Revert "GNN tests (#12)" (#19)

This reverts commit 9b91847.

.github/workflows/build-and-test.yml

@@ -53,11 +53,11 @@ jobs:
         shell: bash -l {0}
     strategy:
       matrix:
-        build-type: ['Release']
-        sanitizer-type: ['nosan']
-        # exclude:
-        #   - build-type: 'Debug'
-        #     sanitizer-type: 'san'
+        build-type: ['Release', 'Debug']
+        sanitizer-type: ['nosan', 'san']
+        exclude:
+          - build-type: 'Debug'
+            sanitizer-type: 'san'
     needs: docker-create-ubuntu-2204
 
     steps:
@@ -105,9 +105,9 @@ jobs:
           make docker
 
     - name: Run Tests
-      timeout-minutes: 15
+      timeout-minutes: 5
       run: |
-        CONTAINER_CMD="bash -lc 'source /opt/intel/oneapi/setvars.sh &&  make run-tests'" \
+        CONTAINER_CMD="make run-tests" \
           IMAGE_NAME="${{ env.IMAGE_NAME }}" \
           VERSION="${{ env.IMAGE_VERSION }}" \
           make docker

Makefile

@@ -117,12 +117,11 @@ run-tests:
 	@ctest --test-dir build -R wmd --verbose
 	@ctest --test-dir build -R large-vec --verbose
 	@ctest --test-dir build -R compile-lscsr --verbose
-	@ctest --test-dir build/libgnn/test --verbose
 
 # this command is slow since hooks are not stored in the container image
 # this is mostly for CI use
 docker-pre-commit:
 	@docker --context ${CONTAINER_CONTEXT} run --rm \
 	-v ${SRC_DIR}/:${CONTAINER_SRC_DIR} --privileged \
 	--workdir=${CONTAINER_WORKDIR} -t \
-	${IMAGE_NAME}:${VERSION} bash -lc "git config --global --add safe.directory /galois && make hooks && make pre-commit"
+	${IMAGE_NAME}:${VERSION} bash -lc "git config --global --add safe.directory /pando-galois && make hooks && make pre-commit"

libcusp/test/shad-dist-graph.cpp

@@ -53,10 +53,13 @@ int main() {
   sumGlobalNodes += graph->numMasters();
   sumGlobalEdges += graph->sizeEdges();
 
-  assert(sumGlobalNodes.reduce() == numNodes);
-  assert(sumGlobalNodes.reduce() == graph->globalSize());
-  assert(sumGlobalEdges.reduce() == numEdges);
-  assert(sumGlobalEdges.reduce() == graph->globalSizeEdges());
+  uint64_t reducedSumGlobalNodes = sumGlobalNodes.reduce();
+  uint64_t reducedSumGlobalEdges = sumGlobalEdges.reduce();
+
+  assert(reducedSumGlobalNodes == numNodes);
+  assert(reducedSumGlobalNodes == graph->globalSize());
+  assert(reducedSumGlobalEdges == numEdges);
+  assert(reducedSumGlobalEdges == graph->globalSizeEdges());
 
   std::cout << "Num. nodes/edges tests has been passed\n";
 

libgnn/include/galois/graphs/GNNGraph.h

@@ -24,8 +24,7 @@ namespace galois {
 // TODO remove the need to hardcode this path
 //! Path to location of all gnn files
 static const std::string default_gnn_dataset_path =
-    //"/net/ohm/export/iss/inputs/Learning/";
-    " nope";
+    "/home/hochan/inputs/Learning/";
 
 //! Helper struct to maintain start/end/size of any particular range. Mostly
 //! used for mask ranges.
@@ -71,9 +70,6 @@ class GNNGraph {
         std::string("[") +
         std::to_string(galois::runtime::getSystemNetworkInterface().ID) +
         std::string("] ");
-
-    std::cout << "input directory:" << input_directory_ << ", "
-              << " data set name:" << dataset_name << "\n";
     // load partition
     partitioned_graph_ =
         LoadPartition(input_directory_, dataset_name, partition_scheme);
@@ -1661,15 +1657,6 @@ class GNNGraph {
     }
     GALOIS_LOG_VERBOSE("Partition loading: File to read is {}", input_file);
 
