def _create_cell(self, seq, no_stacked_cells):
"""
Creates GRU cell
:param seq: placeholder of the input batch
:return: cell and placeholder for its internal state
"""
batch_size = tf.shape(seq)[0]
##########################################################################################################
#
# TODO: Create a stacked MultiRNNCell from GRU cells
# First, you have to use tf.contrib.rnn.GRUCell() to construct cells
# Since around May 2017, there is new way of constructing MultiRNNCell and you need to create
# one cell for each layer. Old code snippets that used [cell * no_stacked_cells] that you can
# find online might not work with the latest Tensorflow
#
# After construction GRUCell objects, use it to construct tf.contrib.rnn.MultiRNNCell().
#
# YOUR CODE BEGIN
#
##########################################################################################################
cell = None # you
##########################################################################################################
#
# YOUR CODE END
#
##########################################################################################################
multi_cell_zero_state = cell.zero_state(batch_size, tf.float32)
in_state_shape = tuple([None, self.hidden_size] for _ in range(no_stacked_cells))
in_state = tuple(tf.placeholder_with_default(cell_zero_state, [None, self.hidden_size], name='in_state') for cell_zero_state in multi_cell_zero_state)
return cell, in_state
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