// Copyright (c) 2025 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 <stdio.h>
#include <string.h>
#include <sys/ipc.h>
#include <sys/msg.h>
#include <sys/types.h>
#include "paddle/extension.h"
#include "../custom_ftok.h"
#include "speculate_logprob_msg.h"

#ifndef PD_BUILD_STATIC_OP
#define PD_BUILD_STATIC_OP(name) PD_BUILD_OP(static_op_##name)
#endif

void SpeculateGetOutMmsgTopK(const paddle::Tensor& output_tokens,
                             const paddle::Tensor& output_scores,
                             const paddle::Tensor& output_ranks,
                             int real_k,
                             int64_t rank_id,
                             bool wait_flag) {
  struct msgdata msg_rcv;
  int msg_queue_id = 1;

  if (const char* inference_msg_queue_id_env_p =
          std::getenv("INFERENCE_MSG_QUEUE_ID")) {
    std::string inference_msg_queue_id_env_str(inference_msg_queue_id_env_p);
    int inference_msg_queue_id_from_env =
        std::stoi(inference_msg_queue_id_env_str);
#ifdef SPECULATE_GET_WITH_OUTPUT_DEBUG
    std::cout << "Your INFERENCE_MSG_QUEUE_ID is: "
              << inference_msg_queue_id_from_env << std::endl;
#endif
    msg_queue_id = inference_msg_queue_id_from_env;
  }
  static key_t key = custom_ftok("/dev/shm", msg_queue_id);

  static int msgid = msgget(key, IPC_CREAT | 0666);
#ifdef SPECULATE_GET_WITH_OUTPUT_DEBUG
  std::cout << "get_output_key: " << key << std::endl;
  std::cout << "get_output msgid: " << msgid << std::endl;
#endif

  int64_t* output_tokens_data =
      const_cast<int64_t*>(output_tokens.data<int64_t>());
  float* output_scores_data = const_cast<float*>(output_scores.data<float>());
  int64_t* output_ranks_data =
      const_cast<int64_t*>(output_ranks.data<int64_t>());
  int ret = -1;
  if (!wait_flag) {
    ret =
        msgrcv(msgid, &msg_rcv, sizeof(msg_rcv) - sizeof(long), 0, IPC_NOWAIT);
  } else {
    ret = msgrcv(msgid, &msg_rcv, sizeof(msg_rcv) - sizeof(long), 0, 0);
  }
  if (ret == -1) {
    // read none
    output_tokens_data[0] = -2;  // stop_flag
    output_tokens_data[1] = 0;   // message_flag, Target: 3, Draft: 4
    output_tokens_data[2] = 0;   // bsz
    return;
  }

  int bsz = msg_rcv.meta[2];
  output_tokens_data[0] = (int64_t)msg_rcv.meta[0];
  output_tokens_data[1] = (int64_t)msg_rcv.meta[1];
  output_tokens_data[2] = (int64_t)msg_rcv.meta[2];

  int output_tokens_offset = 3 + SPEC_LOGPROB_MAX_BSZ;
  for (int i = 0; i < bsz; i++) {
    int cur_token_num = msg_rcv.meta[3 + i];
    output_tokens_data[3 + i] = (int64_t)cur_token_num;  // batch_token_nums

    auto* cur_output_token = output_tokens_data + output_tokens_offset +
                             i * (MAX_DRAFT_TOKEN_NUM * (SPEC_LOGPROB_K + 1));
    auto* cur_output_score =
        output_scores_data + i * (MAX_DRAFT_TOKEN_NUM * (SPEC_LOGPROB_K + 1));
    auto* cur_batch_msg_rcv = &msg_rcv.mtext[i];
    for (int j = 0; j < cur_token_num; j++) {
      for (int k = 0; k < real_k + 1; k++) {
        cur_output_token[j * (SPEC_LOGPROB_K + 1) + k] =
            (int64_t)cur_batch_msg_rcv->tokens[j * (SPEC_LOGPROB_K + 1) + k];
        cur_output_score[j * (SPEC_LOGPROB_K + 1) + k] =
            cur_batch_msg_rcv->scores[j * (SPEC_LOGPROB_K + 1) + k];
      }
      output_ranks_data[i * MAX_DRAFT_TOKEN_NUM + j] =
          (int64_t)cur_batch_msg_rcv->ranks[j];
    }
  }
#ifdef SPECULATE_GET_WITH_OUTPUT_DEBUG
  std::cout << "msg data: " << std::endl;
  std::cout << "stop_flag: " << output_tokens_data[0]
            << ", message_flag: " << output_tokens_data[1]
            << ", bsz: " << output_tokens_data[2] << std::endl;
  for (int i = 0; i < output_tokens_data[2]; i++) {
    int cur_token_num = output_tokens_data[3 + i];
    std::cout << "batch " << i << " token_num: " << cur_token_num << std::endl;
    for (int j = 0; j < cur_token_num; j++) {
      std::cout << "tokens: ";
      for (int k = 0; k < SPEC_LOGPROB_K + 1; k++) {
        std::cout << output_tokens_data[output_tokens_offset +
                                        i * MAX_DRAFT_TOKEN_NUM *
                                            (SPEC_LOGPROB_K + 1) +
                                        j * (SPEC_LOGPROB_K + 1) + k]
                  << " ";
      }
      std::cout << std::endl;
      std::cout << "scores: ";
      for (int k = 0; k < SPEC_LOGPROB_K + 1; k++) {
        std::cout << output_scores_data[i * MAX_DRAFT_TOKEN_NUM *
                                            (SPEC_LOGPROB_K + 1) +
                                        j * (SPEC_LOGPROB_K + 1) + k]
                  << " ";
      }
      std::cout << std::endl;
      std::cout << "ranks: " << output_ranks_data[i * MAX_DRAFT_TOKEN_NUM + j]
                << std::endl;
    }
  }
  std::cout << std::endl;
#endif
  return;
}

PD_BUILD_STATIC_OP(speculate_get_output_topk)
    .Inputs({"output_tokens", "output_scores", "output_ranks"})
    .Attrs({"real_k: int", "rank_id: int64_t", "wait_flag: bool"})
    .Outputs({"output_tokens_out", "output_scores_out", "output_ranks_out"})
    .SetInplaceMap({{"output_tokens", "output_tokens_out"},
                    {"output_scores", "output_scores_out"},
                    {"output_ranks", "output_ranks_out"}})
    .SetKernelFn(PD_KERNEL(SpeculateGetOutMmsgTopK));
