add objectivec/test and objectivec/docs
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edgchen1
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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#import <XCTest/XCTest.h>
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#import "ort_checkpoint.h"
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#import "ort_training_session.h"
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#import "ort_env.h"
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#import "ort_session.h"
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#import "ort_value.h"
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#import "test/test_utils.h"
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#import "test/assertion_utils.h"
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NS_ASSUME_NONNULL_BEGIN
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@interface ORTTrainingSessionTest : XCTestCase
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@property(readonly, nullable) ORTEnv* ortEnv;
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@property(readonly, nullable) ORTCheckpoint* checkpoint;
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@property(readonly, nullable) ORTTrainingSession* session;
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@end
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@implementation ORTTrainingSessionTest
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- (void)setUp {
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[super setUp];
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self.continueAfterFailure = NO;
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NSError* err = nil;
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_ortEnv = [[ORTEnv alloc] initWithLoggingLevel:ORTLoggingLevelWarning
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error:&err];
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ORTAssertNullableResultSuccessful(_ortEnv, err);
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_checkpoint = [[ORTCheckpoint alloc] initWithPath:[ORTTrainingSessionTest
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getFilePathFromName:@"checkpoint.ckpt"]
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error:&err];
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ORTAssertNullableResultSuccessful(_checkpoint, err);
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_session = [self makeTrainingSessionWithCheckpoint:_checkpoint];
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}
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+ (NSString*)getFilePathFromName:(NSString*)name {
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NSBundle* bundle = [NSBundle bundleForClass:[ORTTrainingSessionTest class]];
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NSString* path = [[bundle resourcePath] stringByAppendingPathComponent:name];
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return path;
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}
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+ (NSMutableData*)loadTensorDataFromFile:(NSString*)filePath skipHeader:(BOOL)skipHeader {
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NSError* error = nil;
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NSString* fileContents = [NSString stringWithContentsOfFile:filePath
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encoding:NSUTF8StringEncoding
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error:&error];
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ORTAssertNullableResultSuccessful(fileContents, error);
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NSArray<NSString*>* lines = [fileContents componentsSeparatedByCharactersInSet:[NSCharacterSet newlineCharacterSet]];
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if (skipHeader) {
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lines = [lines subarrayWithRange:NSMakeRange(1, lines.count - 1)];
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}
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NSArray<NSString*>* dataArray = [lines[0] componentsSeparatedByCharactersInSet:
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[NSCharacterSet characterSetWithCharactersInString:@",[] "]];
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NSMutableData* tensorData = [NSMutableData data];
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for (NSString* str in dataArray) {
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if (str.length > 0) {
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float value = [str floatValue];
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[tensorData appendBytes:&value length:sizeof(float)];
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}
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}
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return tensorData;
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}
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- (ORTTrainingSession*)makeTrainingSessionWithCheckpoint:(ORTCheckpoint*)checkpoint {
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NSError* error = nil;
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ORTSessionOptions* sessionOptions = [[ORTSessionOptions alloc] initWithError:&error];
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ORTAssertNullableResultSuccessful(sessionOptions, error);
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ORTTrainingSession* session = [[ORTTrainingSession alloc]
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initWithEnv:self.ortEnv
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sessionOptions:sessionOptions
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checkpoint:checkpoint
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trainModelPath:[ORTTrainingSessionTest getFilePathFromName:@"training_model.onnx"]
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evalModelPath:[ORTTrainingSessionTest getFilePathFromName:@"eval_model.onnx"]
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optimizerModelPath:[ORTTrainingSessionTest getFilePathFromName:@"adamw.onnx"]
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error:&error];
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ORTAssertNullableResultSuccessful(session, error);
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return session;
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}
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- (void)testInitTrainingSession {
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NSError* error = nil;
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// check that inputNames contains input-0
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NSArray<NSString*>* inputNames = [self.session getTrainInputNamesWithError:&error];
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ORTAssertNullableResultSuccessful(inputNames, error);
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XCTAssertTrue(inputNames.count > 0);
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XCTAssertTrue([inputNames containsObject:@"input-0"]);
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// check that outNames contains onnx::loss::21273
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NSArray<NSString*>* outputNames = [self.session getTrainOutputNamesWithError:&error];
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ORTAssertNullableResultSuccessful(outputNames, error);
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XCTAssertTrue(outputNames.count > 0);
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XCTAssertTrue([outputNames containsObject:@"onnx::loss::21273"]);
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}
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- (void)testInitTrainingSessionWithEval {
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NSError* error = nil;
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// check that inputNames contains input-0
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NSArray<NSString*>* inputNames = [self.session getEvalInputNamesWithError:&error];
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ORTAssertNullableResultSuccessful(inputNames, error);
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XCTAssertTrue(inputNames.count > 0);
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XCTAssertTrue([inputNames containsObject:@"input-0"]);
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// check that outNames contains onnx::loss::21273
