rnn支持导出

ppocr/modeling/necks/rnn.py

@@ -28,8 +28,9 @@ class Im2Seq(nn.Layer):
 
     def forward(self, x):
         B, C, H, W = x.shape
-        x = x.reshape((B, -1, W))
-        x = x.transpose((0, 2, 1))  # (NTC)(batch, width, channels)
+        assert H == 1
+        x = x.squeeze(axis=2)
+        x = x.transpose([0, 2, 1])  # (NTC)(batch, width, channels)
         return x
 
 
@@ -76,7 +77,8 @@ class SequenceEncoder(nn.Layer):
                 'fc': EncoderWithFC,
                 'rnn': EncoderWithRNN
             }
-            assert encoder_type in support_encoder_dict, '{} must in {}'.format(encoder_type, support_encoder_dict.keys())
+            assert encoder_type in support_encoder_dict, '{} must in {}'.format(
+                encoder_type, support_encoder_dict.keys())
 
             self.encoder = support_encoder_dict[encoder_type](
                 self.encoder_reshape.out_channels, hidden_size)