microsoft · najeeb-kazmi · Dec 4, 2019
diff --git a/docs/release-notes/release-1.6.0.md b/docs/release-notes/release-1.6.0.md
@@ -0,0 +1,42 @@
+# [NimbusML](https://docs.microsoft.com/en-us/nimbusml/overview) 1.6.0
+
+## **New Features**
+
+- **Initial implementation of NGramExtractor.**
+
+    [PR#320](https://github.com/microsoft/NimbusML/pull/320)
+    Produces a bag of counts of n-grams (sequences of consecutive values of length 1-n)
+    in a given vector of keys. It does so by building a dictionary of n-grams and using
+    the id in the dictionary as the index in the bag.
+
+- **Update Manifest Generator.**
+
+    [PR#329](https://github.com/microsoft/NimbusML/pull/329)
+    Update the Manifest Generator project to work with the latest changes and incorporate
+    it in to the build process.
+
+## **Bug Fixes**
+
+None.
+
+## **Enhancements**
+
+- **Update To ML.Net Version 1.4.0.**
+
+    [PR#353](https://github.com/microsoft/NimbusML/pull/353)
+
+- **Update To Latest Version Of DataPrep.**
+
+    [PR#379](https://github.com/microsoft/NimbusML/pull/379)
+
+- **Update Tests To Execute In Parallel.**
+
+    [PR#331](https://github.com/microsoft/NimbusML/pull/331)
+
+## **Documentation and Samples**
+
+None. 
+
+## **Remarks**
+
+None.
diff --git a/release-next.md b/release-next.md
@@ -2,28 +2,15 @@
 
 ## **New Features**
 
-- **Initial implementation of NGramExtractor.**
-
-    [PR#320](https://github.com/microsoft/NimbusML/pull/320)
-    Produces a bag of counts of n-grams (sequences of consecutive values of length 1-n)
-    in a given vector of keys. It does so by building a dictionary of n-grams and using
-    the id in the dictionary as the index in the bag.
-
-- **Update Manifest Generator.**
-
-    [PR#329](https://github.com/microsoft/NimbusML/pull/329)
-    Update the Manifest Generator project to work with the latest changes and incorporate
-    it in to the build process.
+None.
 
 ## **Bug Fixes**
 
 None.
 
 ## **Enhancements**
 
-- **Update Tests To Execute In Parallel.**
-
-    [PR#331](https://github.com/microsoft/NimbusML/pull/331)
+None.
 
 ## **Documentation and Samples**
 

diff --git a/src/DotNetBridge/DotNetBridge.csproj b/src/DotNetBridge/DotNetBridge.csproj
@@ -43,7 +43,7 @@
     <PackageReference Include="Microsoft.ML.Vision" Version="1.4.0" />
     <PackageReference Include="Microsoft.ML.Ensemble" Version="0.16.0" />
     <PackageReference Include="Microsoft.ML.TimeSeries" Version="1.4.0" />
-    <PackageReference Include="Microsoft.DataPrep" Version="0.0.2.3-preview" />
+    <PackageReference Include="Microsoft.DataPrep" Version="0.0.3.1-preview" />
     <PackageReference Include="TensorFlow.NET" Version="0.11.8.1" />
     <PackageReference Include="SciSharp.TensorFlow.Redist" Version="1.14.0" />
   </ItemGroup>

diff --git a/src/Platforms/build.csproj b/src/Platforms/build.csproj
@@ -22,7 +22,7 @@
     <PackageReference Include="Microsoft.ML.Vision" Version="1.4.0" />
     <PackageReference Include="Microsoft.ML.Ensemble" Version="0.16.0" />
     <PackageReference Include="Microsoft.ML.TimeSeries" Version="1.4.0" />
-    <PackageReference Include="Microsoft.DataPrep" Version="0.0.2.3-preview" />
+    <PackageReference Include="Microsoft.DataPrep" Version="0.0.3.1-preview" />
     <PackageReference Include="TensorFlow.NET" Version="0.11.8.1" />
     <PackageReference Include="SciSharp.TensorFlow.Redist" Version="1.14.0" />
   </ItemGroup>

diff --git a/src/python/docs/docstrings/DssmFeaturizer.txt b/src/python/docs/docstrings/DssmFeaturizer.txt
diff --git a/src/python/docs/docstrings/SsweEmbedding.txt b/src/python/docs/docstrings/SsweEmbedding.txt
@@ -63,7 +63,6 @@
 
     .. seealso::
         :py:class:`NGramFeaturizer <nimbusml.feature_extraction.text.NGramFeaturizer>`,
-        :py:class:`DssmFeaturizer <nimbusml.feature_extraction.text.DssmFeaturizer>`,
         :py:class:`Sentiment <nimbusml.feature_extraction.text.Sentiment>`,
         :py:class:`WordEmbedding <nimbusml.feature_extraction.text.WordEmbedding>`.
 

