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."""
