Fix the bug of BidirectionalCell

CONTRIBUTORS.md

@@ -192,6 +192,7 @@ List of Contributors
 * [Rahul Padmanabhan](https://github.com/rahul3)
 * [Yuxi Hu](https://github.com/yuxihu)
 * [Harsh Patel](https://github.com/harshp8l)
+* [Xiao Wang](https://github.com/BeyonderXX)
 
 Label Bot
 ---------

python/mxnet/gluon/rnn/rnn_cell.py

@@ -1041,8 +1041,8 @@ def unroll(self, length, inputs, begin_state=None, layout='NTC', merge_outputs=N
             reversed_inputs = F.SequenceReverse(F.stack(*inputs, axis=0),
                                                 sequence_length=valid_length,
                                                 use_sequence_length=True)
-            reversed_inputs = _as_list(F.split(reversed_inputs, axis=0, num_outputs=length,
-                                               squeeze_axis=True))
+            reversed_inputs = list(F.split(reversed_inputs, axis=0, num_outputs=length,
+                                           squeeze_axis=True))
         begin_state = _get_begin_state(self, F, begin_state, inputs, batch_size)
 
         states = begin_state
@@ -1063,8 +1063,8 @@ def unroll(self, length, inputs, begin_state=None, layout='NTC', merge_outputs=N
                                                    sequence_length=valid_length,
                                                    use_sequence_length=True,
                                                    axis=0)
-            reversed_r_outputs = _as_list(F.split(reversed_r_outputs, axis=0, num_outputs=length,
-                                                  squeeze_axis=True))
+            reversed_r_outputs = list(F.split(reversed_r_outputs, axis=0, num_outputs=length,
+                                              squeeze_axis=True))
         if merge_outputs is None:
             merge_outputs = isinstance(l_outputs, tensor_types)
             l_outputs, _, _, _ = _format_sequence(None, l_outputs, layout, merge_outputs)

tests/python/unittest/test_gluon_rnn.py

@@ -243,6 +243,34 @@ def test_bidirectional():
     assert outs == [(10, 200), (10, 200), (10, 200)]
 
 
+def test_bidirectional_unroll_valid_length():
+    # Test BidirectionalCell.
+    # In 1.3.1 version, after hybridize( ), BidirectionalCell would failed when pass valid_length to unroll( ).
+    class BiLSTM(gluon.nn.HybridBlock):
+        def __init__(self, rnn_size, time_step, **kwargs):
+            super(BiLSTM, self).__init__(**kwargs)
+            self.time_step = time_step
+            with self.name_scope():
+                self.bi_lstm = gluon.rnn.BidirectionalCell(
+                    gluon.rnn.LSTMCell(rnn_size, prefix='rnn_l0_'),
+                    gluon.rnn.LSTMCell(rnn_size, prefix='rnn_r0_'),
+                    output_prefix='lstm_bi_')
+
+        def hybrid_forward(self, F, inputs, valid_len):
+            outputs, states = self.bi_lstm.unroll(self.time_step, inputs, valid_length=valid_len,
+                                                  layout='TNC', merge_outputs='True')
+            return outputs, states
+
+    rnn_size, time_step = 100, 3
+    net = BiLSTM(rnn_size, time_step)
+    net.initialize()
+    net.hybridize()
+    inputs_data = mx.nd.random.uniform(shape=(3, 10, 50))
+    valid_len = mx.nd.array(range(1, 11))
+    outputs, _ = net(inputs_data, valid_len)
+    assert outputs.shape == (3, 10, 200)
+
+
 @assert_raises_cudnn_not_satisfied(min_version='5.1.10')
 def test_layer_bidirectional():
     class RefBiLSTM(gluon.Block):