Dense layer: 'module' object has no attribute 'unpack' on TensorFlow 1.0.0rc0

[luthfianto]

<ipython-input-3-4256fdfb69f0> in create_model(gate)
    134     net = Convolution1D(num_label, 1, init=init)(net)
    135     #net = Dropout(0.5)(net)
--> 136     net = Dense(num_label, activation='softmax', init=init)(net)
    137     model = Model(input=input_, output=net)
    138     return model

/usr/local/lib/python2.7/dist-packages/keras/engine/topology.pyc in __call__(self, x, mask)
    567         if inbound_layers:
    568             # This will call layer.build() if necessary.
--> 569             self.add_inbound_node(inbound_layers, node_indices, tensor_indices)
    570             # Outputs were already computed when calling self.add_inbound_node.
    571             outputs = self.inbound_nodes[-1].output_tensors

/usr/local/lib/python2.7/dist-packages/keras/engine/topology.pyc in add_inbound_node(self, inbound_layers, node_indices, tensor_indices)
    630         # creating the node automatically updates self.inbound_nodes
    631         # as well as outbound_nodes on inbound layers.
--> 632         Node.create_node(self, inbound_layers, node_indices, tensor_indices)
    633 
    634     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)
    162 
    163         if len(input_tensors) == 1:
--> 164             output_tensors = to_list(outbound_layer.call(input_tensors[0], mask=input_masks[0]))
    165             output_masks = to_list(outbound_layer.compute_mask(input_tensors[0], input_masks[0]))
    166             # TODO: try to auto-infer shape

/usr/local/lib/python2.7/dist-packages/keras/layers/core.pyc in call(self, x, mask)
    766 
    767     def call(self, x, mask=None):
--> 768         output = K.dot(x, self.W)
    769         if self.bias:
    770             output += self.b

/usr/local/lib/python2.7/dist-packages/keras/backend/tensorflow_backend.pyc in dot(x, y)
    783     if ndim(x) is not None and (ndim(x) > 2 or ndim(y) > 2):
    784         x_shape = []
--> 785         for i, s in zip(int_shape(x), tf.unpack(tf.shape(x))):
    786             if i is not None:
    787                 x_shape.append(i)

AttributeError: 'module' object has no attribute 'unpack'

Code to easily reproduce the issue:

import tensorflow as tf
x=tf.Variable(4.0)
tf.unpack(tf.shape(x))

It seems that it is because tf.unpack has been renamed to tf.unstack

---

Checklist:

• Keras master
• TensorFlow 1.0.0rc0