def test_update_edges_independent(self):
with self.test_session() as sess:
adj_mt = tf.convert_to_tensor(
np.array([[0, 1, 1], [1, 0, 1], [1, 1, 0]], dtype=np.int32))
points_data = np.array([[1], [2], [3]], dtype=np.float32)
edges_data = tf.constant(
np.array([[5], [6], [7], [8], [9], [10]], dtype=np.float32))
A = DynamicAdjacentMatrix(adj_mt=adj_mt,
points_data=points_data,
edges_data=edges_data)
A.global_attr = tf.convert_to_tensor(
np.array([[21]], dtype=np.float32))
def update_edges(x):
def fn(x):
return x * 2
return tf.map_fn(fn, elems=(x))
A.update_edges_independent(update_edges)
self.assertAllClose(A.edges_data.eval(), edges_data * 2, atol=1e-5)
def test_update_globals(self):
with self.test_session() as sess:
adj_mt = tf.convert_to_tensor(
np.array([[0, 1, 1], [1, 0, 1], [1, 1, 0]], dtype=np.int32))
points_data = np.array([[1], [2], [3]], dtype=np.float32)
edges_data = tf.constant(
np.array([[5], [6], [7], [8], [9], [10]], dtype=np.float32))
A = DynamicAdjacentMatrix(adj_mt=adj_mt,
points_data=points_data,
edges_data=edges_data)
A.global_attr = tf.convert_to_tensor(
np.array([[21]], dtype=np.float32))
def update_global(x):
def fn(x):
return tf.reshape(tf.reduce_sum(x), [1])
return tf.map_fn(fn, elems=(x))
A.update_global(update_global)
self.assertAllClose(A.global_attr.eval(), [[30.5]], atol=1e-5)