Fix saving inference model in PACT quanter (#728)

paddleslim/dygraph/quant/quanter.py

@@ -213,7 +213,12 @@ class QAT(object):
 
     def save_quantized_model(self, model, path, input_spec=None):
         if self.weight_preprocess is not None or self.act_preprocess is not None:
+            training = model.training
             model = self._remove_preprocess(model)
+            if training:
+                model.train()
+            else:
+                model.eval()
 
         self.imperative_qat.save_quantized_model(
             layer=model, path=path, input_spec=input_spec)

tests/dygraph/test_dygraph_quant_aware.py

@@ -256,6 +256,16 @@ class TestImperativeQatPACT(unittest.TestCase):
         _logger.info("After quantization: top1: {}, top5: {}".format(top1_1,
                                                                      top5_1))
 
+        # test for saving model in train mode
+        lenet.train()
+        quanter.save_quantized_model(
+            lenet,
+            './dygraph_qat',
+            input_spec=[
+                paddle.static.InputSpec(
+                    shape=[None, 1, 28, 28], dtype='float32')
+            ])
+
 
 if __name__ == '__main__':
     unittest.main()