[LLM] First commit the llm deployment code

custom_ops/gpu_ops/save_with_output_msg.cc

@@ -0,0 +1,155 @@
+// 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 "save_with_output_msg.h"
+
+void save_kernel(const paddle::Tensor& x,
+                 const paddle::Tensor& not_need_stop,
+                 int64_t rank_id,
+                 int msg_queue_id,
+                 bool save_each_rank) {
+
+    const int64_t* x_data = x.data<int64_t>();
+    static struct msgdata msg_sed;
+
+    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);
+        msg_queue_id = inference_msg_queue_id_from_env;
+#ifdef SAVE_WITH_OUTPUT_DEBUG
+        std::cout << "Your INFERENCE_MSG_QUEUE_ID is: "
+                  << inference_msg_queue_id_from_env << std::endl;
+#endif
+    } else {
+#ifdef SAVE_WITH_OUTPUT_DEBUG
+        std::cout << "Failed to got INFERENCE_MSG_QUEUE_ID at env, use default."
+                  << std::endl;
+#endif
+    }
+    int inference_msg_id_from_env = 1;
+    if (const char* inference_msg_id_env_p = std::getenv("INFERENCE_MSG_ID")) {
+        std::string inference_msg_id_env_str(inference_msg_id_env_p);
+        inference_msg_id_from_env = std::stoi(inference_msg_id_env_str);
+        if (inference_msg_id_from_env == 2) {
+            // 2 and -2 is perserve for no-output indication.
+            throw std::runtime_error(
+                " INFERENCE_MSG_ID cannot be 2, please use other number.");
+        }
+        if (inference_msg_id_from_env < 0) {
+            throw std::runtime_error(
+                " INFERENCE_MSG_ID cannot be negative, please use other "
+                "number.");
+        }
+
+#ifdef SAVE_WITH_OUTPUT_DEBUG
+        std::cout << "Your INFERENCE_MSG_ID is: " << inference_msg_id_from_env
+                  << std::endl;
+#endif
+    } else {
+#ifdef SAVE_WITH_OUTPUT_DEBUG
+        std::cout
+            << "Failed to got INFERENCE_MSG_ID at env, use (int)1 as default."
+            << std::endl;
+#endif
+    }
+    static key_t key = ftok("/dev/shm", msg_queue_id);
+
+    static int msgid = msgget(key, IPC_CREAT | 0666);
+#ifdef SAVE_WITH_OUTPUT_DEBUG
+    std::cout << "save_output_key: " << key << std::endl;
+    std::cout << "save msgid: " << msgid << std::endl;
+#endif
+    msg_sed.mtype = 1;
+    bool not_need_stop_data = not_need_stop.data<bool>()[0];
+    // printf("not_need_stop_data %d\n", (int)not_need_stop_data);
+    msg_sed.mtext[0] = not_need_stop_data ? inference_msg_id_from_env
+                                          : -inference_msg_id_from_env;
+    int bsz = x.shape()[0];
+    msg_sed.mtext[1] = bsz;
+    for (int i = 2; i < bsz + 2; i++) {
+        msg_sed.mtext[i] = (int)x_data[i - 2];
+    }
+#ifdef SAVE_WITH_OUTPUT_DEBUG
+    std::cout << "msg data: ";
+    for (int i = 0; i < bsz; i++) {
+        std::cout << " " << (int)x_data[i];
+    }
+    std::cout << std::endl;
+#endif
+    if ((msgsnd(msgid, &msg_sed, (MAX_BSZ + 2) * 4, 0)) == -1) {
+        printf("full msg buffer\n");
+    }
+    return;
+}
+
+void SaveOutMmsg(const paddle::Tensor& x,
+                 const paddle::Tensor& not_need_stop,
+                 int64_t rank_id,
+                 int msg_queue_id,
+                 bool save_each_rank) {
+    if (!save_each_rank && rank_id > 0) {
+        return;
+    }
+    if (x.place() == paddle::CPUPlace()) {
+        save_kernel(
+            x,
+            not_need_stop,
+            rank_id,
+            msg_queue_id,
+            save_each_rank
+        );
+    } else {
+        auto x_cpu = x.copy_to(paddle::CPUPlace(), false);
+        save_kernel(
+            x_cpu,
+            not_need_stop,
+            rank_id,
+            msg_queue_id,
+            save_each_rank
+        );
+    }
+}
+
+void SaveOutMmsgStatic(const paddle::Tensor& x,
+                       const paddle::Tensor& not_need_stop,
+                       int64_t rank_id,
+                       bool save_each_rank) {
+    SaveOutMmsg(x, not_need_stop, rank_id, 1, save_each_rank);
+}
+
+void SaveOutMmsgDynamic(const paddle::Tensor& x,
+                        const paddle::Tensor& not_need_stop,
+                        int64_t rank_id,
+                        int msg_queue_id,
+                        bool save_each_rank) {
+    SaveOutMmsg(x, not_need_stop, rank_id, msg_queue_id, save_each_rank);
+}
+
+PD_BUILD_STATIC_OP(save_output)
+    .Inputs({"x", "not_need_stop"})
+    .Attrs({"rank_id: int64_t",
+            "save_each_rank: bool"})
+    .Outputs({"x_out"})
+    .SetInplaceMap({{"x", "x_out"}})
+    .SetKernelFn(PD_KERNEL(SaveOutMmsgStatic));
+
+PD_BUILD_STATIC_OP(save_output_dynamic)
+    .Inputs({"x", "not_need_stop"})
+    .Attrs({"rank_id: int64_t", "msg_queue_id: int", "save_each_rank: bool"})
+    .Outputs({"x_out"})
+    .SetInplaceMap({{"x", "x_out"}})
+    .SetKernelFn(PD_KERNEL(SaveOutMmsgDynamic));