removed batch norm for now

pkmital · pkmital · commit 63863747590c · 2016-04-06T09:37:54.000-07:00
diff --git a/python/10_residual_network.py b/python/10_residual_network.py
@@ -53,7 +53,7 @@ def residual_network(x, n_outputs,
     # %%
     # First convolution expands to 64 channels and downsamples
     net = conv2d(x, 64, k_h=7, k_w=7,
-                 batch_norm=True, name='conv1',
+                 name='conv1',
                  activation=activation)
 
     # %%
@@ -74,17 +74,17 @@ def residual_network(x, n_outputs,
             name = 'block_%d/layer_%d' % (block_i, layer_i)
             conv = conv2d(net, block.bottleneck_size, k_h=1, k_w=1,
                           padding='VALID', stride_h=1, stride_w=1,
-                          activation=activation, batch_norm=True,
+                          activation=activation,
                           name=name + '/conv_in')
 
             conv = conv2d(conv, block.bottleneck_size, k_h=3, k_w=3,
                           padding='SAME', stride_h=1, stride_w=1,
-                          activation=activation, batch_norm=True,
+                          activation=activation,
                           name=name + '/conv_bottleneck')
 
             conv = conv2d(conv, block.num_filters, k_h=1, k_w=1,
                           padding='VALID', stride_h=1, stride_w=1,
-                          activation=activation, batch_norm=True,
+                          activation=activation,
                           name=name + '/conv_out')
 
             net = conv + net
diff --git a/python/libs/connections.py b/python/libs/connections.py
@@ -54,7 +54,7 @@ def conv2d(x, n_filters,
                 'b', [n_filters],
                 initializer=tf.truncated_normal_initializer(stddev=stddev))
             conv = conv + b
-        return conv
+        return activation(conv)
 
 
 def linear(x, n_units, scope=None, stddev=0.02,
