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250 lines
9.2 KiB
250 lines
9.2 KiB
/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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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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*/
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#include <algorithm>
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#include <string>
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#include <memory>
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#include <unordered_set>
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#include "common/common.h"
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#include "gtest/gtest.h"
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#include "dataset/util/status.h"
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#include "dataset/engine/gnn/node.h"
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#include "dataset/engine/gnn/graph_loader.h"
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using namespace mindspore::dataset;
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using namespace mindspore::dataset::gnn;
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#define print_int_vec(_i, _str) \
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do { \
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std::stringstream ss; \
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std::copy(_i.begin(), _i.end(), std::ostream_iterator<int>(ss, " ")); \
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MS_LOG(INFO) << _str << " " << ss.str(); \
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} while (false)
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class MindDataTestGNNGraph : public UT::Common {
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protected:
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MindDataTestGNNGraph() = default;
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};
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TEST_F(MindDataTestGNNGraph, TestGraphLoader) {
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std::string path = "data/mindrecord/testGraphData/testdata";
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GraphLoader gl(path, 4);
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EXPECT_TRUE(gl.InitAndLoad().IsOk());
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NodeIdMap n_id_map;
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EdgeIdMap e_id_map;
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NodeTypeMap n_type_map;
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EdgeTypeMap e_type_map;
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NodeFeatureMap n_feature_map;
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EdgeFeatureMap e_feature_map;
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DefaultFeatureMap default_feature_map;
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EXPECT_TRUE(gl.GetNodesAndEdges(&n_id_map, &e_id_map, &n_type_map, &e_type_map, &n_feature_map, &e_feature_map,
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&default_feature_map)
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.IsOk());
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EXPECT_EQ(n_id_map.size(), 20);
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EXPECT_EQ(e_id_map.size(), 40);
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EXPECT_EQ(n_type_map[2].size(), 10);
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EXPECT_EQ(n_type_map[1].size(), 10);
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}
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TEST_F(MindDataTestGNNGraph, TestGetAllNeighbors) {
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std::string path = "data/mindrecord/testGraphData/testdata";
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Graph graph(path, 1);
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Status s = graph.Init();
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EXPECT_TRUE(s.IsOk());
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MetaInfo meta_info;
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s = graph.GetMetaInfo(&meta_info);
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EXPECT_TRUE(s.IsOk());
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EXPECT_TRUE(meta_info.node_type.size() == 2);
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std::shared_ptr<Tensor> nodes;
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s = graph.GetAllNodes(meta_info.node_type[0], &nodes);
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EXPECT_TRUE(s.IsOk());
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std::vector<NodeIdType> node_list;
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for (auto itr = nodes->begin<NodeIdType>(); itr != nodes->end<NodeIdType>(); ++itr) {
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node_list.push_back(*itr);
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if (node_list.size() >= 10) {
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break;
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}
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}
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std::shared_ptr<Tensor> neighbors;
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s = graph.GetAllNeighbors(node_list, meta_info.node_type[1], &neighbors);
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EXPECT_TRUE(s.IsOk());
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EXPECT_TRUE(neighbors->shape().ToString() == "<10,6>");
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TensorRow features;
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s = graph.GetNodeFeature(nodes, meta_info.node_feature_type, &features);
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EXPECT_TRUE(s.IsOk());
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EXPECT_TRUE(features.size() == 4);
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EXPECT_TRUE(features[0]->shape().ToString() == "<10,5>");
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EXPECT_TRUE(features[0]->ToString() ==
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"Tensor (shape: <10,5>, Type: int32)\n"
