diff --git a/tf/tfprocess.py b/tf/tfprocess.py
index bcfc1c0d..c67a6df6 100644
--- a/tf/tfprocess.py
+++ b/tf/tfprocess.py
@@ -108,6 +108,7 @@ def __init__(self, cfg):
         loss_scale = self.cfg['training'].get('loss_scale', 128)
         self.virtual_batch_size = self.cfg['model'].get(
             'virtual_batch_size', None)
+        self.SE_blocks = self.cfg['model'].get('se_blocks', None)
 
         if precision == 'single':
             self.model_dtype = tf.float32
@@ -1036,7 +1037,9 @@ def batch_norm(self, input, name, scale=False):
                 virtual_batch_size=self.virtual_batch_size,
                 name=name)(input)
 
-    def squeeze_excitation(self, inputs, channels, name):
+    def squeeze_excitation(self, inputs, channels, block_num, name):
+        if self.SE_blocks is not None and block_num not in self.SE_blocks:
+            return inputs
         assert channels % self.SE_ratio == 0
 
         pooled = tf.keras.layers.GlobalAveragePooling2D(
@@ -1069,7 +1072,7 @@ def conv_block(self,
         return tf.keras.layers.Activation('relu')(self.batch_norm(
             conv, name=name + '/bn', scale=bn_scale))
 
-    def residual_block(self, inputs, channels, name):
+    def residual_block(self, inputs, channels, block_num, name):
         conv1 = tf.keras.layers.Conv2D(channels,
                                        3,
                                        use_bias=False,
@@ -1094,6 +1097,7 @@ def residual_block(self, inputs, channels, name):
                                                        name + '/2/bn',
                                                        scale=True),
                                        channels,
+                                       block_num,
                                        name=name + '/se')
         return tf.keras.layers.Activation('relu')(tf.keras.layers.add(
             [inputs, out2]))
@@ -1107,6 +1111,7 @@ def construct_net(self, inputs):
         for i in range(self.RESIDUAL_BLOCKS):
             flow = self.residual_block(flow,
                                        self.RESIDUAL_FILTERS,
+                                       i + 1,
                                        name='residual_{}'.format(i + 1))
 
         # Policy head