remove _contrib_format_sequence.

python/mxnet/gluon/contrib/rnn/rnn_cell.py

@@ -319,28 +319,6 @@ def hybrid_forward(self, F, inputs, states, i2h_weight,
     # pylint: enable= arguments-differ
 
 
-def _contrib_format_sequence(inputs, layout, in_layout=None):
-    assert inputs is not None, \
-        "unroll(inputs=None) has been deprecated. " \
-        "Please create input variables outside unroll."
-
-    axis = layout.find('T')
-    batch_axis = layout.find('N')
-    batch_size = 0
-    in_axis = in_layout.find('T') if in_layout is not None else axis
-    assert isinstance(inputs, tensor_types)
-    if isinstance(inputs, symbol.Symbol):
-        F = symbol
-    else:
-        F = ndarray
-        batch_size = inputs.shape[batch_axis]
-
-    if axis != in_axis:
-        inputs = F.swapaxes(inputs, dim1=axis, dim2=in_axis)
-
-    return inputs, axis, F, batch_size
-
-
 def unroll(cell, inputs, begin_state, drop_inputs=0, drop_outputs=0,
            layout='TNC', valid_length=None):
     """Unrolls an RNN cell across time steps.
@@ -407,7 +385,8 @@ def unroll(cell, inputs, begin_state, drop_inputs=0, drop_outputs=0,
      <NDArray 3x2x5 @cpu(0)>
     """
 
-    inputs, axis, F, _ = _contrib_format_sequence(inputs, layout)
+    # Merge is always True, so we don't need length.
+    inputs, axis, F, _ = _format_sequence(0, inputs, layout, True)
     if axis != 0:
         axes = list(range(len(layout)))
         tmp = axes[0]