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"[[0,1,0,0,0],[1,0,0,0,1],[0,0,1,1,0],[0,0,0,0,0],[1,1,0,1,0],[0,0,0,0,1],[0,1,0,0,0],[0,0,0,1,1],[0,1,1,"
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"0,0],[0,1,0,1,0]]");
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EXPECT_TRUE(features[1]->shape().ToString() == "<10>");
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EXPECT_TRUE(features[1]->ToString() ==
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"Tensor (shape: <10>, Type: float32)\n[0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1]");
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EXPECT_TRUE(features[2]->shape().ToString() == "<10>");
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EXPECT_TRUE(features[2]->ToString() == "Tensor (shape: <10>, Type: int32)\n[1,2,3,1,4,3,5,3,5,4]");
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}
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TEST_F(MindDataTestGNNGraph, TestGetSampledNeighbors) {
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std::string path = "data/mindrecord/testGraphData/testdata";
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Graph graph(path, 1);
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Status s = graph.Init();
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EXPECT_TRUE(s.IsOk());
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MetaInfo meta_info;
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s = graph.GetMetaInfo(&meta_info);
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EXPECT_TRUE(s.IsOk());
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EXPECT_TRUE(meta_info.node_type.size() == 2);
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std::shared_ptr<Tensor> edges;
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s = graph.GetAllEdges(meta_info.edge_type[0], &edges);
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EXPECT_TRUE(s.IsOk());
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std::vector<EdgeIdType> edge_list;
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edge_list.resize(edges->Size());
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std::transform(edges->begin<EdgeIdType>(), edges->end<EdgeIdType>(), edge_list.begin(),
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[](const EdgeIdType edge) { return edge; });
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std::shared_ptr<Tensor> nodes;
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s = graph.GetNodesFromEdges(edge_list, &nodes);
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EXPECT_TRUE(s.IsOk());
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std::unordered_set<NodeIdType> node_set;
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std::vector<NodeIdType> node_list;
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int index = 0;
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for (auto itr = nodes->begin<NodeIdType>(); itr != nodes->end<NodeIdType>(); ++itr) {
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index++;
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if (index % 2 == 0) {
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continue;
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}
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node_set.emplace(*itr);
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if (node_set.size() >= 5) {
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break;
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}
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}
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node_list.resize(node_set.size());
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std::transform(node_set.begin(), node_set.end(), node_list.begin(), [](const NodeIdType node) { return node; });
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std::shared_ptr<Tensor> neighbors;
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s = graph.GetSampledNeighbors(node_list, {10}, {meta_info.node_type[1]}, &neighbors);
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EXPECT_TRUE(s.IsOk());
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EXPECT_TRUE(neighbors->shape().ToString() == "<5,11>");
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neighbors.reset();
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s = graph.GetSampledNeighbors(node_list, {2, 3}, {meta_info.node_type[1], meta_info.node_type[0]}, &neighbors);
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EXPECT_TRUE(s.IsOk());
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EXPECT_TRUE(neighbors->shape().ToString() == "<5,9>");
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neighbors.reset();
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s = graph.GetSampledNeighbors(node_list, {2, 3, 4},
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{meta_info.node_type[1], meta_info.node_type[0], meta_info.node_type[1]}, &neighbors);
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EXPECT_TRUE(s.IsOk());
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EXPECT_TRUE(neighbors->shape().ToString() == "<5,33>");
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neighbors.reset();
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s = graph.GetSampledNeighbors({}, {10}, {meta_info.node_type[1]}, &neighbors);
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EXPECT_TRUE(s.ToString().find("Input node_list is empty.") != std::string::npos);
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neighbors.reset();
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s = graph.GetSampledNeighbors({-1, 1}, {10}, {meta_info.node_type[1]}, &neighbors);
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EXPECT_TRUE(s.ToString().find("Invalid node id") != std::string::npos);
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neighbors.reset();
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s = graph.GetSampledNeighbors(node_list, {2, 50}, {meta_info.node_type[0], meta_info.node_type[1]}, &neighbors);
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EXPECT_TRUE(s.ToString().find("Wrong samples number") != std::string::npos);
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neighbors.reset();
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s = graph.GetSampledNeighbors(node_list, {2}, {5}, &neighbors);
