def test_detection_output(self):
program = Program()
with program_guard(program):
pb = layers.data(name='prior_box',
shape=[10, 4],
append_batch_size=False,
dtype='float32')
pbv = layers.data(name='prior_box_var',
shape=[10, 4],
append_batch_size=False,
dtype='float32')
loc = layers.data(name='target_box',
shape=[2, 10, 4],
append_batch_size=False,
dtype='float32')
scores = layers.data(name='scores',
shape=[2, 10, 20],
append_batch_size=False,
dtype='float32')
out = layers.detection_output(scores=scores,
loc=loc,
prior_box=pb,
prior_box_var=pbv)
out2, index = layers.detection_output(scores=scores,
loc=loc,
prior_box=pb,
prior_box_var=pbv,
return_index=True)
self.assertIsNotNone(out)
self.assertIsNotNone(out2)
self.assertIsNotNone(index)
self.assertEqual(out.shape[-1], 6)
print(str(program))
def test_detection_output(self):
program = Program()
with program_guard(program):
pb = layers.data(
name='prior_box',
shape=[10, 4],
append_batch_size=False,
dtype='float32')
pbv = layers.data(
name='prior_box_var',
shape=[10, 4],
append_batch_size=False,
dtype='float32')
loc = layers.data(
name='target_box',
shape=[2, 10, 4],
append_batch_size=False,
dtype='float32')
scores = layers.data(
name='scores',
shape=[2, 10, 20],
append_batch_size=False,
dtype='float32')
out = layers.detection_output(
scores=scores, loc=loc, prior_box=pb, prior_box_var=pbv)
self.assertIsNotNone(out)
self.assertEqual(out.shape[-1], 6)
print(str(program))