More output for multi-GPU error on Kur

more-traceback.txt

$ python parallel_bug.py 
Using TensorFlow backend.
get_output_shape_for((None, 32))
  self.name: dense_1
  self.input_dim: 32
  self.output_dim: 100
  id(self): 140287380209560
get_output_shape_for((None, 32))
  self.name: dense_1
  self.input_dim: 32
  self.output_dim: 100
  id(self): 140287380209560
get_output_shape_for((None, 50))
  self.name: dense_2
  self.input_dim: 50
  self.output_dim: 20
  id(self): 140287379155432
get_output_shape_for((None, 50))
  self.name: dense_2
  self.input_dim: 50
  self.output_dim: 20
  id(self): 140287379155432
____________________________________________________________________________________________________
Layer (type)                     Output Shape          Param #     Connected to                     
====================================================================================================
input_1 (InputLayer)             (None, 32, 32)        0                                            
____________________________________________________________________________________________________
timedistributed_1 (TimeDistribut (None, 32, 100)       3300        input_1[0][0]                    
____________________________________________________________________________________________________
lstm_1 (LSTM)                    (None, 32, 50)        30200       timedistributed_1[0][0]          
____________________________________________________________________________________________________
timedistributed_2 (TimeDistribut (None, 32, 20)        1020        lstm_1[0][0]                     
====================================================================================================
Total params: 34,520
Trainable params: 34,520
Non-trainable params: 0
____________________________________________________________________________________________________
get_output_shape_for((None, 32))
  self.name: dense_1
  self.input_dim: 32
  self.output_dim: 100
  id(self): 140287380209560
get_output_shape_for((32,))
  self.name: dense_1
  self.input_dim: 32
  self.output_dim: 100
  id(self): 140287380209560
Traceback (most recent call last):
  File "parallel_bug.py", line 31, in <module>
    model = make_parallel(model, 1)
  File "/home/ubuntu/projects/mgpu/kur/kur/utils/parallelism.py", line 66, in make_parallel
    outputs = model(inputs)
  File "/home/ubuntu/projects/mgpu/keras/keras/engine/topology.py", line 572, in __call__
    self.add_inbound_node(inbound_layers, node_indices, tensor_indices)
  File "/home/ubuntu/projects/mgpu/keras/keras/engine/topology.py", line 635, in add_inbound_node
    Node.create_node(self, inbound_layers, node_indices, tensor_indices)
  File "/home/ubuntu/projects/mgpu/keras/keras/engine/topology.py", line 166, in create_node
    output_tensors = to_list(outbound_layer.call(input_tensors[0], mask=input_masks[0]))
  File "/home/ubuntu/projects/mgpu/keras/keras/engine/topology.py", line 2247, in call
    output_tensors, output_masks, output_shapes = self.run_internal_graph(inputs, masks)
  File "/home/ubuntu/projects/mgpu/keras/keras/engine/topology.py", line 2420, in run_internal_graph
    shapes = to_list(layer.get_output_shape_for(computed_tensors[0]._keras_shape))
  File "/home/ubuntu/projects/mgpu/keras/keras/layers/wrappers.py", line 100, in get_output_shape_for
    child_output_shape = self.layer.get_output_shape_for(child_input_shape)
  File "/home/ubuntu/projects/mgpu/keras/keras/layers/core.py", line 825, in get_output_shape_for
    assert input_shape and len(input_shape) >= 2
AssertionError