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Move ExecutorchRuntimeValueSupport and ExecutorchRuntimeBridge to xplat
Differential Revision: D70825991 Pull Request resolved: pytorch#9244
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‎extension/apple/ExecutorchRuntimeBridge/ExecutorchRuntimeBridge/Exported/Data/ExecutorchRuntimeTensorValue.h

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// (c) Meta Platforms, Inc. and affiliates. Confidential and proprietary.
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#ifdef __cplusplus
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#import <executorch/extension/module/module.h>
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#import <executorch/runtime/core/evalue.h>
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#endif
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#import <ModelRunnerDataKit/ModelRunnerDataKit-Swift.h>
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NS_ASSUME_NONNULL_BEGIN
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@interface ExecutorchRuntimeTensorValue : NSObject <ModelRuntimeTensorValueBridging>
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- (instancetype)init NS_UNAVAILABLE;
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+ (instancetype)new NS_UNAVAILABLE;
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- (instancetype)initWithFloatArray:(NSArray<NSNumber *> *)floatArray shape:(NSArray<NSNumber *> *)sizes NS_SWIFT_NAME(init(floatArray:shape:));
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#ifdef __cplusplus
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- (nullable instancetype)initWithTensor:(torch::executor::Tensor)tensor error:(NSError * _Nullable * _Nullable)error;
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- (instancetype)initWithData:(std::vector<float>)floatData
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shape:(std::vector<int32_t>)shape NS_DESIGNATED_INITIALIZER;
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- (torch::executor::Tensor)backedValue;
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#endif
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@end
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NS_ASSUME_NONNULL_END

‎extension/apple/ExecutorchRuntimeBridge/ExecutorchRuntimeBridge/Exported/Data/ExecutorchRuntimeTensorValue.mm

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// (c) Meta Platforms, Inc. and affiliates. Confidential and proprietary.
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#import "ExecutorchRuntimeTensorValue.h"
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#import <memory>
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#import <executorch/extension/module/module.h>
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using torch::executor::TensorImpl;
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using torch::executor::ScalarType;
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@implementation ExecutorchRuntimeTensorValue
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{
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std::unique_ptr<TensorImpl> _tensor;
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// TensorImpl DOES NOT take ownership.
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// This float vector is what keeps the data in memory.
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std::vector<float> _floatData;
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std::vector<int32_t> _shape;
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}
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- (instancetype)initWithData:(std::vector<float>)floatData
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shape:(std::vector<int32_t>)shape
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{
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if (self = [super init]) {
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_floatData.assign(floatData.begin(), floatData.end());
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_shape.assign(shape.begin(), shape.end());
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_tensor = std::make_unique<TensorImpl>(ScalarType::Float, std::size(_shape), _shape.data(), _floatData.data());
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}
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return self;
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}
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- (instancetype)initWithFloatArray:(NSArray<NSNumber *> *)floatArray shape:(NSArray<NSNumber *> *)shape
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{
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std::vector<float> floatVector;
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std::vector<int32_t> shapeVector;
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floatVector.reserve(floatArray.count);
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for (int i = 0; i < floatArray.count; i++) {
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floatVector.push_back([floatArray[i] floatValue]);
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}
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shapeVector.reserve(shape.count);
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for (int i = 0; i < shape.count; i++) {
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shapeVector.push_back([shape[i] intValue]);
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}
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return [self initWithData:floatVector shape:shapeVector];
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}
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- (nullable instancetype)initWithTensor:(torch::executor::Tensor)tensor error:(NSError * _Nullable * _Nullable)error
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{
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if (tensor.scalar_type() != ScalarType::Float) {
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if (error) {
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*error = [ModelRuntimeValueErrorFactory invalidType:[NSString stringWithFormat:@"torch::executor::ScalarType::%hhd", tensor.scalar_type()] expectedType:@"torch::executor::ScalarType::Float"];
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}
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return nil;
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}
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std::vector<float> floatVector;
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std::vector<int32_t> shapeVector;
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shapeVector.assign(tensor.sizes().begin(), tensor.sizes().end());
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floatVector.assign(tensor.const_data_ptr<float>(), tensor.const_data_ptr<float>() + tensor.numel());
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return [self initWithData:floatVector shape:shapeVector];
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}
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- (nullable ModelRuntimeTensorValueBridgingTuple *)floatRepresentationAndReturnError:(NSError * _Nullable * _Nullable)error
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{
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if (_tensor->scalar_type() == torch::executor::ScalarType::Float) {
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const auto *tensorPtr = _tensor->data<float>();
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const auto sizes = _tensor->sizes();
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std::vector<float> tensorVec(tensorPtr, tensorPtr + _tensor->numel());
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std::vector<int32_t> tensorSizes(sizes.begin(), sizes.end());
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NSMutableArray<NSNumber *> *floatArray = [[NSMutableArray alloc] initWithCapacity:tensorVec.size()];
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for (float &i : tensorVec) {
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[floatArray addObject:@(i)];
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}
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NSMutableArray<NSNumber *> *sizesArray = [[NSMutableArray alloc] initWithCapacity:tensorSizes.size()];
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for (int &tensorSize : tensorSizes) {
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[sizesArray addObject:@(tensorSize)];
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}
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return [[ModelRuntimeTensorValueBridgingTuple alloc] initWithFloatArray:floatArray shape:sizesArray];
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}
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if (error) {
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*error = [ModelRuntimeValueErrorFactory
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invalidType:[NSString stringWithFormat:@"torch::executor::ScalarType::%hhd", _tensor->scalar_type()]
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expectedType:@"torch::executor::ScalarType::Float"];
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}
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return nil;
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}
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- (torch::executor::Tensor)backedValue
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{
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return torch::executor::Tensor(_tensor.get());
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}
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@end

