mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2026-04-24 01:29:57 +08:00
chenjian
74d0f1c01f
* [Bug fix] Sync status for caching output cache * fix * fix * fix bug * fix * fix * support xpu * fix * fix * fix * fix * fix * fix ci * fix ci * fix xpu --------- Co-authored-by: YuBaoku <49938469+EmmonsCurse@users.noreply.github.com>
206 lines
8.0 KiB
C++
206 lines
8.0 KiB
C++
// Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <stdio.h>
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#include <string.h>
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#include <sys/ipc.h>
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#include <sys/msg.h>
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#include <sys/types.h>
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#include "paddle/extension.h"
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#ifndef PD_BUILD_STATIC_OP
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#define PD_BUILD_STATIC_OP(name) PD_BUILD_OP(static_op_##name)
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#endif
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#include "speculate_msg.h"
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void SpeculateSaveWithOutputMsg(const paddle::Tensor& accept_tokens,
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const paddle::Tensor& accept_num,
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const paddle::Tensor& not_need_stop,
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const paddle::Tensor& seq_lens_decoder,
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const paddle::Tensor& prompt_lens,
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const paddle::Tensor& preempted_idx,
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int64_t rank_id,
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int msg_queue_id,
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int save_each_rank,
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bool skip_prefill) {
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// printf("enter save output");
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if (!save_each_rank && rank_id > 0) {
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return;
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}
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int max_draft_tokens = accept_tokens.shape()[1];
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auto accept_tokens_cpu = accept_tokens.copy_to(paddle::CPUPlace(), true);
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auto accept_num_cpu = accept_num.copy_to(paddle::CPUPlace(), true);
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int64_t* accept_tokens_data = accept_tokens_cpu.data<int64_t>();
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int* accept_num_data = accept_num_cpu.data<int>();
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auto seq_lens_decoder_cpu =
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seq_lens_decoder.copy_to(paddle::CPUPlace(), true);
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auto prompt_lens_cpu = prompt_lens.copy_to(paddle::CPUPlace(), true);
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int* seq_lens_decoder_data = seq_lens_decoder_cpu.data<int>();
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int64_t* prompt_lens_data = prompt_lens_cpu.data<int64_t>();
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const int32_t* preempted_idx_data = preempted_idx.data<int32_t>();
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if (const char* inference_msg_queue_id_env_p =
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std::getenv("INFERENCE_MSG_QUEUE_ID")) {
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std::string inference_msg_queue_id_env_str(inference_msg_queue_id_env_p);
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int inference_msg_queue_id_from_env =
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std::stoi(inference_msg_queue_id_env_str);
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#ifdef GET_OUTPUT_DEBUG
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std::cout << "Your INFERENCE_MSG_QUEUE_ID is: "
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<< inference_msg_queue_id_from_env << std::endl;
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#endif
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msg_queue_id = inference_msg_queue_id_from_env;
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}
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static struct speculate_msgdata msg_sed;
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static key_t key = ftok("./", msg_queue_id);
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static int msgid = msgget(key, IPC_CREAT | 0666);
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msg_sed.mtype = 1;
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bool not_need_stop_data = not_need_stop.data<bool>()[0];
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int inference_msg_id_from_env = 1;
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if (const char* inference_msg_id_env_p = std::getenv("INFERENCE_MSG_ID")) {
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std::string inference_msg_id_env_str(inference_msg_id_env_p);
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inference_msg_id_from_env = std::stoi(inference_msg_id_env_str);
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if (inference_msg_id_from_env == 2) {
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// 2 and -2 is preserve for no-output indication.
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throw std::runtime_error(
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" INFERENCE_MSG_ID cannot be 2, please use other number.");
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}
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if (inference_msg_id_from_env < 0) {
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throw std::runtime_error(
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" INFERENCE_MSG_ID cannot be negative, please use other "
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"number.");
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}
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#ifdef SAVE_WITH_OUTPUT_DEBUG
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std::cout << "Your INFERENCE_MSG_ID is: " << inference_msg_id_from_env
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<< std::endl;
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#endif
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} else {
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#ifdef SAVE_WITH_OUTPUT_DEBUG
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std::cout << "Failed to got INFERENCE_MSG_ID at env, use (int)1 as default."
