add variable in batchrenorm. fix bug in CacheData

tensorpack/dataflow/common.py

@@ -566,6 +566,7 @@ class CacheData(ProxyDataFlow):
 
     def get_data(self):
         if len(self.buffer):
+            if self.shuffle:
                 self.rng.shuffle(self.buffer)
             for dp in self.buffer:
                 yield dp

tensorpack/models/batch_norm.py

@@ -232,7 +232,6 @@ def BatchNorm(x, use_local_stat=None, decay=0.9, epsilon=1e-5,
     return ret
 
 
-# TODO support NCHW
 @layer_register(log_shape=False)
 def BatchRenorm(x, rmax, dmax, decay=0.9, epsilon=1e-5,
                 use_scale=True, use_bias=True, data_format='NHWC'):
@@ -308,6 +307,13 @@ def BatchRenorm(x, rmax, dmax, decay=0.9, epsilon=1e-5,
                 x, moving_mean, moving_var, beta, gamma, epsilon)
 
     if ctx.is_main_training_tower:
-        return update_bn_ema(xn, batch_mean, batch_var, moving_mean, moving_var, decay)
+        ret = update_bn_ema(xn, batch_mean, batch_var, moving_mean, moving_var, decay)
     else:
-        return tf.identity(xn, name='output')
+        ret = tf.identity(xn, name='output')
+
+    vh = ret.variables = VariableHolder(mean=moving_mean, variance=moving_var)
+    if use_scale:
+        vh.gamma = gamma
+    if use_bias:
+        vh.beta = beta
+    return ret