def test_fastattn(self):
nodes = tf.constant([1, 3], dtype=tf.float32)
nodes2 = tf.constant([1, 3], dtype=tf.float32)
fused = efficientdet_arch.fuse_features([nodes, nodes2], 'fastattn')
with self.cached_session() as sess:
sess.run(tf.global_variables_initializer())
self.assertAllCloseAccordingToType(fused, [0.99995, 2.99985])
def test_channel_attn(self):
nodes = tf.constant([1, 3], dtype=tf.float32)
nodes2 = tf.constant([1, 3], dtype=tf.float32)
fused = efficientdet_arch.fuse_features([nodes, nodes2], 'channel_attn')
with self.cached_session() as sess:
# initialize weights
sess.run(tf.global_variables_initializer())
self.assertAllCloseAccordingToType(fused, [1.0, 3.0])
def test_sum(self):
tf.disable_eager_execution()
nodes = tf.constant([1, 3])
nodes2 = tf.constant([1, 3])
fused = efficientdet_arch.fuse_features([nodes, nodes2], 'sum')
self.assertAllCloseAccordingToType(fused, [2, 6])
