| /* 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/softmax.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::BHWC; |
| using ::tflite::gpu::DataType; |
| using ::tflite::gpu::HWC; |
| using ::tflite::gpu::Linear; |
| using ::tflite::gpu::OperationType; |
| using ::tflite::gpu::PReLUAttributes; |
| using ::tflite::gpu::Tensor; |
| using ::tflite::gpu::TensorRef; |
| using ::tflite::gpu::metal::CompareVectors; |
| using ::tflite::gpu::metal::SingleOpModel; |
| |
| @interface SoftmaxTest : XCTestCase |
| @end |
| |
| @implementation SoftmaxTest |
| - (void)setUp { |
| [super setUp]; |
| } |
| |
| - (void)testPReluLinearAlphaNoClip { |
| TensorRef<BHWC> input; |
| input.type = DataType::FLOAT32; |
| input.ref = 0; |
| input.shape = BHWC(1, 2, 2, 1); |
| |
| PReLUAttributes attr; |
| attr.clip = 0; |
| Tensor<Linear, DataType::FLOAT32> alpha; |
| alpha.shape.v = 1; |
| alpha.id = 1; |
| alpha.data = {2}; |
| attr.alpha = std::move(alpha); |
| |
| TensorRef<BHWC> output; |
| output.type = DataType::FLOAT32; |
| output.ref = 2; |
| output.shape = BHWC(1, 2, 2, 1); |
| |
| SingleOpModel model({ToString(OperationType::PRELU), attr}, {input}, {output}); |
| XCTAssertTrue(model.PopulateTensor(0, {-1.0, -2.0, 1.0, 2.0})); |
| auto status = model.Invoke(); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| status = CompareVectors({-2, -4, 1, 2}, model.GetOutput(0), 1e-6f); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| } |
| |
| - (void)testPReluLinearAlphaWithClip { |
| TensorRef<BHWC> input; |
| input.type = DataType::FLOAT32; |
| input.ref = 0; |
| input.shape = BHWC(1, 2, 2, 1); |
| |
| PReLUAttributes attr; |
| attr.clip = 1.0; |
| Tensor<Linear, DataType::FLOAT32> alpha; |
| alpha.shape.v = 1; |
| alpha.id = 1; |
| alpha.data = {2}; |
| attr.alpha = std::move(alpha); |
| |
| TensorRef<BHWC> output; |
| output.type = DataType::FLOAT32; |
| output.ref = 2; |
| output.shape = BHWC(1, 2, 2, 1); |
| |
| SingleOpModel model({ToString(OperationType::PRELU), attr}, {input}, {output}); |
| XCTAssertTrue(model.PopulateTensor(0, {-1.0, -2.0, 1.0, 2.0})); |
| auto status = model.Invoke(); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| status = CompareVectors({-2, -4, 1, 1}, model.GetOutput(0), 1e-6f); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| } |
| |
| - (void)testPRelu3DAlphaNoClip { |
| TensorRef<BHWC> input; |
| input.type = DataType::FLOAT32; |
| input.ref = 0; |
| input.shape = BHWC(1, 2, 2, 1); |
| |
| OperationType op_type = OperationType::PRELU; |
| PReLUAttributes attr; |
| attr.clip = 0; |
| Tensor<HWC, DataType::FLOAT32> alpha; |
| alpha.shape = HWC(2, 2, 1); |
| alpha.id = 1; |
| alpha.data = {1, 2, 2, 2}; |
| attr.alpha = std::move(alpha); |
| |
| TensorRef<BHWC> output; |
| output.type = DataType::FLOAT32; |
| output.ref = 2; |
| output.shape = BHWC(1, 2, 2, 1); |
| |
| SingleOpModel model({ToString(op_type), attr}, {input}, {output}); |
| XCTAssertTrue(model.PopulateTensor(0, {0.0, -1.0, 2.0, -3.0})); |
| auto status = model.Invoke(); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| status = CompareVectors({0, -2, 2, -6}, model.GetOutput(0), 1e-6f); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| } |
| |
| - (void)testPRelu3DAlphaWithClip { |
| TensorRef<BHWC> input; |
| input.type = DataType::FLOAT32; |
| input.ref = 0; |
| input.shape = BHWC(1, 2, 2, 1); |
| |
| OperationType op_type = OperationType::PRELU; |
| PReLUAttributes attr; |
| attr.clip = 1.0; |
| Tensor<HWC, DataType::FLOAT32> alpha; |
| alpha.shape = HWC(2, 2, 1); |
| alpha.id = 1; |
| alpha.data = {1, 2, 2, 2}; |
| attr.alpha = std::move(alpha); |
| |
| TensorRef<BHWC> output; |
| output.type = DataType::FLOAT32; |
| output.ref = 2; |
| output.shape = BHWC(1, 2, 2, 1); |
| |
| SingleOpModel model({ToString(op_type), attr}, {input}, {output}); |
| XCTAssertTrue(model.PopulateTensor(0, {0.0, -1.0, 2.0, -3.0})); |
| auto status = model.Invoke(); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| status = CompareVectors({0, -2, 1, -6}, model.GetOutput(0), 1e-6f); |
| XCTAssertTrue(status.ok(), @"%s", std::string(status.message()).c_str()); |
| } |
| |
| @end |