[LLM] First commit the llm deployment code

custom_ops/gpu_ops/get_output.cc

@@ -0,0 +1,108 @@
+// 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 <stdio.h>
+#include <string.h>
+#include <sys/ipc.h>
+#include <sys/msg.h>
+#include <sys/types.h>
+#include "paddle/extension.h"
+
+#ifndef PD_BUILD_STATIC_OP
+#define PD_BUILD_STATIC_OP(name) PD_BUILD_OP(static_op_##name)
+#endif
+
+#define MAX_BSZ 512
+// #define GET_OUTPUT_DEBUG
+struct msgdata {
+    long mtype;
+    int mtext[MAX_BSZ + 2];  // stop_flag, bsz, tokens
+};
+
+void GetOutput(const paddle::Tensor& x,
+               int64_t rank_id,
+               bool wait_flag,
+               int msg_queue_id) {
+    if (rank_id > 0) {
+        return;
+    }
+    static struct msgdata msg_rcv;
+    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 GET_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 = ftok("/dev/shm", msg_queue_id);
+    static int msgid = msgget(key, IPC_CREAT | 0666);
+
+#ifdef GET_OUTPUT_DEBUG
+    std::cout << "get_output_key: " << key << std::endl;
+    std::cout << "get_output msgid: " << msgid << std::endl;
+#endif
+
+    int64_t* out_data = const_cast<int64_t*>(x.data<int64_t>());
+    int ret = -1;
+    if (!wait_flag) {
+        ret = msgrcv(msgid, &msg_rcv, (MAX_BSZ + 2) * 4, 0, IPC_NOWAIT);
+    } else {
+        ret = msgrcv(msgid, &msg_rcv, (MAX_BSZ + 2) * 4, 0, 0);
+    }
+    if (ret == -1) {
+        out_data[0] = -2;
+        out_data[1] = 0;
+        return;
+    }
+    int bsz = msg_rcv.mtext[1];
+
+    for (int64_t i = 0; i < bsz + 2; i++) {
+        out_data[i] = (int64_t)msg_rcv.mtext[i];
+    }
+#ifdef GET_OUTPUT_DEBUG
+    std::cout << "get_output finished: " << msgid << std::endl;
+#endif
+
+    return;
+}
+
+void GetOutputStatic(const paddle::Tensor& x, int64_t rank_id, bool wait_flag) {
+    GetOutput(x, rank_id, wait_flag, 1);
+}
+
+void GetOutputDynamic(const paddle::Tensor& x,
+                      int64_t rank_id,
+                      bool wait_flag,
+                      int msg_queue_id) {
+    GetOutput(x, rank_id, wait_flag, msg_queue_id);
+}
+
+PD_BUILD_STATIC_OP(get_output)
+    .Inputs({"x"})
+    .Attrs({"rank_id: int64_t", "wait_flag: bool"})
+    .Outputs({"x_out"})
+    .SetInplaceMap({{"x", "x_out"}})
+    .SetKernelFn(PD_KERNEL(GetOutputStatic));
+
+PD_BUILD_STATIC_OP(get_output_dynamic)
+    .Inputs({"x"})
+    .Attrs({"rank_id: int64_t", "wait_flag: bool", "msg_queue_id: int"})
+    .Outputs({"x_out"})
+    .SetInplaceMap({{"x", "x_out"}})
+    .SetKernelFn(PD_KERNEL(GetOutputDynamic));