add `hybridize()`

cnocr/symbols/crnn.py

@@ -42,6 +42,7 @@ def gen_network(model_name, hp):
             else (64, 128, 256, 512)
         )
         densenet = DenseNet(layer_channels)
+        densenet.hybridize()
         model = CRnn(hp, densenet)
     elif model_name.startswith('conv-lite'):
         hp.seq_len_cmpr_ratio = 4

tests/test_models.py

 # coding: utf-8
 import os
 import sys
-import logging
 from copy import deepcopy
 import pytest
 import mxnet as mx
@@ -44,7 +43,7 @@ def test_densenet():
     net.initialize()
     y = net(x)
     logger.info(net)
-    logger.info(y.shape)  # (128, 512, 1, 69)
+    logger.info(y.shape)  # (128, 512, 1, 70)
     assert y.shape[2] == 1
     logger.info('number of parameters: %d', cal_num_params(net))  # 1748224