def inference_v2(self, im):
l0 = im
l1 = self._conv_layer(l0,
32, (5, 5), (1, 1), (2, 2), (2, 2),
name='l1',
flag=True)
l2 = self._conv_layer(l1,
32, (5, 5), (1, 1), (2, 2), (2, 2),
name='l2',
flag=True)
l3 = self._conv_layer(l2,
64, (3, 3), (1, 1), (2, 2), (2, 2),
name='l3',
flag=True)
l4 = self._conv_layer(l3,
64, (3, 3), (1, 1), (0, 0), (0, 0),
name='l4',
flag=False)
l5 = self._conv_layer(l4,
128, (3, 3), (1, 1), (0, 0), (0, 0),
name='l5',
flag=False)
fc0 = tf.reshape(l5, [self.batch_size, -1])
fc1 = tl.fc(fc0, 64, name='fc1')
fc2 = tl.fc(fc1, 32, name='fc2')
fc3 = tl.fc(fc2, 4, name='fc3')
return fc3
def inference(self, im):
l0 = im
l1 = self._conv_layer(l0,
32, (5, 5), (1, 1), (2, 2), (2, 2),
name='l1')
l2 = self._conv_layer(l1,
32, (5, 5), (1, 1), (2, 2), (2, 2),
name='l2')
l3 = self._conv_layer(l2,
64, (5, 5), (1, 1), (2, 2), (2, 2),
name='l3')
fc0 = tf.reshape(l3, [self.batch_size, -1])
fc1 = tl.fc(fc0, 64, name='fc1')
fc2 = tl.fc(fc1, 101, name='fc2')
return fc2