def get_data():
inputs_tr, targets_tr, sort_indices_tr, _ = create_data(
batch_size_tr, num_elements_min_max_tr)
inputs_tr = utils_tf.set_zero_edge_features(inputs_tr, 1)
inputs_tr = utils_tf.set_zero_global_features(inputs_tr, 1)
# Test/generalization.
inputs_ge, targets_ge, sort_indices_ge, _ = create_data(
batch_size_ge, num_elements_min_max_ge)
inputs_ge = utils_tf.set_zero_edge_features(inputs_ge, 1)
inputs_ge = utils_tf.set_zero_global_features(inputs_ge, 1)
targets_tr = utils_tf.set_zero_global_features(targets_tr, 1)
targets_ge = utils_tf.set_zero_global_features(targets_ge, 1)
return inputs_tr, targets_tr, sort_indices_tr, inputs_ge, targets_ge, sort_indices_ge
def test_fill_global_state(self, global_size):
"""Tests for filling the global state with a constant content."""
for g in self.graphs_dicts_in:
g.pop("globals")
graphs_tuple = utils_tf.data_dicts_to_graphs_tuple(self.graphs_dicts_in)
n_graphs = self.reference_graph.n_edge.shape[0]
graphs_tuple = utils_tf.set_zero_global_features(graphs_tuple, global_size)
self.assertAllEqual((n_graphs, global_size),
graphs_tuple.globals.get_shape().as_list())
def test_fill_state_user_specified_types(self, dtype):
"""Tests that the features are created with the correct default type."""
for g in self.graphs_dicts_in:
g.pop("nodes")
g.pop("globals")
g.pop("edges")
graphs_tuple = utils_tf.data_dicts_to_graphs_tuple(self.graphs_dicts_in)
graphs_tuple = utils_tf.set_zero_edge_features(graphs_tuple, 1, dtype)
graphs_tuple = utils_tf.set_zero_node_features(graphs_tuple, 1, dtype)
graphs_tuple = utils_tf.set_zero_global_features(graphs_tuple, 1, dtype)
self.assertEqual(dtype, graphs_tuple.edges.dtype)
self.assertEqual(dtype, graphs_tuple.nodes.dtype)
self.assertEqual(dtype, graphs_tuple.globals.dtype)
def test_fill_state_default_types(self):
"""Tests that the features are created with the correct default type."""
for g in self.graphs_dicts_in:
g.pop("nodes")
g.pop("globals")
g.pop("edges")
graphs_tuple = utils_tf.data_dicts_to_graphs_tuple(self.graphs_dicts_in)
graphs_tuple = utils_tf.set_zero_edge_features(graphs_tuple, edge_size=1)
graphs_tuple = utils_tf.set_zero_node_features(graphs_tuple, node_size=1)
graphs_tuple = utils_tf.set_zero_global_features(
graphs_tuple, global_size=1)
self.assertEqual(tf.float32, graphs_tuple.edges.dtype)
self.assertEqual(tf.float32, graphs_tuple.nodes.dtype)
self.assertEqual(tf.float32, graphs_tuple.globals.dtype)
def test_fill_global_state_dynamic(self, global_size):
"""Tests for filling the global state with a constant content."""
for g in self.graphs_dicts_in:
g.pop("globals")
graphs_tuple = utils_tf.data_dicts_to_graphs_tuple(self.graphs_dicts_in)
# Hide global shape information
graphs_tuple = graphs_tuple._replace(
n_node=tf.placeholder_with_default(graphs_tuple.n_node, shape=[None]))
n_graphs = self.reference_graph.n_edge.shape[0]
graphs_tuple = utils_tf.set_zero_global_features(graphs_tuple, global_size)
with self.test_session() as sess:
actual_globals = sess.run(graphs_tuple.globals)
self.assertNDArrayNear(
np.zeros((n_graphs, global_size)), actual_globals, err=1e-4)
def zeros_graph(sample_graph, edge_size, node_size, global_size):
zeros_graphs = sample_graph.replace(nodes=None, edges=None, globals=None)
zeros_graphs = utils_tf.set_zero_edge_features(zeros_graphs, edge_size)
zeros_graphs = utils_tf.set_zero_node_features(zeros_graphs, node_size)
zeros_graphs = utils_tf.set_zero_global_features(zeros_graphs, global_size)
return zeros_graphs
def main():
all_graphs = test_graph()
inputs = [all_graphs[0][0]]
in_graphs = utils_tf.data_dicts_to_graphs_tuple(inputs)
in_graphs = utils_tf.set_zero_global_features(in_graphs, 1)
dtype_shape_from_graphs_tuple(in_graphs)