我想在LSTM之前使用掩码，但是Lstm的输出必须重塑为4 dim。 所以我的代码：
main_input = Input(shape=(96,1000), name='main_input')
pre_input = BatchNormalization()(main_input)
aaa= Masking(mask_value=0)(pre_input)
recurrent1 = LSTM(256,return_sequences=True)(aaa)
r_out= Reshape((1,96,256))(recurrent1)`
但它运行时出错： [！[在此处输入图像说明] [1]] [1]
---------------------------------------------------------------------------
Exception Traceback (most recent call last)
<ipython-input-2-d1107015501b> in <module>()
17 recurrent1 = LSTM(256,return_sequences=True)(aaa)
18
---> 19 r_out= Reshape((1,96,256))(recurrent1)
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.pyc in __call__(self, x, mask)
512 if inbound_layers:
513 # this will call layer.build() if necessary
--> 514 self.add_inbound_node(inbound_layers, node_indices, tensor_indices)
515 input_added = True
516
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.pyc in add_inbound_node(self, inbound_layers, node_indices, tensor_indices)
570 # creating the node automatically updates self.inbound_nodes
571 # as well as outbound_nodes on inbound layers.
--> 572 Node.create_node(self, inbound_layers, node_indices, tensor_indices)
573
574 def get_output_shape_for(self, input_shape):
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.pyc in create_node(cls, outbound_layer, inbound_layers, node_indices, tensor_indices)
148 if len(input_tensors) == 1:
149 output_tensors = to_list(outbound_layer.call(input_tensors[0], mask=input_masks[0]))
--> 150 output_masks = to_list(outbound_layer.compute_mask(input_tensors[0], input_masks[0]))
151 # TODO: try to auto-infer shape if exception is raised by get_output_shape_for
152 output_shapes = to_list(outbound_layer.get_output_shape_for(input_shapes[0]))
/usr/local/lib/python2.7/dist-packages/keras/engine/topology.pyc in compute_mask(self, input, input_mask)
605 else:
606 raise Exception('Layer ' + self.name + ' does not support masking, ' +
--> 607 'but was passed an input_mask: ' + str(input_mask))
608 # masking not explicitly supported: return None as mask
609 return None
Exception: Layer reshape_1 does not support masking, but was passed an input_mask: Any{2}.0
我打印出来，recurrent1的外形是（96,256）
我怎么能做对吗？