Implementing batch normalization

bob/learn/tensorflow/layers/Layer.py

@@ -69,12 +69,12 @@ class Layer(object):
         #with tf.variable_scope(name):
         phase_train = tf.convert_to_tensor(phase_train, dtype=tf.bool)
         n_out = int(x.get_shape()[-1])
-        self.beta = tf.Variable(tf.constant(0.0, shape=[n_out], dtype=x.dtype),
-                                name=name + '_beta',
+        self.beta = tf.get_variable(name + '_beta',
+                                    initializer=tf.constant(0.0, shape=[n_out], dtype=x.dtype),
                                     trainable=True,
                                     dtype=x.dtype)
-        self.gamma = tf.Variable(tf.constant(1.0, shape=[n_out], dtype=x.dtype),
-                                 name=name + '_gamma',
+        self.gamma = tf.get_variable(name + '_gamma',
+                                     initializer=tf.constant(1.0, shape=[n_out], dtype=x.dtype),
                                      trainable=True,
                                      dtype=x.dtype)
 

bob/learn/tensorflow/network/SequenceNetwork.py

@@ -244,7 +244,9 @@ class SequenceNetwork(six.with_metaclass(abc.ABCMeta, object)):
                 self.sequence_net[k].b.assign(hdf5.read(self.sequence_net[k].b.name)).eval(session=session)
                 session.run(self.sequence_net[k].b)
 
-                
+                if self.sequence_net[k].batch_norm:
+                    self.sequence_net[k].beta.assign(hdf5.read(self.sequence_net[k].beta.name)).eval(session=session)
+                    self.sequence_net[k].gamma.assign(hdf5.read(self.sequence_net[k].gamma.name)).eval(session=session)
 
         hdf5.cd("..")
 

bob/learn/tensorflow/test/test_cnn_scratch.py

@@ -54,7 +54,7 @@ def validate_network(validation_data, validation_labels, directory):
         path = os.path.join(directory, "model.hdf5")
         #path = os.path.join(directory, "model.ckp")
         #scratch = SequenceNetwork(default_feature_layer="fc1")
-        scratch = SequenceNetwork()
+        scratch = SequenceNetwork(default_feature_layer="fc1")
         #scratch.load_original(session, os.path.join(directory, "model.ckp"))
         scratch.load(bob.io.base.HDF5File(path),
                      shape=validation_shape, session=session)
@@ -94,8 +94,10 @@ def test_cnn_trainer_scratch():
                       prefetch=False,
                       temp_dir=directory)
     trainer.train(train_data_shuffler)
+    del trainer
+    del scratch
 
-    import ipdb; ipdb.set_trace();
+    #import ipdb; ipdb.set_trace();
 
     accuracy = validate_network(validation_data, validation_labels, directory)