support multi input models for nnframes (intel-analytics#1553)

* support multi input for nnframes * update ut * add doc and unit test * doc update * scala style
dding3 · Aug 20, 2019 · 50885fe · 50885fe
1 parent cb16521
commit 50885fe
Showing 1 changed file with 8 additions and 4 deletions.
diff --git a/python/dllib/src/bigdl/dllib/nnframes/nn_classifier.py b/python/dllib/src/bigdl/dllib/nnframes/nn_classifier.py
@@ -190,8 +190,10 @@ def __init__(self, model, criterion,
             label_preprocessing = SeqToTensor()
 
         if type(feature_preprocessing) is list:
-            assert(all(isinstance(x, int) for x in feature_preprocessing))
-            feature_preprocessing = SeqToTensor(feature_preprocessing)
+            if type(feature_preprocessing[0]) is list:
+                feature_preprocessing = SeqToMultipleTensors(feature_preprocessing)
+            elif isinstance(feature_preprocessing[0], int):
+                feature_preprocessing = SeqToTensor(feature_preprocessing)
 
         if type(label_preprocessing) is list:
             assert(all(isinstance(x, int) for x in label_preprocessing))
@@ -461,8 +463,10 @@ def __init__(self, model, feature_preprocessing=None, jvalue=None, bigdl_type="f
                 feature_preprocessing = SeqToTensor()
 
             if type(feature_preprocessing) is list:
-                assert(all(isinstance(x, int) for x in feature_preprocessing))
-                feature_preprocessing = SeqToTensor(feature_preprocessing)
+                if type(feature_preprocessing[0]) is list:
+                    feature_preprocessing = SeqToMultipleTensors(feature_preprocessing)
+                elif isinstance(feature_preprocessing[0], int):
+                    feature_preprocessing = SeqToTensor(feature_preprocessing)
 
             sample_preprocessing = ChainedPreprocessing([feature_preprocessing, TensorToSample()])
             self.value = callBigDlFunc(