| /* Copyright 2019 The TensorFlow Authors. All Rights Reserved. |
| |
| Licensed under the Apache License, Version 2.0 (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, software |
| distributed under the License is distributed on an "AS IS" BASIS, |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and |
| limitations under the License. |
| ==============================================================================*/ |
| |
| #include "tensorflow/lite/delegates/gpu/metal/kernels/add.h" |
| |
| #import <XCTest/XCTest.h> |
| |
| #include <string> |
| #include <vector> |
| |
| #include "tensorflow/lite/delegates/gpu/common/operations.h" |
| #include "tensorflow/lite/delegates/gpu/common/shape.h" |
| #include "tensorflow/lite/delegates/gpu/common/status.h" |
| #include "tensorflow/lite/delegates/gpu/common/tensor.h" |
| #include "tensorflow/lite/delegates/gpu/common/util.h" |
| #include "tensorflow/lite/delegates/gpu/metal/compute_task_descriptor.h" |
| #include "tensorflow/lite/delegates/gpu/metal/kernels/test_util.h" |
| |
| using ::tflite::gpu::Axis; |
| using ::tflite::gpu::BHWC; |
| using ::tflite::gpu::DataType; |
| using ::tflite::gpu::DepthwiseConvolution2DAttributes; |
| using ::tflite::gpu::HW; |
| using ::tflite::gpu::Linear; |
| using ::tflite::gpu::OHWI; |
| using ::tflite::gpu::OperationType; |
| using ::tflite::gpu::Tensor; |
| using ::tflite::gpu::TensorRef; |
| using ::tflite::gpu::metal::CompareVectors; |
| using ::tflite::gpu::metal::SingleOpModel; |
| |
| @interface DepthwiseConvTest : XCTestCase |
| @end |
| |
| @implementation DepthwiseConvTest |
| - (void)setUp { |
| [super setUp]; |
| } |
| |
| - (void)testO4H1W1I2Strides1x1Dilation1x1 { |
| TensorRef<BHWC> input; |
| input.type = DataType::FLOAT32; |
| input.ref = 0; |
| input.shape = BHWC(1, 1, 1, 2); |
| |
| DepthwiseConvolution2DAttributes attr; |
| Tensor<Linear, DataType::FLOAT32> bias; |
| bias.shape.v = 4; |
| bias.id = 1; |
| bias.data = {1, 2, 3, 4}; |
| attr.bias = std::move(bias); |
| |
| Tensor<OHWI, DataType::FLOAT32> weights; |
| weights.shape = OHWI(2, 1, 1, 2); |
| weights.id = 2; |
| weights.data = {1, 3, 2, 4}; |
| |
| attr.weights = std::move(weights); |
| |
| attr.dilations = HW(1, 1); |
| attr.padding.prepended = HW(0, 0); |
| attr.padding.appended = HW(0, 0); |
| attr.strides = HW(1, 1); |
| |
| TensorRef<BHWC> output; |
| output.type = DataType::FLOAT32; |
| output.ref = 3; |
| output.shape = BHWC(1, 1, 1, 4); |
| |
| SingleOpModel model({ToString(OperationType::DEPTHWISE_CONVOLUTION), std::move(attr)}, {input}, |
| {output}); |
| XCTAssertTrue(model.PopulateTensor(0, {1, 3})); |
| auto status = model.Invoke(); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| status = CompareVectors({2, 4, 12, 16}, model.GetOutput(0), 1e-6f); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| } |
| |
| - (void)testO2H1W1I1Strides2x2Dilation1x1 { |
| TensorRef<BHWC> input; |
| input.type = DataType::FLOAT32; |
| input.ref = 0; |
| input.shape = BHWC(1, 3, 3, 1); |
| |
| DepthwiseConvolution2DAttributes attr; |
| Tensor<Linear, DataType::FLOAT32> bias; |
| bias.shape.v = 4; |
| bias.id = 1; |
| bias.data = {0, 0}; |
| attr.bias = std::move(bias); |
| |
| Tensor<OHWI, DataType::FLOAT32> weights; |
