assert for simplified conv api

Author: zsdonghao

tensorlayer/layers.py

@@ -1710,7 +1710,7 @@ def Conv2d(net, n_filter=32, filter_size=(3, 3), strides=(1, 1), act = None,
     >>> conv2 = Conv2d(conv2, 128, (3, 3), act=tf.nn.relu, padding='SAME', W_init=w_init, b_init=b_init, name='conv2_2')
     >>> pool2 = MaxPool2d(conv2, (2, 2), padding='SAME', name='pool2')
     """
-    # assert len(strides) == 2, print("len(strides)==2, Conv2d and Conv2dLayer are different.")
+    assert len(strides) == 2, "len(strides) should be 2, Conv2d and Conv2dLayer are different."
     if act is None:
         act = tf.identity
     net = Conv2dLayer(net,
@@ -1742,7 +1742,7 @@ def DeConv2d(net, n_out_channel = 32, filter_size=(3, 3),
     act : None or activation function.
     others : see :class:`DeConv2dLayer`.
     """
-    # assert len(strides) == 2, print("len(strides)==2, DeConv2d and DeConv2dLayer are different.")
+    assert len(strides) == 2, "len(strides) should be 2, DeConv2d and DeConv2dLayer are different."
     if act is None:
         act = tf.identity
     if batch_size is None:
@@ -1772,7 +1772,7 @@ def MaxPool2d(net, filter_size=(2, 2), strides=None, padding='SAME', name='maxpo
     """
     if strides is None:
         strides = filter_size
-    # assert len(strides) == 2, print("len(strides)==2, MaxPool2d and PoolLayer are different.")
+    assert len(strides) == 2, "len(strides) should be 2, MaxPool2d and PoolLayer are different."
     net = PoolLayer(net, ksize=[1, filter_size[0], filter_size[1], 1],
             strides=[1, strides[0], strides[1], 1],
             padding=padding,
@@ -1792,7 +1792,7 @@ def MeanPool2d(net, filter_size=(2, 2), strides=None, padding='SAME', name='mean
     """
     if strides is None:
         strides = filter_size
-    # assert len(strides) == 2, print("len(strides)==2, MeanPool2d and PoolLayer are different.")
+    assert len(strides) == 2, "len(strides) should be 2, MeanPool2d and PoolLayer are different."
     net = PoolLayer(net, ksize=[1, filter_size[0], filter_size[1], 1],
             strides=[1, strides[0], strides[1], 1],
             padding=padding,