diff --git a/src/python/docs/sphinx/modules/feature_extraction/text/dssmfeaturizer.rst b/src/python/docs/sphinx/modules/feature_extraction/text/dssmfeaturizer.rst
diff --git a/src/python/nimbusml.pyproj b/src/python/nimbusml.pyproj
@@ -959,7 +959,6 @@
     <Content Include="docs\docstrings\CustomStopWordsRemover.txt" />
     <Content Include="docs\docstrings\Dart.txt" />
     <Content Include="docs\docstrings\DnnFeaturizer.txt" />
-    <Content Include="docs\docstrings\DssmFeaturizer.txt" />
     <Content Include="docs\docstrings\EnsembleClassifier.txt" />
     <Content Include="docs\docstrings\EnsembleRegressor.txt" />
     <Content Include="docs\docstrings\ExponentialAverage.txt" />

diff --git a/src/python/nimbusml/_pipeline.py b/src/python/nimbusml/_pipeline.py
@@ -2543,7 +2543,7 @@ def summary(self, verbose=0, **params):
         if len(self.steps) > 0 and not isinstance(
                 self.last_node, BasePredictor):
             raise ValueError(
-                "Summary is availabe only for predictor types, instead "
+                "Summary is available only for predictor types, instead "
                 "got " +
                 self.last_node.type)
 
@@ -2581,6 +2581,10 @@ def summary(self, verbose=0, **params):
             self._run_time = time.time() - start_time
             raise e
 
+        # .summary() not supported if size of summary_data
+        # is less or equal to 1 (if only PredictedName in summary_data)
+        if summary_data.size == 1 and summary_data.columns.values == ["PredictorName"]:
+            raise TypeError("One or more predictors in this pipeline do not support the .summary() function.")
         self.model_summary = summary_data
 
         # stop the clock

diff --git a/src/python/nimbusml/tests/model_summary/test_model_summary.py b/src/python/nimbusml/tests/model_summary/test_model_summary.py
@@ -66,25 +66,25 @@
     #SymSgdBinaryClassifier(),
     OrdinaryLeastSquaresRegressor(),
     PoissonRegressionRegressor(),
-    OneVsRestClassifier(FastLinearBinaryClassifier()),
     GamRegressor(),
     GamBinaryClassifier(),
     PcaAnomalyDetector(),
-    FactorizationMachineBinaryClassifier(),
-    KMeansPlusPlus(n_clusters=2),
-    NaiveBayesClassifier(),
     FastForestBinaryClassifier(number_of_trees=2), 
     FastForestRegressor(number_of_trees=2),
     FastTreesBinaryClassifier(number_of_trees=2),
     FastTreesRegressor(number_of_trees=2),
     FastTreesTweedieRegressor(number_of_trees=2),
     LightGbmRegressor(number_of_iterations=2),
-    LightGbmClassifier(),
     LightGbmBinaryClassifier(number_of_iterations=2)
 ]
 
 learners_not_supported = [
-    #PcaTransformer(), # REVIEW: crashes
+    FactorizationMachineBinaryClassifier(),
+    OneVsRestClassifier(FastLinearBinaryClassifier()),
+    FactorizationMachineBinaryClassifier(),
+    KMeansPlusPlus(n_clusters=2),
+    NaiveBayesClassifier(),
+    LightGbmClassifier()
 ]
 
 
@@ -98,7 +98,6 @@ def test_model_summary(self):
             pipeline.fit(train_stream, label_column)
             pipeline.summary()
 
-    @unittest.skip("No unsupported learners")
     def test_model_summary_not_supported(self):
         for learner in learners_not_supported:
             pipeline = Pipeline(
@@ -107,6 +106,23 @@ def test_model_summary_not_supported(self):
             pipeline.fit(train_stream, label_column)
             assert_raises(TypeError, pipeline.summary)
 
+    def test_model_summary_not_supported_specific(self):
+        path = get_dataset('infert').as_filepath()
+        data = FileDataStream.read_csv(path, sep=',',
+                               names={0: 'row_num', 5: 'case'})
+        pipeline = Pipeline([
+            OneHotVectorizer(columns={'edu': 'education'}),
+            FactorizationMachineBinaryClassifier(feature=['induced', 'edu', 'parity'],
+                                         label='case')
+        ])
+        pipeline.fit(data)
+        try:
+            pipeline.summary()
+        except TypeError as e:
+            self.assertEqual(e.args[0], "One or more predictors in this pipeline do not support the .summary() function.")
+        else:
+            assert False
+
     def test_summary_called_back_to_back_on_predictor(self):
         """
         When a predictor is fit without using a Pipeline,

diff --git a/src/python/tests/test_estimator_checks.py b/src/python/tests/test_estimator_checks.py
@@ -161,7 +161,7 @@
 }
 
 OMITTED_CHECKS_TUPLE = (
-    'OneHotHashVectorizer, FromKey, DssmFeaturizer, DnnFeaturizer, '
+    'OneHotHashVectorizer, FromKey, DnnFeaturizer, '
     'PixelExtractor, Loader, Resizer, \
                         GlobalContrastRowScaler, PcaTransformer, '
     'ColumnConcatenator, Sentiment, CharTokenizer, LightLda, '

diff --git a/src/python/tools/manifest_diff.json b/src/python/tools/manifest_diff.json
@@ -176,7 +176,6 @@
     "Common.MakeArrayIDataView",
     "Common.MakeArrayIPredictorModel",
     "CountTable.Create",
-    "Dssm.Trigram",
     "EnsembleCreator.CreateAnomalyPipelineEnsemble",
     "EnsembleCreator.CreateBinaryEnsemble",
     "EnsembleCreator.CreateBinaryPipelineEnsemble",