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EXPECT_TRUE(s.ToString().find("Invalid neighbor type") != std::string::npos);
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neighbors.reset();
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s = graph.GetSampledNeighbors(node_list, {2, 3, 4}, {meta_info.node_type[1], meta_info.node_type[0]}, &neighbors);
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EXPECT_TRUE(s.ToString().find("The sizes of neighbor_nums and neighbor_types are inconsistent.") !=
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std::string::npos);
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neighbors.reset();
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s = graph.GetSampledNeighbors({301}, {10}, {meta_info.node_type[1]}, &neighbors);
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EXPECT_TRUE(s.ToString().find("Invalid node id:301") != std::string::npos);
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}
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TEST_F(MindDataTestGNNGraph, TestGetNegSampledNeighbors) {
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std::string path = "data/mindrecord/testGraphData/testdata";
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Graph graph(path, 1);
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Status s = graph.Init();
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EXPECT_TRUE(s.IsOk());
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MetaInfo meta_info;
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s = graph.GetMetaInfo(&meta_info);
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EXPECT_TRUE(s.IsOk());
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EXPECT_TRUE(meta_info.node_type.size() == 2);
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std::shared_ptr<Tensor> nodes;
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s = graph.GetAllNodes(meta_info.node_type[0], &nodes);
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EXPECT_TRUE(s.IsOk());
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std::vector<NodeIdType> node_list;
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for (auto itr = nodes->begin<NodeIdType>(); itr != nodes->end<NodeIdType>(); ++itr) {
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node_list.push_back(*itr);
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if (node_list.size() >= 10) {
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break;
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}
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}
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std::shared_ptr<Tensor> neg_neighbors;
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s = graph.GetNegSampledNeighbors(node_list, 3, meta_info.node_type[1], &neg_neighbors);
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EXPECT_TRUE(s.IsOk());
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EXPECT_TRUE(neg_neighbors->shape().ToString() == "<10,4>");
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neg_neighbors.reset();
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s = graph.GetNegSampledNeighbors({}, 3, meta_info.node_type[1], &neg_neighbors);
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EXPECT_TRUE(s.ToString().find("Input node_list is empty.") != std::string::npos);
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neg_neighbors.reset();
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s = graph.GetNegSampledNeighbors({-1, 1}, 3, meta_info.node_type[1], &neg_neighbors);
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EXPECT_TRUE(s.ToString().find("Invalid node id") != std::string::npos);
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neg_neighbors.reset();
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s = graph.GetNegSampledNeighbors(node_list, 50, meta_info.node_type[1], &neg_neighbors);
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EXPECT_TRUE(s.ToString().find("Wrong samples number") != std::string::npos);
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neg_neighbors.reset();
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s = graph.GetNegSampledNeighbors(node_list, 3, 3, &neg_neighbors);
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EXPECT_TRUE(s.ToString().find("Invalid neighbor type") != std::string::npos);
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}
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TEST_F(MindDataTestGNNGraph, TestRandomWalk) {
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std::string path = "data/mindrecord/testGraphData/sns";
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Graph graph(path, 1);
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Status s = graph.Init();
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EXPECT_TRUE(s.IsOk());
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MetaInfo meta_info;
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s = graph.GetMetaInfo(&meta_info);
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EXPECT_TRUE(s.IsOk());
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std::shared_ptr<Tensor> nodes;
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s = graph.GetAllNodes(meta_info.node_type[0], &nodes);
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EXPECT_TRUE(s.IsOk());
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std::vector<NodeIdType> node_list;
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for (auto itr = nodes->begin<NodeIdType>(); itr != nodes->end<NodeIdType>(); ++itr) {
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node_list.push_back(*itr);
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}
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print_int_vec(node_list, "node list ");
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std::vector<NodeType> meta_path(59, 1);
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std::shared_ptr<Tensor> walk_path;
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s = graph.RandomWalk(node_list, meta_path, 2.0, 0.5, -1, &walk_path);
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EXPECT_TRUE(s.IsOk());
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EXPECT_TRUE(walk_path->shape().ToString() == "<33,60>");
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} |