/* Copyright (c) 2021 PaddlePaddle 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 "rbox_iou_op.h"
#include "paddle/extension.h"


template <typename T>
void rbox_iou_cpu_kernel(
    const int rbox1_num,
    const int rbox2_num,
    const T* rbox1_data_ptr,
    const T* rbox2_data_ptr,
    T* output_data_ptr) {

    int i, j;
    for (i = 0; i < rbox1_num; i++) {
        for (j = 0; j < rbox2_num; j++) {
		int offset = i * rbox2_num + j;
		output_data_ptr[offset] = rbox_iou_single<T>(rbox1_data_ptr + i * 5, rbox2_data_ptr + j * 5);
        }
    }
}


#define CHECK_INPUT_CPU(x) PD_CHECK(x.place() == paddle::PlaceType::kCPU, #x " must be a CPU Tensor.")

std::vector<paddle::Tensor> RboxIouCPUForward(const paddle::Tensor& rbox1, const paddle::Tensor& rbox2) {
    CHECK_INPUT_CPU(rbox1);
    CHECK_INPUT_CPU(rbox2);

    auto rbox1_num = rbox1.shape()[0];
    auto rbox2_num = rbox2.shape()[0];

    auto output = paddle::Tensor(paddle::PlaceType::kCPU);
    output.reshape({rbox1_num, rbox2_num});

    PD_DISPATCH_FLOATING_TYPES(
        rbox1.type(),
        "rbox_iou_cpu_kernel",
        ([&] {
            rbox_iou_cpu_kernel<data_t>(
                rbox1_num,
                rbox2_num,
                rbox1.data<data_t>(),
                rbox2.data<data_t>(),
                output.mutable_data<data_t>());
        }));
    
    return {output};
}


#ifdef PADDLE_WITH_CUDA
std::vector<paddle::Tensor> RboxIouCUDAForward(const paddle::Tensor& rbox1, const paddle::Tensor& rbox2);
#endif


#define CHECK_INPUT_SAME(x1, x2) PD_CHECK(x1.place() == x2.place(), "input must be smae pacle.")

std::vector<paddle::Tensor> RboxIouForward(const paddle::Tensor& rbox1, const paddle::Tensor& rbox2) {
    CHECK_INPUT_SAME(rbox1, rbox2);
    if (rbox1.place() == paddle::PlaceType::kCPU) {
        return RboxIouCPUForward(rbox1, rbox2);
#ifdef PADDLE_WITH_CUDA
    } else if (rbox1.place() == paddle::PlaceType::kGPU) {
        return RboxIouCUDAForward(rbox1, rbox2);
#endif
    }
}

std::vector<std::vector<int64_t>> InferShape(std::vector<int64_t> rbox1_shape, std::vector<int64_t> rbox2_shape) {
    return {{rbox1_shape[0], rbox2_shape[0]}};
}

std::vector<paddle::DataType> InferDtype(paddle::DataType t1, paddle::DataType t2) {
    return {t1};
}

PD_BUILD_OP(rbox_iou)
    .Inputs({"RBOX1", "RBOX2"})
    .Outputs({"Output"})
    .SetKernelFn(PD_KERNEL(RboxIouForward))
    .SetInferShapeFn(PD_INFER_SHAPE(InferShape))
    .SetInferDtypeFn(PD_INFER_DTYPE(InferDtype));