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https://github.com/saymrwulf/onnxruntime.git
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c3db1d3628
A couple of places in onnxruntime used `float_t` data type alias as an
alternative to `float`. However, this is not entirely correct, since
`float_t` is an implementation-defined type alias, which may be `float`,
`double`, `long double` or some other implementation-defined data type,
depending on the state of the internal `FLT_EVAL_METHOD` macro:
https://en.cppreference.com/w/c/numeric/math/float_t
On most major platforms and compilers (clang, GCC, MSVC) this is only a
cosmetic change and will not lead to any changes. However, icpx compiler
(and legacy icc) tends to substitute `float_t` with `long double`,
resulting in a linker error (unresolved reference) to the base onnx
library, that only contains the `ParseData` function for `float` and
`double` as in
[here](9264e09367/onnx/defs/tensor_proto_util.cc (L133-L134)).
Overall, this PR cleans up the implementation-defined behaviour and
enables building onnxruntime with icpx.
118 lines
4.2 KiB
Text
118 lines
4.2 KiB
Text
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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#import "OnnxruntimeModule.h"
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#import "FakeRCTBlobManager.h"
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#import "TensorHelper.h"
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#import <XCTest/XCTest.h>
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#import <onnxruntime/onnxruntime_cxx_api.h>
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@interface OnnxruntimeModuleTest : XCTestCase
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@end
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@implementation OnnxruntimeModuleTest
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FakeRCTBlobManager *fakeBlobManager = nil;
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+ (void)initialize {
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if (self == [OnnxruntimeModuleTest class]) {
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fakeBlobManager = [FakeRCTBlobManager new];
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}
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}
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- (void)testOnnxruntimeModule {
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NSBundle *bundle = [NSBundle bundleForClass:[OnnxruntimeModuleTest class]];
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NSString *dataPath = [bundle pathForResource:@"test_types_float" ofType:@"ort"];
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NSString *sessionKey = @"";
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NSString *sessionKey2 = @"";
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OnnxruntimeModule *onnxruntimeModule = [OnnxruntimeModule new];
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[onnxruntimeModule setBlobManager:fakeBlobManager];
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{
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// test loadModelFromBuffer()
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NSMutableDictionary *options = [NSMutableDictionary dictionary];
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NSData *fileData = [NSData dataWithContentsOfFile:dataPath];
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NSDictionary *resultMap = [onnxruntimeModule loadModelFromBuffer:fileData options:options];
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sessionKey = resultMap[@"key"];
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NSArray *inputNames = resultMap[@"inputNames"];
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XCTAssertEqual([inputNames count], 1);
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XCTAssertEqualObjects(inputNames[0], @"input");
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NSArray *outputNames = resultMap[@"outputNames"];
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XCTAssertEqual([outputNames count], 1);
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XCTAssertEqualObjects(outputNames[0], @"output");
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// test loadModel()
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NSDictionary *resultMap2 = [onnxruntimeModule loadModel:dataPath options:options];
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sessionKey2 = resultMap2[@"key"];
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NSArray *inputNames2 = resultMap2[@"inputNames"];
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XCTAssertEqual([inputNames2 count], 1);
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XCTAssertEqualObjects(inputNames2[0], @"input");
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NSArray *outputNames2 = resultMap2[@"outputNames"];
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XCTAssertEqual([outputNames2 count], 1);
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XCTAssertEqualObjects(outputNames2[0], @"output");
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}
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// test run()
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{
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NSMutableDictionary *inputTensorMap = [NSMutableDictionary dictionary];
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// dims
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NSArray *dims = @[ [NSNumber numberWithLong:1], [NSNumber numberWithLong:5] ];
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inputTensorMap[@"dims"] = dims;
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// type
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inputTensorMap[@"type"] = JsTensorTypeFloat;
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// data
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std::array<float, 5> outValues{std::numeric_limits<float>::min(), 1.0f, -2.0f, 3.0f,
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std::numeric_limits<float>::max()};
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const NSInteger byteBufferSize = outValues.size() * sizeof(float);
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unsigned char *byteBuffer = static_cast<unsigned char *>(malloc(byteBufferSize));
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NSData *byteBufferRef = [NSData dataWithBytesNoCopy:byteBuffer length:byteBufferSize];
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float *floatPtr = (float *)[byteBufferRef bytes];
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for (NSUInteger i = 0; i < outValues.size(); ++i) {
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*floatPtr++ = outValues[i];
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}
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floatPtr = (float *)[byteBufferRef bytes];
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XCTAssertNotNil(fakeBlobManager);
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inputTensorMap[@"data"] = [fakeBlobManager testCreateData:byteBufferRef];
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NSMutableDictionary *inputDataMap = [NSMutableDictionary dictionary];
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inputDataMap[@"input"] = inputTensorMap;
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NSMutableDictionary *options = [NSMutableDictionary dictionary];
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NSMutableArray *output = [NSMutableArray array];
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[output addObject:@"output"];
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NSDictionary *resultMap = [onnxruntimeModule run:sessionKey input:inputDataMap output:output options:options];
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NSDictionary *resultMap2 = [onnxruntimeModule run:sessionKey2 input:inputDataMap output:output options:options];
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// Compare output & input, but data.blobId is different
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// dims
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XCTAssertTrue([[resultMap objectForKey:@"output"][@"dims"] isEqualToArray:inputTensorMap[@"dims"]]);
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XCTAssertTrue([[resultMap2 objectForKey:@"output"][@"dims"] isEqualToArray:inputTensorMap[@"dims"]]);
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// type
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XCTAssertEqual([resultMap objectForKey:@"output"][@"type"], JsTensorTypeFloat);
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XCTAssertEqual([resultMap2 objectForKey:@"output"][@"type"], JsTensorTypeFloat);
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// data ({ blobId, offset, size })
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XCTAssertEqual([[resultMap objectForKey:@"output"][@"data"][@"offset"] longValue], 0);
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XCTAssertEqual([[resultMap2 objectForKey:@"output"][@"data"][@"size"] longValue], byteBufferSize);
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}
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// test dispose
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{
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[onnxruntimeModule dispose:sessionKey];
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[onnxruntimeModule dispose:sessionKey2];
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}
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}
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@end
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