resolve conflicts

cmake/configure.cmake

@@ -100,6 +100,11 @@ if(WITH_GPU)
     if(NOT CUDNN_FOUND)
         message(FATAL_ERROR "Paddle needs cudnn to compile")
     endif()
+
+    if(${CUDNN_MAJOR_VERSION} VERSION_LESS 7)
+        message(FATAL_ERROR "Paddle needs CUDNN >= 7.0 to compile")
+    endif()
+
     if(CUPTI_FOUND)
         include_directories(${CUPTI_INCLUDE_DIR})
         add_definitions(-DPADDLE_WITH_CUPTI)

paddle/fluid/distributed/table/graph_edge.cc

@@ -0,0 +1,29 @@
+// Copyright (c) 2021 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 "paddle/fluid/distributed/table/graph_edge.h"
+#include <cstring>
+namespace paddle {
+namespace distributed {
+
+void GraphEdgeBlob::add_edge(uint64_t id, float weight = 1) {
+  id_arr.push_back(id);
+}
+
+void WeightedGraphEdgeBlob::add_edge(uint64_t id, float weight = 1) {
+  id_arr.push_back(id);
+  weight_arr.push_back(weight);
+}
+}
+}

paddle/fluid/distributed/table/graph_edge.h

@@ -0,0 +1,46 @@
+// Copyright (c) 2021 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.
+
+#pragma once
+#include <cstddef>
+#include <cstdint>
+#include <vector>
+namespace paddle {
+namespace distributed {
+
+class GraphEdgeBlob {
+ public:
+  GraphEdgeBlob() {}
+  virtual ~GraphEdgeBlob() {}
+  size_t size() { return id_arr.size(); }
+  virtual void add_edge(uint64_t id, float weight);
+  uint64_t get_id(int idx) { return id_arr[idx]; }
+  virtual float get_weight(int idx) { return 1; }
+
+ protected:
+  std::vector<uint64_t> id_arr;
+};
+
+class WeightedGraphEdgeBlob : public GraphEdgeBlob {
+ public:
+  WeightedGraphEdgeBlob() {}
+  virtual ~WeightedGraphEdgeBlob() {}
+  virtual void add_edge(uint64_t id, float weight);
+  virtual float get_weight(int idx) { return weight_arr[idx]; }
+
+ protected:
+  std::vector<float> weight_arr;
+};
+}
+}

paddle/fluid/distributed/table/graph_node.cc

@@ -0,0 +1,117 @@
+// Copyright (c) 2021 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 "paddle/fluid/distributed/table/graph_node.h"
+#include <cstring>
+namespace paddle {
+namespace distributed {
+
+GraphNode::~GraphNode() {
+  if (sampler != nullptr) {
+    delete sampler;
+    sampler = nullptr;
+  }
+  if (edges != nullptr) {
+    delete edges;
+    edges = nullptr;
+  }
+}
+
+int Node::weight_size = sizeof(float);
+int Node::id_size = sizeof(uint64_t);
+int Node::int_size = sizeof(int);
+
+int Node::get_size(bool need_feature) { return id_size + int_size; }
+
+void Node::to_buffer(char* buffer, bool need_feature) {
+  memcpy(buffer, &id, id_size);
+  buffer += id_size;
+
+  int feat_num = 0;
+  memcpy(buffer, &feat_num, sizeof(int));
+}
+
+void Node::recover_from_buffer(char* buffer) { memcpy(&id, buffer, id_size); }
+
+int FeatureNode::get_size(bool need_feature) {
+  int size = id_size + int_size;  // id, feat_num
+  if (need_feature) {
+    size += feature.size() * int_size;
+    for (const std::string& fea : feature) {
+      size += fea.size();
+    }
+  }
+  return size;
+}
+
+void GraphNode::build_edges(bool is_weighted) {
+  if (edges == nullptr) {
+    if (is_weighted == true) {
+      edges = new WeightedGraphEdgeBlob();
+    } else {
+      edges = new GraphEdgeBlob();
+    }
+  }
+}
+void GraphNode::build_sampler(std::string sample_type) {
+  if (sample_type == "random") {
+    sampler = new RandomSampler();
+  } else if (sample_type == "weighted") {
+    sampler = new WeightedSampler();
+  }
+  sampler->build(edges);
+}
+void FeatureNode::to_buffer(char* buffer, bool need_feature) {
+  memcpy(buffer, &id, id_size);
+  buffer += id_size;
+
+  int feat_num = 0;
+  int feat_len;
+  if (need_feature) {
+    feat_num += feature.size();
+    memcpy(buffer, &feat_num, sizeof(int));
+    buffer += sizeof(int);
+    for (int i = 0; i < feat_num; ++i) {
+      feat_len = feature[i].size();
+      memcpy(buffer, &feat_len, sizeof(int));
+      buffer += sizeof(int);
+      memcpy(buffer, feature[i].c_str(), feature[i].size());
+      buffer += feature[i].size();
+    }
+  } else {
+    memcpy(buffer, &feat_num, sizeof(int));
+  }
+}
+void FeatureNode::recover_from_buffer(char* buffer) {
+  int feat_num, feat_len;
+  memcpy(&id, buffer, id_size);
+  buffer += id_size;
+
+  memcpy(&feat_num, buffer, sizeof(int));
+  buffer += sizeof(int);
+
+  feature.clear();
+  for (int i = 0; i < feat_num; ++i) {
+    memcpy(&feat_len, buffer, sizeof(int));
+    buffer += sizeof(int);
+
+    char str[feat_len + 1];
+    memcpy(str, buffer, feat_len);
+    buffer += feat_len;
+    str[feat_len] = '\0';
+    feature.push_back(std::string(str));
+  }
+}
+}
+}

