def populated_graph_db(request) -> graph_tuple_database.Database: """A test fixture which yields a graph database with random graph tuples.""" with testing_databases.DatabaseContext(graph_tuple_database.Database, request.param) as db: random_graph_tuple_database_generator.PopulateDatabaseWithRandomGraphTuples( db, graph_count=100, graph_y_dimensionality=2) yield db
def test_PopulateDatahaseithRandomGraphTuples( db: graph_tuple_database.Database, graph_count: int, node_x_dimensionality: int, node_y_dimensionality: int, graph_x_dimensionality: int, graph_y_dimensionality: int, with_data_flow: bool, split_count: int, ): """Test populating databases.""" random_graph_tuple_database_generator.PopulateDatabaseWithRandomGraphTuples( db=db, graph_count=graph_count, node_x_dimensionality=node_x_dimensionality, node_y_dimensionality=node_y_dimensionality, graph_x_dimensionality=graph_x_dimensionality, graph_y_dimensionality=graph_y_dimensionality, with_data_flow=with_data_flow, split_count=split_count, ) with db.Session() as session: assert ( session.query(sql.func.count(graph_tuple_database.GraphTuple.id)).scalar() == graph_count ) assert ( session.query( sql.func.min(graph_tuple_database.GraphTuple.node_x_dimensionality) ).scalar() == node_x_dimensionality ) assert ( session.query( sql.func.min(graph_tuple_database.GraphTuple.node_y_dimensionality) ).scalar() == node_y_dimensionality ) assert ( session.query( sql.func.min(graph_tuple_database.GraphTuple.graph_y_dimensionality) ).scalar() == graph_y_dimensionality ) assert ( session.query( sql.func.min(graph_tuple_database.GraphTuple.graph_y_dimensionality) ).scalar() == graph_y_dimensionality )
def graph_db(request) -> graph_tuple_database.Database: """A test fixture which returns a graph database with random graphs.""" graph_y_dimensionality, node_y_dimensionality = request.param db = graph_tuple_database.Database(testing_databases.GetDatabaseUrls()[0]) random_graph_tuple_database_generator.PopulateDatabaseWithRandomGraphTuples( db, graph_count=100, graph_y_dimensionality=graph_y_dimensionality, node_y_dimensionality=node_y_dimensionality, ) return db
def populated_graph_db( request, y_dimensionalities: Tuple[int, int] ) -> graph_tuple_database.Database: """Test fixture which returns a populated graph database.""" node_y_dimensionality, graph_y_dimensionality = y_dimensionalities with testing_databases.DatabaseContext( graph_tuple_database.Database, request.param ) as db: random_graph_tuple_database_generator.PopulateDatabaseWithRandomGraphTuples( db, graph_count=100, node_y_dimensionality=node_y_dimensionality, graph_y_dimensionality=graph_y_dimensionality, ) yield db
def node_classification_graph_db( request, graph_count: int, node_y_dimensionality: int, ) -> graph_tuple_database.Database: """A test fixture which yields a graph database with 256 OpenCL IR entries.""" with testing_databases.DatabaseContext( graph_tuple_database.Database, request.param ) as db: random_graph_tuple_database_generator.PopulateDatabaseWithRandomGraphTuples( db, graph_count, node_y_dimensionality=node_y_dimensionality, node_x_dimensionality=2, graph_y_dimensionality=0, split_count=3, ) yield db
def graph_db() -> graph_tuple_database.Database: """A test fixture which creates a session-level graph database.""" with testing_databases.DatabaseContext( graph_tuple_database.Database, testing_databases.GetDatabaseUrls()[0] ) as db: random_graph_tuple_database_generator.PopulateDatabaseWithRandomGraphTuples( db, graph_count=20, node_x_dimensionality=2, node_y_dimensionality=0, graph_x_dimensionality=2, graph_y_dimensionality=2, with_data_flow=False, split_count=3, ) yield db
def graph_db( request, y_dimensionalities: Tuple[int, int], ) -> graph_tuple_database.Database: """A test fixture which enumerates session-level graph databases.""" node_y_dimensionality, graph_y_dimensionality = y_dimensionalities with testing_databases.DatabaseContext(graph_tuple_database.Database, request.param) as db: random_graph_tuple_database_generator.PopulateDatabaseWithRandomGraphTuples( db, graph_count=100, node_x_dimensionality=2, node_y_dimensionality=node_y_dimensionality, graph_x_dimensionality=2, graph_y_dimensionality=graph_y_dimensionality, with_data_flow=False, split_count=3, ) yield db
def populated_db_and_rows( request, graph_count: int, node_x_dimensionality: int, node_y_dimensionality: int, graph_x_dimensionality: int, graph_y_dimensionality: int, with_data_flow: bool, split_count: int, ) -> random_graph_tuple_database_generator.DatabaseAndRows: """Generate a populated database and a list of rows.""" with testing_databases.DatabaseContext(graph_tuple_database.Database, request.param) as db: yield random_graph_tuple_database_generator.PopulateDatabaseWithRandomGraphTuples( db, graph_count, node_x_dimensionality=node_x_dimensionality, node_y_dimensionality=node_y_dimensionality, graph_x_dimensionality=graph_x_dimensionality, graph_y_dimensionality=graph_y_dimensionality, with_data_flow=with_data_flow, split_count=split_count, )
) @test.Fixture(scope="session", params=testing_databases.GetDatabaseUrls()) def node_y_graph_db( >>>>>>> de933d07a... Add a node text embedding enum.:deeplearning/ml4pl/models/ggnn/ggnn_test.py request, graph_count: int, node_y_dimensionality: int, ) -> graph_tuple_database.Database: """A test fixture which yields a graph database with 256 OpenCL IR entries.""" with testing_databases.DatabaseContext( graph_tuple_database.Database, request.param ) as db: random_graph_tuple_database_generator.PopulateDatabaseWithRandomGraphTuples( db, graph_count, node_y_dimensionality=node_y_dimensionality, node_x_dimensionality=2, graph_y_dimensionality=0, split_count=3, ) yield db @test.Fixture( scope="session", params=testing_databases.GetDatabaseUrls(), namer=testing_databases.DatabaseUrlNamer("graph_db"), ) def graph_classification_graph_db( request, graph_count: int, graph_y_dimensionality: int, ) -> graph_tuple_database.Database: """A test fixture which yields a graph database with 256 OpenCL IR entries."""