| weights.shape = OHWI(2, 1, 1, 1); |
| weights.id = 1; |
| weights.data = {1, 3}; |
| |
| attr.weights = std::move(weights); |
| |
| attr.dilations = HW(1, 1); |
| attr.padding.prepended = HW(0, 0); |
| attr.padding.appended = HW(0, 0); |
| attr.strides = HW(2, 2); |
| |
| TensorRef<BHWC> output; |
| output.type = DataType::FLOAT32; |
| output.ref = 3; |
| output.shape = BHWC(1, 2, 2, 2); |
| |
| SingleOpModel model({ToString(OperationType::DEPTHWISE_CONVOLUTION), std::move(attr)}, {input}, |
| {output}); |
| XCTAssertTrue(model.PopulateTensor(0, {1, 0, 1, 1, 0, 1, 1, 0, 1})); |
| auto status = model.Invoke(); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| status = CompareVectors({1, 3, 1, 3, 1, 3, 1, 3}, model.GetOutput(0), 1e-6f); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| } |
| |
| - (void)testO2H2W2I1Strides1x1Dilation2x2 { |
| TensorRef<BHWC> input; |
| input.type = DataType::FLOAT32; |
| input.ref = 0; |
| input.shape = BHWC(1, 3, 3, 1); |
| |
| DepthwiseConvolution2DAttributes attr; |
| Tensor<Linear, DataType::FLOAT32> bias; |
| bias.shape.v = 4; |
| bias.id = 1; |
| bias.data = {0, 0}; |
| attr.bias = std::move(bias); |
| |
| Tensor<OHWI, DataType::FLOAT32> weights; |
| weights.shape = OHWI(2, 2, 2, 1); |
| weights.id = 1; |
| weights.data = {1, 2, 3, 4, 5, 6, 7, 8}; |
| |
| attr.weights = std::move(weights); |
| |
| attr.dilations = HW(2, 2); |
| attr.padding.prepended = HW(0, 0); |
| attr.padding.appended = HW(0, 0); |
| attr.strides = HW(1, 1); |
| |
| TensorRef<BHWC> output; |
| output.type = DataType::FLOAT32; |
| output.ref = 3; |
| output.shape = BHWC(1, 1, 1, 2); |
| |
| SingleOpModel model({ToString(OperationType::DEPTHWISE_CONVOLUTION), std::move(attr)}, {input}, |
| {output}); |
| XCTAssertTrue(model.PopulateTensor(0, {1, 0, 1, 1, 0, 1, 1, 0, 1})); |
| auto status = model.Invoke(); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| status = CompareVectors({10, 26}, model.GetOutput(0), 1e-6f); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| } |
| |
| - (void)testShape2x2Kernel2x2 { |
| TensorRef<BHWC> input; |
| input.type = DataType::FLOAT32; |
| input.ref = 0; |
| input.shape = BHWC(1, 2, 2, 1); |
| |
| DepthwiseConvolution2DAttributes attr; |
| Tensor<Linear, DataType::FLOAT32> bias; |
| bias.shape.v = 1; |
| bias.id = 1; |
| bias.data = {0}; |
| attr.bias = std::move(bias); |
| |
| Tensor<OHWI, DataType::FLOAT32> weights; |
| weights.shape = OHWI(1, 2, 2, 1); |
| weights.id = 1; |
| weights.data = {1, 2, 3, 4}; |
| |
| attr.weights = std::move(weights); |
| |
| attr.dilations = HW(1, 1); |
| attr.padding.prepended = HW(0, 0); |
| attr.padding.appended = HW(1, 1); |
| attr.strides = HW(1, 1); |
| |
| TensorRef<BHWC> output; |
| output.type = DataType::FLOAT32; |
| output.ref = 3; |
| output.shape = BHWC(1, 2, 2, 1); |
| |
| SingleOpModel model({ToString(OperationType::DEPTHWISE_CONVOLUTION), std::move(attr)}, {input}, |
| {output}); |
| XCTAssertTrue(model.PopulateTensor(0, {1, 4, 9, 16})); |
| auto status = model.Invoke(); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| status = CompareVectors({100, 52, 41, 16}, model.GetOutput(0), 1e-6f); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| } |
| |
| @end |