Keras 1.1.0 - Error with TimeDistributed wrapper

Stacktrace

ValueError                                Traceback (most recent call last)
/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/tensorflow/python/framework/tensor_shape.py in merge_with(self, other)
    562       try:
--> 563         self.assert_same_rank(other)
    564         new_dims = []

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/tensorflow/python/framework/tensor_shape.py in assert_same_rank(self, other)
    608         raise ValueError(
--> 609             "Shapes %s and %s must have the same rank" % (self, other))
    610 

ValueError: Shapes (?, 1, 15, 63, 32) and (1, 1, 32) must have the same rank

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-5-94aae201f795> in <module>()
----> 1 model.add(TimeDistributed(Convolution2D(32,2,2), batch_input_shape=(1, 1, 16, 64, 3)))

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/keras/models.py in add(self, layer)
    274                 else:
    275                     input_dtype = None
--> 276                 layer.create_input_layer(batch_input_shape, input_dtype)
    277 
    278             if len(layer.inbound_nodes) != 1:

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/keras/engine/topology.py in create_input_layer(self, batch_input_shape, input_dtype, name)
    368         # and create the node connecting the current layer
    369         # to the input layer we just created.
--> 370         self(x)
    371 
    372     def assert_input_compatibility(self, input):

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/keras/engine/topology.py 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 

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/keras/engine/topology.py 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):

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/keras/engine/topology.py in create_node(cls, outbound_layer, inbound_layers, node_indices, tensor_indices)
    147 
    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

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/keras/layers/wrappers.py in call(self, X, mask)
    115 
    116             last_output, outputs, states = K.rnn(step, X,
--> 117                                                  initial_states=[])
    118             y = outputs
    119         else:

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py in rnn(step_function, inputs, initial_states, go_backwards, mask, constants, unroll, input_length)
   1252             parallel_iterations=32,
   1253             swap_memory=True,
-> 1254             sequence_length=None)
   1255 
   1256         if nb_states > 1:

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/tensorflow/python/ops/rnn.py in _dynamic_rnn_loop(cell, inputs, initial_state, parallel_iterations, swap_memory, sequence_length, dtype)
   1023     shape = _state_size_with_prefix(
   1024         output_size, prefix=[const_time_steps, const_batch_size])
-> 1025     output.set_shape(shape)
   1026 
   1027   final_outputs = nest.pack_sequence_as(

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/tensorflow/python/framework/ops.py in set_shape(self, shape)
    406         this tensor.
    407     """
--> 408     self._shape = self._shape.merge_with(shape)
    409 
    410   @property

/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/tensorflow/python/framework/tensor_shape.py in merge_with(self, other)
    568       except ValueError:
    569         raise ValueError("Shapes %s and %s are not compatible" %
--> 570                          (self, other))
    571 
    572   def concatenate(self, other):

ValueError: Shapes (?, 1, 15, 63, 32) and (1, 1, 32) are not compatible