// 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 ReformatLayerTest : public LayerTest,
                          public ::testing::WithParamInterface<std::tuple<int, int, int, DataType>> {};

INSTANTIATE_TEST_SUITE_P(LayerTest, ReformatLayerTest,
                         ::testing::Combine(BASIC_BATCH_CHANNEL_SIZE,
                                            // src_type
                                            testing::Values(DATA_TYPE_INT8, DATA_TYPE_FLOAT)

                                                ));

TEST_P(ReformatLayerTest, ReformatLayer) {
    // get param
    int batch                = std::get<0>(GetParam());
    int channel              = std::get<1>(GetParam());
    int input_size           = std::get<2>(GetParam());
    DataType input_data_type = std::get<3>(GetParam());
    DeviceType dev           = ConvertDeviceType(FLAGS_dt);
    if (DEVICE_ARM != dev) {
        GTEST_SKIP();
    }

    DataType output_data_type = input_data_type == DATA_TYPE_INT8 ? DATA_TYPE_FLOAT : DATA_TYPE_INT8;

    std::shared_ptr<ReformatLayerParam> param(new ReformatLayerParam());
    param->name     = "Reformat";
    param->src_type = input_data_type;
    param->dst_type = output_data_type;

    // generate interpreter
    std::vector<int> input_dims = {batch, channel, input_size, input_size};
    auto interpreter            = GenerateInterpreter("Reformat", {input_dims}, param);
    Run(interpreter);
}

}  // namespace TNN_NS
