More review comments.

Author: TomFinley

src/Microsoft.ML.Data/Model/ModelOperationsCatalog.cs

@@ -58,7 +58,7 @@ public void Save<TSource>(ITransformer model, IDataLoader<TSource> loader, Strea
         /// Save a transformer model and the loader used to create its input data to the file.
         /// </summary>
         /// <param name="model">The trained model to be saved. Note that this can be <see langword="null"/>, as a shorthand
-        /// for an empty data set. Upon loading with <see cref="LoadWithDataLoader(Stream, out IDataLoader{IMultiStreamSource})"/>
+        /// for an empty transformer chain. Upon loading with <see cref="LoadWithDataLoader(Stream, out IDataLoader{IMultiStreamSource})"/>
         /// the returned value will be an empty <see cref="TransformerChain{TLastTransformer}"/>.</param>
         /// <param name="loader">The loader that was used to create data to train the model.</param>
         /// <param name="filePath">Path where model should be saved.</param>
@@ -76,7 +76,7 @@ public void Save<TSource>(ITransformer model, IDataLoader<TSource> loader, strin
         /// Save a transformer model and the schema of the data that was used to train it to the stream.
         /// </summary>
         /// <param name="model">The trained model to be saved. Note that this can be <see langword="null"/>, as a shorthand
-        /// for an empty data set. Upon loading with <see cref="Load(Stream, out DataViewSchema)"/> the returned value will
+        /// for an empty transformer chain. Upon loading with <see cref="Load(Stream, out DataViewSchema)"/> the returned value will
         /// be an empty <see cref="TransformerChain{TLastTransformer}"/>.</param>
         /// <param name="inputSchema">The schema of the input to the transformer. This can be <see langword="null"/>.</param>
         /// <param name="stream">A writeable, seekable stream to save to.</param>
@@ -98,7 +98,7 @@ public void Save(ITransformer model, DataViewSchema inputSchema, Stream stream)
         /// Save a transformer model and the schema of the data that was used to train it to the file.
         /// </summary>
         /// <param name="model">The trained model to be saved. Note that this can be <see langword="null"/>, as a shorthand
-        /// for an empty data set. Upon loading with <see cref="Load(Stream, out DataViewSchema)"/> the returned value will
+        /// for an empty transformer chain. Upon loading with <see cref="Load(Stream, out DataViewSchema)"/> the returned value will
         /// be an empty <see cref="TransformerChain{TLastTransformer}"/>.</param>
         /// <param name="inputSchema">The schema of the input to the transformer. This can be <see langword="null"/>.</param>
         /// <param name="filePath">Path where model should be saved.</param>

test/Microsoft.ML.Functional.Tests/ModelLoading.cs

@@ -234,10 +234,10 @@ public void SaveCompositeLoaderAndLoad()
             var file = new MultiFileSource(GetDataPath(TestDatasets.adult.trainFilename));
             var loader = ML.Data.CreateTextLoader<InputData>(hasHeader: true, dataSample: file);
             var composite = loader.Append(ML.Transforms.Normalize("Features"));
-            var model = composite.Fit(file);
+            var loaderWithEmbeddedModel = composite.Fit(file);
 
             string modelPath = GetOutputPath(FullTestName + "-model.zip");
-            ML.Model.Save(null, model, modelPath);
+            ML.Model.Save(null, loaderWithEmbeddedModel, modelPath);
 
             Load(modelPath, out var loadedWithSchema, out var loadedSchema,
                 out var loadedWithLoader, out var loadedLoaderWithTransformer);
@@ -247,15 +247,15 @@ public void SaveCompositeLoaderAndLoad()
             Assert.Empty(Assert.IsType<TransformerChain<ITransformer>>(loadedWithSchema));
             Assert.Empty(Assert.IsType<TransformerChain<ITransformer>>(loadedWithLoader));
 
-            var expectedSchema = model.GetOutputSchema();
+            var expectedSchema = loaderWithEmbeddedModel.GetOutputSchema();
             Assert.True(expectedSchema.Count == 3);
             Assert.NotNull(expectedSchema.GetColumnOrNull("Label"));
             Assert.NotNull(expectedSchema.GetColumnOrNull("Features"));
             Assert.True(expectedSchema["Features"].HasSlotNames());
 
-            CheckSameSchemas(model.GetOutputSchema(), loadedSchema);
+            CheckSameSchemas(loaderWithEmbeddedModel.GetOutputSchema(), loadedSchema);
             var schemaFromLoadedLoader = loadedLoaderWithTransformer.GetOutputSchema();
-            CheckSameSchemas(model.GetOutputSchema(), schemaFromLoadedLoader);
+            CheckSameSchemas(loaderWithEmbeddedModel.GetOutputSchema(), schemaFromLoadedLoader);
 
             // The type of the loader itself should be a composite data loader, and its single transformer
             // should be the normalizing transformer.