‎extension/apple/ExecutorchRuntimeBridge/ExecutorchRuntimeBridge/Exported/Data/ExecutorchRuntimeValue.h

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// (c) Meta Platforms, Inc. and affiliates. Confidential and proprietary.
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#ifdef __cplusplus
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#import <executorch/extension/module/module.h>
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#import <executorch/runtime/core/evalue.h>
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#endif
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#import <ModelRunnerDataKit/ModelRunnerDataKit-Swift.h>
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#import "ExecutorchRuntimeTensorValue.h"
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NS_ASSUME_NONNULL_BEGIN
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@interface ExecutorchRuntimeValue : NSObject <ModelRuntimeValueBridging>
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- (instancetype)init NS_UNAVAILABLE;
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+ (instancetype)new NS_UNAVAILABLE;
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- (instancetype)initWithTensor:(ExecutorchRuntimeTensorValue *)tensorValue;
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#ifdef __cplusplus
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- (instancetype)initWithEValue:(torch::executor::EValue)value NS_DESIGNATED_INITIALIZER;
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- (torch::executor::EValue)getBackedValue;
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#endif
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@end
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NS_ASSUME_NONNULL_END

‎extension/apple/ExecutorchRuntimeBridge/ExecutorchRuntimeBridge/Exported/Data/ExecutorchRuntimeValue.mm

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// (c) Meta Platforms, Inc. and affiliates. Confidential and proprietary.
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#import "ExecutorchRuntimeValue.h"
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#import <map>
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#import <vector>
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#import "ExecutorchRuntimeTensorValue.h"
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using torch::executor::EValue;
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@implementation ExecutorchRuntimeValue
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{
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EValue _value;
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// IMPORTANT
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// Tensor value keeps a reference to the original tensor value. However, the value that is wrapped by LiteInterpreterRuntimeTensorValue DOES NOT TAKE OWNERSHIP OF THE RAW DATA!
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// This means once the wrapper is deallocated, the tensor value will be deallocated as well.
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// This reference here is to keep the tensor value alive until the runtime is deallocated.
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ExecutorchRuntimeTensorValue *_tensorValue;
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}
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- (instancetype)initWithEValue:(EValue)value
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{
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if (self = [super init]) {
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_value = value;
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}
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return self;
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}
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- (instancetype)initWithTensor:(ExecutorchRuntimeTensorValue *)tensorValue
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{
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if (self = [self initWithEValue:EValue([tensorValue backedValue])]) {
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_tensorValue = tensorValue;
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}
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return self;
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}
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- (nullable NSString *)stringValueAndReturnError:(NSError * _Nullable * _Nullable)error
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{
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if (error) {
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*error = [ModelRuntimeValueErrorFactory unsupportedType:@"ExecutorchRuntimeValue doesn't support strings"];
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}
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return nil;
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}
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- (nullable id<ModelRuntimeTensorValueBridging>)tensorValueAndReturnError:(NSError * _Nullable * _Nullable)error
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{
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if (_value.isTensor()) {
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return [[ExecutorchRuntimeTensorValue alloc] initWithTensor:_value.toTensor() error:error];
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}
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if (error) {
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*error = [ModelRuntimeValueErrorFactory
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invalidType:[NSString stringWithFormat:@"Tag::%d", _value.tag]
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expectedType:@"Tag::Tensor"];
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}
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return nil;
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}
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- (EValue)getBackedValue
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{
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return _value;
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}
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- (NSArray<id<ModelRuntimeValueBridging>> *)arrayValueAndReturnError:(NSError * _Nullable * _Nullable)error
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{
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if (error) {
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*error = [ModelRuntimeValueErrorFactory unsupportedType:@"EValue doesn't support arrays"];
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}
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return nil;
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}
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@end

‎extension/apple/ExecutorchRuntimeBridge/ExecutorchRuntimeBridge/Exported/ExecutorchRuntimeEngine.h