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NSArray<NSString*>* outputNames = [self.session getEvalOutputNamesWithError:&error];
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ORTAssertNullableResultSuccessful(outputNames, error);
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XCTAssertTrue(outputNames.count > 0);
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XCTAssertTrue([outputNames containsObject:@"onnx::loss::21273"]);
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}
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- (void)runTrainStep {
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// load input and expected output
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NSError* error = nil;
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NSMutableData* expectedOutput = [ORTTrainingSessionTest loadTensorDataFromFile:[ORTTrainingSessionTest
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getFilePathFromName:@"loss_1.out"]
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skipHeader:YES];
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NSMutableData* input = [ORTTrainingSessionTest loadTensorDataFromFile:[ORTTrainingSessionTest
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getFilePathFromName:@"input-0.in"]
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skipHeader:YES];
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int32_t labels[] = {1, 1};
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// create ORTValue array for input and labels
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NSMutableArray<ORTValue*>* inputValues = [NSMutableArray array];
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ORTValue* inputTensor = [[ORTValue alloc] initWithTensorData:input
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elementType:ORTTensorElementDataTypeFloat
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shape:@[ @2, @784 ]
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error:&error];
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ORTAssertNullableResultSuccessful(inputTensor, error);
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[inputValues addObject:inputTensor];
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ORTValue* labelTensor = [[ORTValue alloc] initWithTensorData:[NSMutableData dataWithBytes:labels
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length:sizeof(labels)]
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elementType:ORTTensorElementDataTypeInt32
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shape:@[ @2 ]
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error:&error];
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ORTAssertNullableResultSuccessful(labelTensor, error);
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[inputValues addObject:labelTensor];
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NSArray<ORTValue*>* outputs = [self.session trainStepWithInputValues:inputValues error:&error];
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ORTAssertNullableResultSuccessful(outputs, error);
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XCTAssertTrue(outputs.count > 0);
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BOOL result = [self.session lazyResetGradWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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outputs = [self.session trainStepWithInputValues:inputValues error:&error];
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ORTAssertNullableResultSuccessful(outputs, error);
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XCTAssertTrue(outputs.count > 0);
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ORTValue* outputValue = outputs[0];
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ORTValueTypeInfo* typeInfo = [outputValue typeInfoWithError:&error];
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ORTAssertNullableResultSuccessful(typeInfo, error);
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XCTAssertEqual(typeInfo.type, ORTValueTypeTensor);
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XCTAssertNotNil(typeInfo.tensorTypeAndShapeInfo);
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ORTTensorTypeAndShapeInfo* tensorInfo = [outputValue tensorTypeAndShapeInfoWithError:&error];
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ORTAssertNullableResultSuccessful(tensorInfo, error);
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XCTAssertEqual(tensorInfo.elementType, ORTTensorElementDataTypeFloat);
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NSMutableData* tensorData = [outputValue tensorDataWithError:&error];
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ORTAssertNullableResultSuccessful(tensorData, error);
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ORTAssertEqualFloatArrays(test_utils::getFloatArrayFromData(tensorData),
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test_utils::getFloatArrayFromData(expectedOutput));
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}
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- (void)testTrainStepOutput {
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[self runTrainStep];
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}
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- (void)testOptimizerStep {
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// load input and expected output
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NSError* error = nil;
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NSMutableData* expectedOutput1 = [ORTTrainingSessionTest loadTensorDataFromFile:[ORTTrainingSessionTest
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getFilePathFromName:@"loss_1.out"]
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skipHeader:YES];
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NSMutableData* expectedOutput2 = [ORTTrainingSessionTest loadTensorDataFromFile:[ORTTrainingSessionTest
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getFilePathFromName:@"loss_2.out"]
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skipHeader:YES];
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NSMutableData* input = [ORTTrainingSessionTest loadTensorDataFromFile:[ORTTrainingSessionTest
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getFilePathFromName:@"input-0.in"]
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skipHeader:YES];
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int32_t labels[] = {1, 1};
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// create ORTValue array for input and labels
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NSMutableArray<ORTValue*>* inputValues = [NSMutableArray array];
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ORTValue* inputTensor = [[ORTValue alloc] initWithTensorData:input
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elementType:ORTTensorElementDataTypeFloat
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shape:@[ @2, @784 ]
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error:&error];
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ORTAssertNullableResultSuccessful(inputTensor, error);
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[inputValues addObject:inputTensor];
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ORTValue* labelTensor = [[ORTValue alloc] initWithTensorData:[NSMutableData dataWithBytes:labels
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length:sizeof(labels)]
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elementType:ORTTensorElementDataTypeInt32
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shape:@[ @2 ]
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error:&error];
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ORTAssertNullableResultSuccessful(labelTensor, error);
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[inputValues addObject:labelTensor];
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// run train step, optimizer steps and check loss
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NSArray<ORTValue*>* outputs = [self.session trainStepWithInputValues:inputValues error:&error];
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ORTAssertNullableResultSuccessful(outputs, error);
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NSMutableData* loss = [outputs[0] tensorDataWithError:&error];
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ORTAssertNullableResultSuccessful(loss, error);
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ORTAssertEqualFloatArrays(test_utils::getFloatArrayFromData(loss),
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test_utils::getFloatArrayFromData(expectedOutput1));
