Further fix the memory for Hierarchical RNN

Sequences should be sorted according to the number of subsequences they have.

python/paddle/trainer_config_helpers/layers.py

@@ -21,7 +21,6 @@ from .evaluators import *
 from .poolings import MaxPooling, AvgPooling, BasePoolingType
 from .attrs import *
 from .default_decorators import *
-
 try:
     import cPickle as pickle
 except ImportError:
@@ -204,6 +203,25 @@ ERROR_CLIPPING = 'error_clipping_threshold'
 DROPOUT = 'drop_rate'
 
 
+def check_input(input):
+    """
+    Check input is a LayerOutput or list of LayerOutput or tuple of LayerOutput
+    if is a LayerOutput,
+
+    :param input: The input layer. Could be a list/tuple of input layer.
+    :type input: LayerOutput|list|tuple
+    :return: list of LayerOutput
+    :rtype: list of LayerOutput
+    """
+
+    if isinstance(input, LayerOutput):
+        return [LayerOutput]
+    assert isinstance(input, list)
+    for inp in input:
+        assert isinstance(inp, LayerOutput)
+    return list(input)
+
+
 def layer_support(*attrs):
     def decorator(method):
         @functools.wraps(method)
@@ -731,19 +749,27 @@ def fc_layer(input, size, act=None, name=None,
     return LayerOutput(name, LayerType.FC_LAYER, input, activation=act,
                        size=size)
 
+
 @wrap_name_default("print")
 def print_layer(input, name=None):
     """
     Print the output value of input layers. This layer is useful for debugging.
+
+    :param name: The Layer Name.
+    :type name: basestring
+    :param input: The input layer. Could be a list/tuple of input layer.
+    :type input: LayerOutput|list|tuple
+    :return: No return
     """
-    assert isinstance(input, list)
+    check_input(input)
 
     Layer(
         name=name,
         type=LayerType.PRINT_LAYER,
         inputs=[l.name for l in input],
     )
-    return LayerOutput(name, LayerType.PRINT_LAYER, input)
+    LayerOutput(name, LayerType.PRINT_LAYER, input)
+
 
 @wrap_name_default("seq_pooling")
 @wrap_bias_attr_default(has_bias=False)