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// (c) Meta Platforms, Inc. and affiliates. Confidential and proprietary.
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#import <Foundation/Foundation.h>
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#import "ExecutorchRuntimeValue.h"
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NS_ASSUME_NONNULL_BEGIN
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@interface ExecutorchRuntimeEngine : NSObject
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- (nonnull instancetype)init NS_UNAVAILABLE;
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+ (nonnull instancetype)new NS_UNAVAILABLE;
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- (nullable instancetype)initWithModelPath:(NSString *)modelPath
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modelMethodName:(NSString *)modelMethodName
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error:(NSError * _Nullable * _Nullable)error NS_DESIGNATED_INITIALIZER;
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- (nullable NSArray<ExecutorchRuntimeValue *> *)infer:(NSArray<ExecutorchRuntimeValue *> *)input
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error:(NSError * _Nullable * _Nullable)error NS_SWIFT_NAME(infer(input:));
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@end
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NS_ASSUME_NONNULL_END

‎extension/apple/ExecutorchRuntimeBridge/ExecutorchRuntimeBridge/Exported/ExecutorchRuntimeEngine.mm

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// (c) Meta Platforms, Inc. and affiliates. Confidential and proprietary.
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#import "ExecutorchRuntimeEngine.h"
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#import <map>
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#import <vector>
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#import <executorch/extension/module/module.h>
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static int kInitFailed = 0;
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static int kInferenceFailed = 1;
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static auto NSStringToString(NSString *string) -> std::string
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{
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const char *cStr = [string cStringUsingEncoding:NSUTF8StringEncoding];
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if (cStr) {
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return cStr;
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}
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NSData *data = [string dataUsingEncoding:NSUTF8StringEncoding allowLossyConversion:NO];
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return {reinterpret_cast<const char *>([data bytes]), [data length]};
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}
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static auto StringToNSString(const std::string &string) -> NSString *
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{
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CFStringRef cfString = CFStringCreateWithBytes(
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kCFAllocatorDefault,
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reinterpret_cast<const UInt8 *>(string.c_str()),
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string.size(),
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kCFStringEncodingUTF8,
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false
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);
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return (__bridge_transfer NSString *)cfString;
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}
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@implementation ExecutorchRuntimeEngine
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{
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NSString *_modelPath;
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NSString *_modelMethodName;
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std::unique_ptr<torch::executor::Module> _module;
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}
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- (instancetype)initWithModelPath:(NSString *)modelPath
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modelMethodName:(NSString *)modelMethodName
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error:(NSError * _Nullable * _Nullable)error
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{
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if (self = [super init]) {
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_modelPath = modelPath;
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_modelMethodName = modelMethodName;
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try {
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_module = std::make_unique<torch::executor::Module>(NSStringToString(modelPath));
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const auto e = _module->load_method(NSStringToString(modelMethodName));
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if (e != executorch::runtime::Error::Ok) {
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if (error) {
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*error = [NSError errorWithDomain:@"ExecutorchRuntimeEngine"
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code:kInitFailed
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userInfo:@{NSDebugDescriptionErrorKey : StringToNSString(std::to_string(static_cast<uint32_t>(e)))}];
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}
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return nil;
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}
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} catch (...) {
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if (error) {
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*error = [NSError errorWithDomain:@"ExecutorchRuntimeEngine"
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code:kInitFailed
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userInfo:@{NSDebugDescriptionErrorKey : @"Unknown error"}];
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}
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return nil;
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}
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}
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return self;
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}
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- (nullable NSArray<ExecutorchRuntimeValue *> *)infer:(NSArray<ExecutorchRuntimeValue *> *)input
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error:(NSError * _Nullable * _Nullable)error
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{
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try {
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std::vector<torch::executor::EValue> inputEValues;
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inputEValues.reserve(input.count);
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for (ExecutorchRuntimeValue *inputValue in input) {
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inputEValues.push_back([inputValue getBackedValue]);
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}
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const auto result = _module->execute(NSStringToString(_modelMethodName), inputEValues);
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if (!result.ok()) {
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const auto executorchError = static_cast<uint32_t>(result.error());
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if (error) {
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*error = [NSError errorWithDomain:@"ExecutorchRuntimeEngine"
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code:kInferenceFailed
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userInfo:@{NSDebugDescriptionErrorKey : StringToNSString(std::to_string(executorchError))}];
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}
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return nil;
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}
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NSMutableArray<ExecutorchRuntimeValue *> *const resultValues = [NSMutableArray new];
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for (const auto &evalue : result.get()) {
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[resultValues addObject:[[ExecutorchRuntimeValue alloc] initWithEValue:evalue]];
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}
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return resultValues;
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} catch (...) {
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if (error) {
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*error = [NSError errorWithDomain:@"LiteInterpreterRuntimeEngine"
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code:kInferenceFailed
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userInfo:@{NSDebugDescriptionErrorKey : @"Unknown error"}];
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}
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return nil;
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}
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}
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@end

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