diff --git a/python/mxnet/gluon/contrib/cnn/conv_layers.py b/python/mxnet/gluon/contrib/cnn/conv_layers.py
index 098463eca968..c4924c130a28 100644
--- a/python/mxnet/gluon/contrib/cnn/conv_layers.py
+++ b/python/mxnet/gluon/contrib/cnn/conv_layers.py
@@ -313,7 +313,8 @@ def __init__(self, channels, kernel_size=(1, 1), strides=(1, 1), padding=(0, 0),
                 dilation = (dilation,) * len(kernel_size)
             self._op_name = op_name
 
-            offset_channels = 27
+            offset_channels = num_deformable_group * 3 * kernel_size[0] * kernel_size[1]
+            self.offset_split_index = num_deformable_group * 2 * kernel_size[0] * kernel_size[1]
             self._kwargs_offset = {
                 'kernel': kernel_size, 'stride': strides, 'dilate': dilation,
                 'pad': padding, 'num_filter': offset_channels, 'num_group': groups,
@@ -377,8 +378,8 @@ def hybrid_forward(self, F, x, offset_weight, deformable_conv_weight, offset_bia
         else:
             offset = F.Convolution(x, offset_weight, offset_bias, cudnn_off=True, **self._kwargs_offset)
 
-        offset_t = F.slice_axis(offset, axis=1, begin=0, end=18)
-        mask = F.slice_axis(offset, axis=1, begin=18, end=None)
+        offset_t = F.slice_axis(offset, axis=1, begin=0, end=self.offset_split_index)
+        mask = F.slice_axis(offset, axis=1, begin=self.offset_split_index, end=None)
         mask = F.sigmoid(mask) * 2
 
         if deformable_conv_bias is None:
diff --git a/tests/python/unittest/test_gluon_contrib.py b/tests/python/unittest/test_gluon_contrib.py
index fdba553c8560..0ed0d4e8a545 100644
--- a/tests/python/unittest/test_gluon_contrib.py
+++ b/tests/python/unittest/test_gluon_contrib.py
@@ -411,6 +411,10 @@ def test_ModulatedDeformableConvolution():
     net = nn.HybridSequential()
     net.add(
         DeformableConvolution(10, kernel_size=(3, 3), strides=1, padding=0),
+        DeformableConvolution(10, kernel_size=(1, 1), strides=1, padding=0),
+        DeformableConvolution(10, kernel_size=(5, 5), strides=1, padding=0),
+        DeformableConvolution(10, kernel_size=(3, 5), strides=1, padding=0),
+        DeformableConvolution(10, kernel_size=(5, 1), strides=1, padding=0, num_deformable_group=2),
         DeformableConvolution(10, kernel_size=(3, 2), strides=1, padding=0, activation='relu',
                                offset_use_bias=False, use_bias=False),
         DeformableConvolution(10, kernel_size=(3, 2), strides=1, padding=0, activation='relu',