86726adc39
Added Metal delegate and Core as subspecs of the source pod. * Removed manually written module map. The module map and umbrella header `TFLTensorFlowLite-umbrella.h` will be automatically generated with all the delegate headers. `TFLTensorFlowLite.h` is left for legacy purpose. * Modified macro to make tests work with bazel and Cocoapods. Changed some umbrella header imports to module import, `@import TFLTensorFlowLite`. PiperOrigin-RevId: 333012903 Change-Id: Ib743d7a3250b884fc406505f457ed55cea1ad20d
122 lines
4.1 KiB
Objective-C
122 lines
4.1 KiB
Objective-C
// Copyright 2020 Google Inc. All rights reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at:
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifdef COCOAPODS
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@import TFLTensorFlowLite;
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#else
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#import "tensorflow/lite/experimental/objc/apis/TFLMetalDelegate.h"
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#import "tensorflow/lite/experimental/objc/apis/TFLTensorFlowLite.h"
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#endif
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#import <Metal/MTLDevice.h>
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#import <Metal/Metal.h>
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#import <XCTest/XCTest.h>
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NS_ASSUME_NONNULL_BEGIN
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/**
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* Float model resource name.
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* The model has four inputs (a, b, c, d) and two outputs (x, y)
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* x = a + (b + c)
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* y = (b + c) + d
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*/
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static NSString* const kAddFloatModelResourceName = @"multi_add";
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/** Model resource type. */
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static NSString* const kAddModelResourceType = @"bin";
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/** Size of input and output tensors */
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static const int kTensorSize = 8 * 8 * 3;
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/** Size of channel dimension of input and output tensors */
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static const int kTensorChannels = 3;
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/** Number of input tensors */
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static const int kNumInputs = 4;
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/** Number of output tensors */
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static const int kNumOutputs = 2;
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/** Accuracy used in comparing floating numbers. */
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static const float kTestAccuracy = 1E-5F;
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@interface TFLMetalDelegateTests : XCTestCase
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@end
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@implementation TFLMetalDelegateTests
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- (void)testMetalDelegate {
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NSBundle* bundle = [NSBundle bundleForClass:[self class]];
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NSString* floatModelPath = [bundle pathForResource:kAddFloatModelResourceName
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ofType:kAddModelResourceType];
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TFLInterpreterOptions* options = [[TFLInterpreterOptions alloc] init];
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TFLMetalDelegate* metalDelegate = [[TFLMetalDelegate alloc] init];
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XCTAssertNotNil(metalDelegate);
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id<MTLDevice> mtlDevice = MTLCreateSystemDefaultDevice();
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if (mtlDevice == nil) return; // Stop testing if there's no GPU support
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NSError* error;
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TFLInterpreter* interpreter = [[TFLInterpreter alloc] initWithModelPath:floatModelPath
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options:options
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delegates:@[ metalDelegate ]
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error:&error];
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XCTAssertNil(error);
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XCTAssertNotNil(interpreter);
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XCTAssertTrue([interpreter allocateTensorsWithError:&error]);
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XCTAssertNil(error);
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// Copies the input data. For each input, input[i, j, k] == k
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NSMutableData* inputData = [NSMutableData dataWithLength:sizeof(float) * kTensorSize];
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for (int i = 0; i < kTensorSize / kTensorChannels; ++i) {
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float* data = (float*)inputData.mutableBytes;
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for (int j = 0; j < kTensorChannels; ++j) {
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data[i * kTensorChannels + j] = j;
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}
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}
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for (int input_idx = 0; input_idx < kNumInputs; ++input_idx) {
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TFLTensor* inputTensor = [interpreter inputTensorAtIndex:input_idx error:&error];
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XCTAssertNotNil(inputTensor);
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XCTAssertTrue([inputTensor copyData:inputData error:&error]);
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XCTAssertNil(error);
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}
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// Invokes the interpreter.
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XCTAssertTrue([interpreter invokeWithError:&error]);
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XCTAssertNil(error);
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// Gets the output tensor data. For each output, output[i, j, k] == k * 3
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for (int output_idx = 0; output_idx < kNumOutputs; ++output_idx) {
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TFLTensor* outputTensor = [interpreter outputTensorAtIndex:output_idx error:&error];
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NSData* outputData = [outputTensor dataWithError:&error];
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XCTAssertNotNil(outputData);
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XCTAssertNil(error);
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float output[kTensorSize];
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[outputData getBytes:output length:(sizeof(float) * kTensorSize)];
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for (int i = 0; i < kTensorSize / kTensorChannels; ++i) {
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for (int j = 0; j < kTensorChannels; ++j) {
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XCTAssertEqualWithAccuracy(j * 3, output[i * kTensorChannels + j], kTestAccuracy);
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}
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}
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}
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}
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@end
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NS_ASSUME_NONNULL_END
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