paddle/fluid/distributed/table/graph_node.h

@@ -0,0 +1,127 @@
+// Copyright (c) 2021 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.
+
+#pragma once
+#include <cstring>
+#include <iostream>
+#include <sstream>
+#include <vector>
+#include "paddle/fluid/distributed/table/graph_weighted_sampler.h"
+namespace paddle {
+namespace distributed {
+
+class Node {
+ public:
+  Node() {}
+  Node(uint64_t id) : id(id) {}
+  virtual ~Node() {}
+  static int id_size, int_size, weight_size;
+  uint64_t get_id() { return id; }
+  void set_id(uint64_t id) { this->id = id; }
+
+  virtual void build_edges(bool is_weighted) {}
+  virtual void build_sampler(std::string sample_type) {}
+  virtual void add_edge(uint64_t id, float weight) {}
+  virtual std::vector<int> sample_k(int k) { return std::vector<int>(); }
+  virtual uint64_t get_neighbor_id(int idx) { return 0; }
+  virtual float get_neighbor_weight(int idx) { return 1.; }
+
+  virtual int get_size(bool need_feature);
+  virtual void to_buffer(char *buffer, bool need_feature);
+  virtual void recover_from_buffer(char *buffer);
+  virtual std::string get_feature(int idx) { return std::string(""); }
+  virtual void set_feature(int idx, std::string str) {}
+  virtual void set_feature_size(int size) {}
+  virtual int get_feature_size() { return 0; }
+
+ protected:
+  uint64_t id;
+};
+
+class GraphNode : public Node {
+ public:
+  GraphNode() : Node(), sampler(nullptr), edges(nullptr) {}
+  GraphNode(uint64_t id) : Node(id), sampler(nullptr), edges(nullptr) {}
+  virtual ~GraphNode();
+  virtual void build_edges(bool is_weighted);
+  virtual void build_sampler(std::string sample_type);
+  virtual void add_edge(uint64_t id, float weight) {
+    edges->add_edge(id, weight);
+  }
+  virtual std::vector<int> sample_k(int k) { return sampler->sample_k(k); }
+  virtual uint64_t get_neighbor_id(int idx) { return edges->get_id(idx); }
+  virtual float get_neighbor_weight(int idx) { return edges->get_weight(idx); }
+
+ protected:
+  Sampler *sampler;
+  GraphEdgeBlob *edges;
+};
+
+class FeatureNode : public Node {
+ public:
+  FeatureNode() : Node() {}
+  FeatureNode(uint64_t id) : Node(id) {}
+  virtual ~FeatureNode() {}
+  virtual int get_size(bool need_feature);
+  virtual void to_buffer(char *buffer, bool need_feature);
+  virtual void recover_from_buffer(char *buffer);
+  virtual std::string get_feature(int idx) {
+    if (idx < (int)this->feature.size()) {
+      return this->feature[idx];
+    } else {
+      return std::string("");
+    }
+  }
+
+  virtual void set_feature(int idx, std::string str) {
+    if (idx >= (int)this->feature.size()) {
+      this->feature.resize(idx + 1);
+    }
+    this->feature[idx] = str;
+  }
+  virtual void set_feature_size(int size) { this->feature.resize(size); }
+  virtual int get_feature_size() { return this->feature.size(); }
+
+  template <typename T>
+  static std::string parse_value_to_bytes(std::vector<std::string> feat_str) {
+    T v;
+    size_t Tsize = sizeof(T) * feat_str.size();
+    char buffer[Tsize];
+    for (size_t i = 0; i < feat_str.size(); i++) {
+      std::stringstream ss(feat_str[i]);
+      ss >> v;
+      std::memcpy(buffer + sizeof(T) * i, (char *)&v, sizeof(T));
+    }
+    return std::string(buffer, Tsize);
+  }
+
+  template <typename T>
+  static std::vector<T> parse_bytes_to_array(std::string feat_str) {
+    T v;
+    std::vector<T> out;
+    size_t start = 0;
+    const char *buffer = feat_str.data();
+    while (start < feat_str.size()) {
+      std::memcpy((char *)&v, buffer + start, sizeof(T));
+      start += sizeof(T);
+      out.push_back(v);
+    }
+    return out;
+  }
+
+ protected:
+  std::vector<std::string> feature;
+};
+}
+}