modified normaliztion to support batch_norm for fp16
@@ -21,10 +21,13 @@ def normalize(inputs, training, norm_type):
begin_norm_axis=1,
begin_params_axis=-1)
else:
+ inputs = tf.expand_dims(input=inputs, axis= 1)
+ print(inputs)
outputs = tf.layers.batch_normalization(
inputs=inputs,
training=training,
)
+ outputs=tf.squeeze(outputs, axis=1)
return outputs
