// Copyright (c) 2024 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 <cstdio>
#include <iostream>
#include "paddle/extension.h"
#include "x86simdsort-static-incl.h"

void probs_sort(const float *probs,
                int64_t *ProbsIds,
                float *ProbsVals,
                int vocab_size,
                int bsz) {
    float cursum = 0;
    std::vector<int64_t> elementsIds(vocab_size);
    std::vector<float> elementsProbs(vocab_size);
#pragma omp parallel for
    for (int j = 0; j < vocab_size; j++) {
        elementsIds[j] = j;
        elementsProbs[j] = probs[j];
    }
    x86simdsortStatic::keyvalue_qsort(
        elementsProbs.data(), elementsIds.data(), vocab_size, false, true);
#pragma omp parallel for
    for (int j = 0; j < vocab_size; ++j) {
        ProbsVals[j] = elementsProbs[j];
        ProbsIds[j] = elementsIds[j];
    }
}
std::vector<paddle::Tensor> SimdSort(const paddle::Tensor &probs) {
    const int bsz = probs.shape()[0];
    const int vocab_size = probs.shape()[1];
    auto sorted_indices = paddle::empty(
        {bsz, vocab_size}, paddle::DataType::INT64, probs.place());
    auto sorted_probs = paddle::empty(
        {bsz, vocab_size}, paddle::DataType::FLOAT32, probs.place());
    probs_sort(probs.data<float>(),
               const_cast<int64_t *>(sorted_indices.data<int64_t>()),
               const_cast<float *>(sorted_probs.data<float>()),
               vocab_size,
               bsz);
    return {sorted_indices, sorted_probs};
}
std::vector<std::vector<int64_t>> SimdSortInferShape(
    const std::vector<int64_t> &probs_shape) {
    int64_t bsz = probs_shape[0];
    int64_t vocab_size = probs_shape[1];
    return {{bsz, vocab_size}, {bsz, vocab_size}};
}
std::vector<paddle::DataType> SimdSortInferDtype(
    const paddle::DataType &probs_dtype) {
    return {paddle::DataType::INT64, paddle::DataType::FLOAT32};
}
PD_BUILD_STATIC_OP(simd_sort)
    .Inputs({"probs"})
    .Outputs({"sorted_indices_out", "sorted_probs_out"})
    .SetInferShapeFn(PD_INFER_SHAPE(SimdSortInferShape))
    .SetInferDtypeFn(PD_INFER_DTYPE(SimdSortInferDtype))
    .SetKernelFn(PD_KERNEL(SimdSort));