testCreateInputTensorInt8 {
std::array<int8_t, 3> outValues{std::numeric_limits<int8_t>::min(), 2, std::numeric_limits<int8_t>::max()};
std::function<NSNumber *(int8_t value)> convert = [](int8_t value) { return [NSNumber numberWithChar:value]; };
@ -225,6 +233,14 @@ static void testCreateOutputTensorT(const std::array<T, 5> &outValues, std::func
testCreateOutputTensorT<bool>(outValues, convert, JsTensorTypeBool, @"test_types_bool", @"onnx");
}
- (void)testCreateOutputTensorUInt8 {
std::array<uint8_t, 5> outValues{std::numeric_limits<uint8_t>::min(), 1, 2, 3, std::numeric_limits<uint8_t>::max()};
std::function<NSNumber *(uint8_t value)> convert = [](uint8_t value) {
return [NSNumber numberWithUnsignedChar:value];
};
testCreateOutputTensorT<uint8_t>(outValues, convert, JsTensorTypeUnsignedByte, @"test_types_uint8", @"ort");
}
- (void)testCreateOutputTensorInt8 {
std::array<int8_t, 5> outValues{std::numeric_limits<int8_t>::min(), 1, -2, 3, std::numeric_limits<int8_t>::max()};
std::function<NSNumber *(int8_t value)> convert = [](int8_t value) { return [NSNumber numberWithChar:value]; };

1
js/react_native/ios/TensorHelper.h
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@ -13,6 +13,7 @@
* Supported tensor data type
*/
FOUNDATION_EXPORT NSString* const JsTensorTypeBool;
FOUNDATION_EXPORT NSString* const JsTensorTypeUnsignedByte;
FOUNDATION_EXPORT NSString* const JsTensorTypeByte;
FOUNDATION_EXPORT NSString* const JsTensorTypeShort;
FOUNDATION_EXPORT NSString* const JsTensorTypeInt;

9
js/react_native/ios/TensorHelper.mm
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@ -10,6 +10,7 @@
* Supported tensor data type
*/
NSString *const JsTensorTypeBool = @"bool";
NSString *const JsTensorTypeUnsignedByte = @"uint8";
NSString *const JsTensorTypeByte = @"int8";
NSString *const JsTensorTypeShort = @"int16";
NSString *const JsTensorTypeInt = @"int32";
@ -137,6 +138,8 @@ static Ort::Value createInputTensorT(OrtAllocator *ortAllocator, const std::vect
switch (tensorType) {
case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT:
return createInputTensorT<float_t>(ortAllocator, dims, buffer, allocations);
case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8:
return createInputTensorT<uint8_t>(ortAllocator, dims, buffer, allocations);
case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8:
return createInputTensorT<int8_t>(ortAllocator, dims, buffer, allocations);
case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16:
@ -150,7 +153,6 @@ static Ort::Value createInputTensorT(OrtAllocator *ortAllocator, const std::vect
case ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE:
return createInputTensorT<double_t>(ortAllocator, dims, buffer, allocations);
case ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED:
case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8:
case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16:
case ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING:
case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16:
@ -182,6 +184,8 @@ template <typename T> static NSString *createOutputTensorT(const Ort::Value &ten
switch (tensorType) {
case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT:
return createOutputTensorT<float_t>(tensor);
case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8:
return createOutputTensorT<uint8_t>(tensor);
case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8:
return createOutputTensorT<int8_t>(tensor);
case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16:
@ -195,7 +199,6 @@ template <typename T> static NSString *createOutputTensorT(const Ort::Value &ten
case ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE:
return createOutputTensorT<double_t>(tensor);
case ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED:
case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8:
case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16:
case ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING:
case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16:
@ -219,6 +222,7 @@ NSDictionary *OnnxTensorTypeToJsTensorTypeMap;
+ (void)initialize {
JsTensorTypeToOnnxTensorTypeMap = @{
JsTensorTypeFloat : @(ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT),
JsTensorTypeUnsignedByte : @(ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8),
JsTensorTypeByte : @(ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8),
JsTensorTypeShort : @(ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16),
JsTensorTypeInt : @(ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32),
@ -230,6 +234,7 @@ NSDictionary *OnnxTensorTypeToJsTensorTypeMap;
OnnxTensorTypeToJsTensorTypeMap = @{
@(ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) : JsTensorTypeFloat,
@(ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8) : JsTensorTypeUnsignedByte,
@(ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8) : JsTensorTypeByte,
@(ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16) : JsTensorTypeShort,
@(ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32) : JsTensorTypeInt,