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<< std::endl;
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#endif
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}
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msg_sed.mtext[0] = not_need_stop_data ? inference_msg_id_from_env
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: -inference_msg_id_from_env;
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int bsz = accept_tokens.shape()[0];
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msg_sed.mtext[1] = bsz;
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for (int i = 2; i < MAX_BSZ + 2; i++) {
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if (i - 2 >= bsz || (skip_prefill && seq_lens_decoder_data[i - 2] <
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prompt_lens_data[i - 2])) {
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msg_sed.mtext[i] = 0;
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} else {
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msg_sed.mtext[i] = (int)accept_num_data[i - 2];
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}
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if (i - 2 < bsz && preempted_idx_data[i - 2] == 1) {
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msg_sed.mtext[i] = -9;
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}
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}
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for (int i = MAX_BSZ + 2; i < MAX_BSZ * MAX_DRAFT_TOKENS + MAX_BSZ + 2; i++) {
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int token_id = i - MAX_BSZ - 2;
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int bid = token_id / MAX_DRAFT_TOKENS;
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int local_token_id = token_id % MAX_DRAFT_TOKENS;
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if (token_id / MAX_DRAFT_TOKENS >= bsz) {
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msg_sed.mtext[i] = 0;
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} else {
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msg_sed.mtext[i] =
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accept_tokens_data[bid * max_draft_tokens + local_token_id];
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}
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}
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if ((msgsnd(msgid,
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&msg_sed,
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(MAX_BSZ * MAX_DRAFT_TOKENS + MAX_BSZ + 2) * 4,
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0)) == -1) {
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printf("full msg buffer\n");
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}
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return;
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}
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void SpeculateSaveWithOutputMsgStatic(const paddle::Tensor& accept_tokens,
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const paddle::Tensor& accept_num,
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const paddle::Tensor& not_need_stop,
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const paddle::Tensor& seq_lens_decoder,
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const paddle::Tensor& prompt_lens,
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const paddle::Tensor& preempted_idx,
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int64_t rank_id,
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bool save_each_rank,
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bool skip_prefill) {
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SpeculateSaveWithOutputMsg(accept_tokens,
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accept_num,
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not_need_stop,
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seq_lens_decoder,
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prompt_lens,
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preempted_idx,
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rank_id,
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1,
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save_each_rank,
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skip_prefill);
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}
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void SpeculateSaveWithOutputMsgDynamic(const paddle::Tensor& accept_tokens,
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const paddle::Tensor& accept_num,
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const paddle::Tensor& not_need_stop,
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const paddle::Tensor& seq_lens_decoder,
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const paddle::Tensor& prompt_lens,
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const paddle::Tensor& preempted_idx,
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int64_t rank_id,
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int msg_queue_id,
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bool save_each_rank,
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bool skip_prefill) {
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SpeculateSaveWithOutputMsg(accept_tokens,
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accept_num,
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not_need_stop,
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seq_lens_decoder,
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prompt_lens,
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preempted_idx,
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rank_id,
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msg_queue_id,
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save_each_rank,
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skip_prefill);
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}
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PD_BUILD_STATIC_OP(speculate_save_output)
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.Inputs({"accept_tokens",
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"accept_num",
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"not_need_stop",
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"seq_lens_decoder",
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"prompt_lens",
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"preempted_idx"})
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.Attrs({"rank_id: int64_t", "save_each_rank: bool", "skip_prefill: bool"})
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.Outputs({"x_out"})
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.SetInplaceMap({{"accept_tokens", "x_out"}})
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.SetKernelFn(PD_KERNEL(SpeculateSaveWithOutputMsgStatic));
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PD_BUILD_STATIC_OP(speculate_save_output_dynamic)
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.Inputs({"accept_tokens",
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"accept_num",
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"not_need_stop",
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"seq_lens_decoder",
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"prompt_lens",
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"preempted_idx"})
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.Attrs({"rank_id: int64_t",
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"msg_queue_id: int",
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"save_each_rank: bool",
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"skip_prefill: bool"})
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.Outputs({"x_out"})
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.SetInplaceMap({{"accept_tokens", "x_out"}})
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.SetKernelFn(PD_KERNEL(SpeculateSaveWithOutputMsgDynamic));
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