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* delete nonzero * delete setup_ops_base.py * check if * check gcp infer_seed.cpu() * fix repetition_early_stopper_kernel cuda 700
136 lines
4.2 KiB
C++
136 lines
4.2 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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#include "msg_utils.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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#define MAX_BSZ 512
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void GetOutputKVSignal(const paddle::Tensor& x,
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int64_t rank_id,
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bool wait_flag) {
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int msg_queue_id = 1024 + rank_id;
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static struct msgdatakv msg_rcv;
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static key_t key = ftok("/opt/", msg_queue_id);
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static int msgid = msgget(key, IPC_CREAT | 0666);
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int* out_data = const_cast<int*>(x.data<int>());
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int ret = -1;
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if (!wait_flag) {
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ret = msgrcv(msgid, &msg_rcv, (MAX_BSZ * 3 + 2) * 4, 0, IPC_NOWAIT);
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} else {
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ret = msgrcv(msgid, &msg_rcv, (MAX_BSZ * 3 + 2) * 4, 0, 0);
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}
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if (ret == -1) {
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out_data[0] = -1;
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out_data[1] = -1;
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return;
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}
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int encoder_count = msg_rcv.mtext[0];
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for (int i = 0; i < encoder_count * 3 + 2; i++) {
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out_data[i] = msg_rcv.mtext[i];
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}
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return;
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}
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void GetOutputEp(const paddle::Tensor& x,
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int64_t rank_id,
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bool wait_flag,
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int msg_queue_id) {
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static struct msgdata msg_rcv;
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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(
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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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#ifdef GET_OUTPUT_DEBUG
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std::cout << "msg_queue_id is: "
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<< msg_queue_id << std::endl;
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#endif
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// static key_t key = ftok("/dev/shm", msg_queue_id);
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// static int msgid = msgget(key, IPC_CREAT | 0666);
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key_t key = ftok("/dev/shm", msg_queue_id);
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int msgid = msgget(key, IPC_CREAT | 0666);
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#ifdef GET_OUTPUT_DEBUG
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std::cout << "get_output_key: " << key << std::endl;
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std::cout << "get_output msgid: " << msgid << std::endl;
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#endif
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int64_t* out_data = const_cast<int64_t*>(x.data<int64_t>());
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int ret = -1;
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if (!wait_flag) {
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ret = msgrcv(msgid, &msg_rcv, (MAX_BSZ + 2) * 4, 0, IPC_NOWAIT);
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} else {
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ret = msgrcv(msgid, &msg_rcv, (MAX_BSZ + 2) * 4, 0, 0);
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}
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if (ret == -1) {
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out_data[0] = -2;
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out_data[1] = 0;
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return;
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}
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int bsz = msg_rcv.mtext[1];
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for (int64_t i = 0; i < bsz + 2; i++) {
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out_data[i] = (int64_t)msg_rcv.mtext[i];
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}
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#ifdef GET_OUTPUT_DEBUG
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std::cout << "get_output finished: " << msgid << std::endl;
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#endif
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return;
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}
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void GetOutputEPStatic(const paddle::Tensor& x, int64_t rank_id, bool wait_flag) {
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GetOutputEp(x, rank_id, wait_flag, 1);
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}
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void GetOutputEPDynamic(const paddle::Tensor& x,
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int64_t rank_id,
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bool wait_flag,
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int msg_queue_id) {
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GetOutputEp(x, rank_id, wait_flag, msg_queue_id);
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}
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PD_BUILD_STATIC_OP(get_output_ep)
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.Inputs({"x"})
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.Attrs({"rank_id: int64_t", "wait_flag: bool"})
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.Outputs({"x_out"})
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.SetInplaceMap({{"x", "x_out"}})
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.SetKernelFn(PD_KERNEL(GetOutputEPStatic));
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PD_BUILD_STATIC_OP(get_output_ep_dynamic)
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.Inputs({"x"})
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.Attrs({"rank_id: int64_t", "wait_flag: bool", "msg_queue_id: int"})
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.Outputs({"x_out"})
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.SetInplaceMap({{"x", "x_out"}})
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.SetKernelFn(PD_KERNEL(GetOutputEPDynamic));
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