[LLM] First commit the llm deployment code

custom_ops/gpu_ops/get_output_msg_with_topk.cc

@@ -0,0 +1,109 @@
+// 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 K 10
+
+struct msgdata {
+    long mtype;
+    int mtext[MAX_BSZ * (K + 1) + 2];  // stop_flag, bsz, tokens
+    float mtext_f[MAX_BSZ * (K + 1)];  // score
+};
+
+void GetOutputTopK(const paddle::Tensor& x,
+                   const paddle::Tensor& scores,
+                   int k,
+                   int64_t rank_id,
+                   bool wait_flag) {
+    if (rank_id > 0) {
+        return;
+    }
+
+    static 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 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>());
+    float* scores_data = const_cast<float*>(scores.data<float>());
+    int ret = -1;
+    if (!wait_flag) {
+        ret = msgrcv(msgid,
+                     &msg_rcv,
+                     (MAX_BSZ * (K + 1) + 2) * 4 + MAX_BSZ * (K + 1) * 4,
+                     0,
+                     IPC_NOWAIT);
+    } else {
+        ret = msgrcv(msgid,
+                     &msg_rcv,
+                     (MAX_BSZ * (K + 1) + 2) * 4 + MAX_BSZ * (K + 1) * 4,
+                     0,
+                     0);
+    }
+    if (ret == -1) {
+        // read none
+        out_data[0] = -2;
+        out_data[1] = 0;
+        return;
+    }
+
+    int bsz = msg_rcv.mtext[1];
+    out_data[0] = (int64_t)msg_rcv.mtext[0];
+    out_data[1] = (int64_t)msg_rcv.mtext[1];
+
+    for (int i = 0; i < bsz; i++) {
+        for (int j = 0; j < k + 1; j++) {
+            const int64_t offset = i * (K + 1) + j;
+            out_data[offset + 2] = (int64_t)msg_rcv.mtext[offset + 2];
+            scores_data[offset] = msg_rcv.mtext_f[offset];
+        }
+    }
+    return;
+}
+
+PD_BUILD_STATIC_OP(get_output_topk)
+    .Inputs({"x", "scores"})
+    .Attrs({"k: int", "rank_id: int64_t", "wait_flag: bool"})
+    .Outputs({"x_out", "scores_out"})
+    .SetInplaceMap({{"x", "x_out"}, {"scores", "scores_out"}})
+    .SetKernelFn(PD_KERNEL(GetOutputTopK));