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/*
* Copyright (c) 2021 Samsung Electronics Co., Ltd. All Rights Reserved
* Copyright 2017 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 "kernels/SquaredDifference.h"
#include "kernels/TestUtils.h"
#include "luci_interpreter/TestMemoryManager.h"
namespace luci_interpreter
{
namespace kernels
{
namespace
{
using namespace testing;
TEST(SquaredDifferenceTest, Float)
{
std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
Shape input_shape{3, 1, 2};
std::vector<float> input_data1{1.0, 0.0, -1.0, 11.0, -2.0, -1.44};
std::vector<float> input_data2{-1.0, 0.0, 1.0, 12.0, -3.0, -1.43};
Tensor input_tensor1 =
makeInputTensor<DataType::FLOAT32>(input_shape, input_data1, memory_manager.get());
Tensor input_tensor2 =
makeInputTensor<DataType::FLOAT32>(input_shape, input_data2, memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
SquaredDifference kernel(&input_tensor1, &input_tensor2, &output_tensor);
kernel.configure();
memory_manager->allocate_memory(output_tensor);
kernel.execute();
std::vector<float> ref_output_data{4.0, 0.0, 4.0, 1.0, 1.0, 0.0001};
EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
}
TEST(SquaredDifferenceTest, FloatBroadcast)
{
std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
Shape input_shape1{3, 1, 2};
Shape input_shape2{1};
std::vector<float> input_data1{1.0, 0.0, -1.0, 11.0, -2.0, -1.44};
std::vector<float> input_data2{1.0};
Tensor input_tensor1 =
makeInputTensor<DataType::FLOAT32>(input_shape1, input_data1, memory_manager.get());
Tensor input_tensor2 =
makeInputTensor<DataType::FLOAT32>(input_shape2, input_data2, memory_manager.get());
Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
SquaredDifference kernel(&input_tensor1, &input_tensor2, &output_tensor);
kernel.configure();
memory_manager->allocate_memory(output_tensor);
kernel.execute();
std::vector<float> ref_output_data{0.0, 1.0, 4.0, 100.0, 9.0, 5.9536};
EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
}
} // namespace
} // namespace kernels
} // namespace luci_interpreter
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