-    std::cout << "input file:" << input_file << "\n";
-    if (FILE* fp = fopen(input_file.c_str(), "r")) {
-      std::cout << "succeeded to read the input file:" << input_file << "\n"
-                << std::flush;
-      fclose(fp);
-    } else {
-      std::cout << "failed to read the input file:" << input_file << "\n"
-                << std::flush;
-    }
     // load partition
     switch (partition_scheme) {
     case galois::graphs::GNNPartitionScheme::kOEC:
@@ -2411,6 +2398,23 @@ class GNNGraph {
     num_correct_.reset();
     total_checked_.reset();
 
+#if 0
+    std::cout << "single accuracy print:\n";
+    for (int i = *begin_owned(); i < *end_owned(); ++i) {
+      if (!IsValidForPhase(i, GNNPhase::kBatch)) {
+        continue;
+      }
+      //std::cout << subgraph_->SIDToLID(i) << ", " << galois::MaxIndex(num_label_classes_, &predictions[i * num_label_classes_]) <<
+      std::cout << "accuracy:" << subgraph_->SIDToLID(i) << ", " <<
+      predictions[i * num_label_classes_] << ", " <<
+      predictions[i * num_label_classes_ + 1] << ", " <<
+      predictions[i * num_label_classes_ + 2] << ", " <<
+      predictions[i * num_label_classes_ + 3] << ", " <<
+      predictions[i * num_label_classes_ + 4] << "-> " <<
+      galois::MaxIndex(num_label_classes_, &predictions[i * num_label_classes_]) <<
+      " vs " << GetSingleClassLabel(i) << "\n";
+    }
+#endif
     galois::do_all(
         // will only loop over sampled nodes if sampling is on
         galois::iterate(begin_owned(), end_owned()),

libgnn/test/CMakeLists.txt

@@ -1,11 +1,7 @@
 find_package(OpenMP)
 
-set(TESTINPUT "${Galois_SOURCE_DIR}/inputs")
-add_definitions("-DTESTER_DIR=\"${TESTINPUT}/tester/\"")
-add_definitions("-DCORA_DIR=\"${TESTINPUT}/cora/\"")
-
 set(hosts)
-set(host 6)
+set(host 12)
 while (${host} GREATER 1)
   list(APPEND hosts ${host})
   math(EXPR host "${host} - 1")
@@ -21,7 +17,7 @@ if (NOT GALOIS_ENABLE_GPU)
       ${GALOIS_TESTS}
       convlayer-test
       sage-layer-test
-      # l2norm-layer-test TODO(hc): L2Norm is not maintained
+      l2norm-layer-test
       softmaxlayer-test
       sigmoidlayer-test
       gnnconstruct-test
@@ -31,7 +27,7 @@ if (NOT GALOIS_ENABLE_GPU)
       epoch-test
       multilabel-epoch-test
       multilabel-read
-      # f1-test TODO(hc): it is a multilable test and will be fixed later
+      f1-test
       sample-bit-test
       gcn-sample-edge-test
   )

libgnn/test/accuracy-test.cpp

@@ -14,8 +14,7 @@ int main() {
 
   // load test graph
   auto test_graph = std::make_unique<galois::graphs::GNNGraph<char, void>>(
-      TESTER_DIR, "tester", galois::graphs::GNNPartitionScheme::kOEC, true,
-      false);
+      "tester", galois::graphs::GNNPartitionScheme::kOEC, true, false);
 
   std::vector<galois::GNNLayerType> layer_types = {
       galois::GNNLayerType::kGraphConvolutional};
@@ -35,22 +34,23 @@ int main() {
   //////////////////////////////////////////////////////////////////////////////
 
   galois::PointerWithSize<galois::GNNFloat> distributions = gnn->DoInference();
-
+  // accuracy will be 0.2: everything chooses the first 1 as the entire row
+  // is the same
   float pred_accuracy = gnn->GetGlobalAccuracy(distributions);
   GALOIS_LOG_VERBOSE("{}", pred_accuracy);
-  GALOIS_LOG_ASSERT(static_cast<int>(pred_accuracy * 1000) == 333);
+  GALOIS_LOG_ASSERT(pred_accuracy == static_cast<float>(0.2));
 
