def test_train(self):
""" Test reader for training
"""
coco = Reader(
self.coco_conf['DATA'], self.coco_conf['TRANSFORM'], maxiter=1000)
train_rd = coco.train()
self.assertTrue(train_rd is not None)
ct = 0
total = 0
bytes = 0
prev_ts = None
for sample in train_rd():
if prev_ts is None:
start_ts = time.time()
prev_ts = start_ts
ct += 1
bytes += 4 * sample[0][0].size * len(sample[0])
self.assertTrue(sample is not None)
cost = time.time() - prev_ts
if cost >= 1.0:
total += ct
qps = total / (time.time() - start_ts)
bps = bytes / (time.time() - start_ts)
logging.info('got %d/%d samples in %.3fsec with qps:%d bps:%d' %
(ct, total, cost, qps, bps))
bytes = 0
ct = 0
prev_ts = time.time()
total += ct
self.assertEqual(total, coco._maxiter)
def test_rcnn_train(self):
""" Test reader for training
"""
anno = self.rcnn_conf['DATA']['TRAIN']['ANNO_FILE']
if not os.path.exists(anno):
logging.error('exit test_rcnn for not found file[%s]' % (anno))
return
rcnn = Reader(self.rcnn_conf['DATA'], self.rcnn_conf['TRANSFORM'], 10)
rcnn_rd = rcnn.train()
self.assertTrue(rcnn_rd is not None)
ct = 0
out = None
for sample in rcnn_rd():
out = sample
ct += 1
self.assertTrue(sample is not None)
self.assertEqual(out[0][0].shape[0], 3)
self.assertEqual(out[0][1].shape[0], 3)
self.assertEqual(out[0][3].shape[1], 4)
self.assertEqual(out[0][4].shape[1], 1)
self.assertEqual(out[0][5].shape[1], 1)
self.assertGreaterEqual(ct, rcnn._maxiter)
