updates squeeze excitation layers

- added doc strings for squeeze excitation layers
- renaming layer/squeeze_excitation_layer to layer/squeeze_excitation

Author: wyli

niftynet/layer/squeeze_excitation_layer.py renamed to niftynet/layer/squeeze_excitation.py

@@ -12,6 +12,11 @@
 
 
 class ChannelSELayer(Layer):
+    """
+    Re-implementation of Squeeze-and-Excitation (SE) block described in::
+
+         Hu et al., Squeeze-and-Excitation Networks, arXiv:1709.01507
+    """
     def __init__(self,
                  func='AVG',
                  reduction_ratio=16,
@@ -62,8 +67,17 @@ def layer_op(self, input_tensor):
         output_tensor = tf.multiply(input_tensor, fc_out_2)
 
         return output_tensor
-    
+
+
 class SpatialSELayer(Layer):
+    """
+    Re-implementation of SE block -- squeezing spatially
+    and exciting channel-wise described in::
+
+        Roy et al., Concurrent Spatial and Channel Squeeze & Excitation
+        in Fully Convolutional Networks, arXiv:1803.02579
+
+    """
     def __init__(self,
                  name='spatial_squeeze_excitation'):
         super(SpatialSELayer, self).__init__(name=name)
@@ -75,15 +89,24 @@ def layer_op(self, input_tensor):
                                   with_bn=False,
                                   acti_func='sigmoid',
                                   name="se_conv")
-        
+
         squeeze_tensor = conv(input_tensor)
-        
+
         # spatial excitation
         output_tensor = tf.multiply(input_tensor, squeeze_tensor)
 
         return output_tensor
-    
+
+
 class ChannelSpatialSELayer(Layer):
+    """
+    Re-implementation of concurrent spatial and channel
+    squeeze & excitation::
+
+        Roy et al., Concurrent Spatial and Channel Squeeze & Excitation
+        in Fully Convolutional Networks, arXiv:1803.02579
+
+    """
     def __init__(self,
                  func='AVG',
                  reduction_ratio=16,
@@ -99,7 +122,7 @@ def layer_op(self, input_tensor):
                              reduction_ratio=self.reduction_ratio,
                              name='cSE')
         sSE = SpatialSELayer(name='sSE')
-    
+
         output_tensor = tf.add(cSE(input_tensor), sSE(input_tensor))
 
         return output_tensor

niftynet/network/se_resnet.py

@@ -10,7 +10,7 @@
 from niftynet.layer.fully_connected import FCLayer
 from niftynet.layer.base_layer import TrainableLayer
 from niftynet.layer.convolution import ConvolutionalLayer
-from niftynet.layer.squeeze_excitation_layer import ChannelSELayer
+from niftynet.layer.squeeze_excitation import ChannelSELayer
 from niftynet.network.base_net import BaseNet
 
 SE_ResNetDesc = namedtuple('SE_ResNetDesc', ['bn', 'fc', 'conv1', 'blocks'])

tests/squeeze_excitation_layer_test.py renamed to tests/squeeze_excitation_test.py

@@ -2,9 +2,9 @@
 from __future__ import absolute_import, print_function
 
 import tensorflow as tf
-from niftynet.layer.squeeze_excitation_layer import ChannelSELayer
-from niftynet.layer.squeeze_excitation_layer import SpatialSELayer
-from niftynet.layer.squeeze_excitation_layer import ChannelSpatialSELayer
+from niftynet.layer.squeeze_excitation import ChannelSELayer
+from niftynet.layer.squeeze_excitation import SpatialSELayer
+from niftynet.layer.squeeze_excitation import ChannelSpatialSELayer
 
 class SETest(tf.test.TestCase):
     def test_cSE_3d_shape(self):