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BOOL result = [self.session lazyResetGradWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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outputs = [self.session trainStepWithInputValues:inputValues error:&error];
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ORTAssertNullableResultSuccessful(outputs, error);
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loss = [outputs[0] tensorDataWithError:&error];
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ORTAssertNullableResultSuccessful(loss, error);
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ORTAssertEqualFloatArrays(test_utils::getFloatArrayFromData(loss),
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test_utils::getFloatArrayFromData(expectedOutput1));
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result = [self.session optimizerStepWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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outputs = [self.session trainStepWithInputValues:inputValues error:&error];
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ORTAssertNullableResultSuccessful(outputs, error);
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loss = [outputs[0] tensorDataWithError:&error];
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ORTAssertNullableResultSuccessful(loss, error);
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ORTAssertEqualFloatArrays(test_utils::getFloatArrayFromData(loss),
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test_utils::getFloatArrayFromData(expectedOutput2));
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}
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- (void)testSetLearningRate {
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NSError* error = nil;
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float learningRate = 0.1f;
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BOOL result = [self.session setLearningRate:learningRate error:&error];
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ORTAssertBoolResultSuccessful(result, error);
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float actualLearningRate = [self.session getLearningRateWithError:&error];
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ORTAssertEqualFloatAndNoError(learningRate, actualLearningRate, error);
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}
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- (void)testLinearLRScheduler {
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NSError* error = nil;
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float learningRate = 0.1f;
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BOOL result = [self.session registerLinearLRSchedulerWithWarmupStepCount:2
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totalStepCount:4
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initialLr:learningRate
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error:&error];
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ORTAssertBoolResultSuccessful(result, error);
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[self runTrainStep];
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result = [self.session optimizerStepWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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result = [self.session schedulerStepWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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ORTAssertEqualFloatAndNoError(0.05f, [self.session getLearningRateWithError:&error], error);
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result = [self.session optimizerStepWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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result = [self.session schedulerStepWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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ORTAssertEqualFloatAndNoError(0.1f, [self.session getLearningRateWithError:&error], error);
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result = [self.session optimizerStepWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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result = [self.session schedulerStepWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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ORTAssertEqualFloatAndNoError(0.05f, [self.session getLearningRateWithError:&error], error);
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result = [self.session optimizerStepWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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result = [self.session schedulerStepWithError:&error];
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ORTAssertBoolResultSuccessful(result, error);
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ORTAssertEqualFloatAndNoError(0.0f, [self.session getLearningRateWithError:&error], error);
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}
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- (void)testExportModelForInference {
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NSError* error = nil;
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NSString* inferenceModelPath = [test_utils::createTemporaryDirectory(self)
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stringByAppendingPathComponent:@"inference_model.onnx"];
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XCTAssertNotNil(inferenceModelPath);
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NSArray<NSString*>* graphOutputNames = [NSArray arrayWithObjects:@"output-0", nil];
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BOOL result = [self.session exportModelForInferenceWithOutputPath:inferenceModelPath
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graphOutputNames:graphOutputNames
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error:&error];
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ORTAssertBoolResultSuccessful(result, error);
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XCTAssertTrue([[NSFileManager defaultManager] fileExistsAtPath:inferenceModelPath]);
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[self addTeardownBlock:^{
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NSError* error = nil;
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[[NSFileManager defaultManager] removeItemAtPath:inferenceModelPath error:&error];
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}];
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}
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- (void)testToBuffer {
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NSError* error = nil;
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ORTValue* buffer = [self.session toBufferWithTrainable:YES error:&error];
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ORTAssertNullableResultSuccessful(buffer, error);
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ORTValueTypeInfo* typeInfo = [buffer typeInfoWithError:&error];
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ORTAssertNullableResultSuccessful(typeInfo, error);
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XCTAssertEqual(typeInfo.type, ORTValueTypeTensor);
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XCTAssertNotNil(typeInfo.tensorTypeAndShapeInfo);
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}
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- (void)testFromBuffer {
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NSError* error = nil;
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ORTValue* buffer = [self.session toBufferWithTrainable:YES error:&error];
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ORTAssertNullableResultSuccessful(buffer, error);
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BOOL result = [self.session fromBufferWithValue:buffer error:&error];
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ORTAssertBoolResultSuccessful(result, error);
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}
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- (void)tearDown {
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_session = nil;
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_checkpoint = nil;
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_ortEnv = nil;
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[super tearDown];
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}
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@end
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NS_ASSUME_NONNULL_END
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