   // validation mode
   gnn->SetLayerPhases(galois::GNNPhase::kValidate);
   galois::PointerWithSize<galois::GNNFloat> dist2 = gnn->DoInference();
   pred_accuracy = gnn->GetGlobalAccuracy(dist2);
-  GALOIS_LOG_ASSERT(pred_accuracy == static_cast<float>(0));
+  GALOIS_LOG_ASSERT(pred_accuracy == static_cast<float>(0.0));
 
   // test mode
   gnn->SetLayerPhases(galois::GNNPhase::kTest);
   galois::PointerWithSize<galois::GNNFloat> dist3 = gnn->DoInference();
   pred_accuracy = gnn->GetGlobalAccuracy(dist3);
-  GALOIS_LOG_ASSERT(pred_accuracy == static_cast<float>(0));
+  GALOIS_LOG_ASSERT(pred_accuracy == static_cast<float>(0.0));
 
   // manufactured predictions to make sure it predicts things correctly based
   // on mode
@@ -62,11 +62,11 @@ int main() {
   gnn->SetLayerPhases(galois::GNNPhase::kTrain);
   pred_accuracy = gnn->GetGlobalAccuracy(mpred);
   GALOIS_LOG_VERBOSE("{}", pred_accuracy);
-  GALOIS_LOG_ASSERT(static_cast<int>(pred_accuracy * 1000) == 666);
+  GALOIS_LOG_ASSERT(pred_accuracy == static_cast<float>(0.8));
 
   gnn->SetLayerPhases(galois::GNNPhase::kValidate);
   pred_accuracy = gnn->GetGlobalAccuracy(mpred);
-  GALOIS_LOG_ASSERT(pred_accuracy == static_cast<float>(0.5));
+  GALOIS_LOG_ASSERT(pred_accuracy == static_cast<float>(0.0));
 
   gnn->SetLayerPhases(galois::GNNPhase::kTest);
   pred_accuracy = gnn->GetGlobalAccuracy(mpred);

libgnn/test/aggregate-sync-test.cpp

@@ -10,8 +10,7 @@ int main() {
   }
 
   auto test_graph = std::make_unique<galois::graphs::GNNGraph<char, void>>(
-      TESTER_DIR, "tester", galois::graphs::GNNPartitionScheme::kOEC, true,
-      false);
+      "tester", galois::graphs::GNNPartitionScheme::kOEC, true, false);
 
   // print edges for sanity
   for (size_t node = 0; node < test_graph->size(); node++) {
@@ -208,8 +207,7 @@ int main() {
   }
   //////////////////////////////////////////////////////////////////////////////
   auto test_graph_2 = std::make_unique<galois::graphs::GNNGraph<char, void>>(
-      TESTER_DIR, "tester", galois::graphs::GNNPartitionScheme::kCVC, true,
-      false);
+      "tester", galois::graphs::GNNPartitionScheme::kCVC, true, false);
   // print edges for sanity
   for (size_t node = 0; node < test_graph_2->size(); node++) {
     for (auto e = test_graph_2->edge_begin(node);

libgnn/test/back-conv-test.cpp

@@ -12,8 +12,7 @@ int main() {
                      num_threads);
   // load test graph
   galois::graphs::GNNGraph<char, void> test_graph(
-      TESTER_DIR, "tester", galois::graphs::GNNPartitionScheme::kCVC, true,
-      false);
+      "tester", galois::graphs::GNNPartitionScheme::kCVC, true, false);
   galois::PointerWithSize<galois::GNNFloat> feats =
       test_graph.GetLocalFeatures();
   for (size_t row = 0; row < test_graph.size(); row++) {

libgnn/test/convlayer-test.cpp

@@ -15,8 +15,7 @@ int main() {
                      num_threads);
   // load test graph
   galois::graphs::GNNGraph<char, void> test_graph(
-      TESTER_DIR, "tester", galois::graphs::GNNPartitionScheme::kOEC, true,
-      false);
+      "tester", galois::graphs::GNNPartitionScheme::kOEC, true, false);
 
   galois::PointerWithSize<galois::GNNFloat> feats =
       test_graph.GetLocalFeatures();