// Tencent is pleased to support the open source community by making TNN available.
//
// Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// 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 "test/unit_test/layer_test/layer_test.h"
#include "test/unit_test/unit_test_common.h"
#include "test/unit_test/utils/network_helpers.h"
#include "tnn/utils/dims_utils.h"

namespace TNN_NS {

class HardSwishLayerTest
    : public LayerTest,
      public ::testing::WithParamInterface<std::tuple<int, int, int, float, float, int, int, DataType>> {};

INSTANTIATE_TEST_SUITE_P(LayerTest, HardSwishLayerTest,
                         ::testing::Combine(
                             // batch
                             testing::Values(1, 2),
                             // channel Values(1, 6, 8, 13),
                             testing::Values(1, 6, 8, 13),
                             // size Values(1, 6, 8, 13),
                             testing::Values(6),
                             // alpha Values(2, 1, 0.5),
                             testing::Values(2, 1, 0.5),
                             // beta Values(0, 2, 1.5, 3),
                             testing::Values(0, 2, 1.5, 3),
                             // input count
                             testing::Values(1, 2),
                             // input dim
                             testing::Values(2, 3, 4),
                             // data_type
                             testing::Values(DATA_TYPE_FLOAT)));

TEST_P(HardSwishLayerTest, HardSwishLayer) {
    // get param
    int batch       = std::get<0>(GetParam());
    int channel     = std::get<1>(GetParam());
    int input_size  = std::get<2>(GetParam());
    float alpha     = std::get<3>(GetParam());
    float beta      = std::get<4>(GetParam());
    int input_count = std::get<5>(GetParam());
    int dim_count   = std::get<6>(GetParam());

    DataType data_type = std::get<7>(GetParam());
    DeviceType dev     = ConvertDeviceType(FLAGS_dt);

    if (DEVICE_HUAWEI_NPU == dev) {
        GTEST_SKIP();
    }

    // param
    std::shared_ptr<HardSwishLayerParam> param(new HardSwishLayerParam());
    param->name  = "HardSwish";
    param->alpha = alpha;
    param->beta  = beta;

    // generate interpreter
    std::vector<int> input_dims = {batch, channel};
    while(input_dims.size() < dim_count) input_dims.push_back(input_size);

    std::vector<std::vector<int>> input_dims_vec;
    for (int i = 0; i < input_count; ++i) {
        input_dims_vec.push_back(input_dims);
    }
    auto interpreter = GenerateInterpreter("HardSwish", input_dims_vec, param);
    Run(interpreter);
}

}  // namespace TNN_NS
