Refactoring related to namespaces and public input/output classes.

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/ApplyCustomWordEmbedding.cs

@@ -1,9 +1,9 @@
 using System;
 using System.Collections.Generic;
 using System.IO;
-using System.Text;
+using Microsoft.ML;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class ApplyCustomWordEmbedding
     {
@@ -67,12 +67,12 @@ public static void Example()
             //   Features: -1.0000 0.0000 -100.0000 0.0000 34.0000 -25.6667 1.0000 100.0000 20.0000
         }
 
-        public class TextData
+        private class TextData
         {
             public string Text { get; set; }
         }
 
-        public class TransformedTextData : TextData
+        private class TransformedTextData : TextData
         {
             public float[] Features { get; set; }
         }

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/ApplyWordEmbedding.cs

@@ -1,8 +1,9 @@
 using System;
 using System.Collections.Generic;
-using System.Text;
+using Microsoft.ML;
+using Microsoft.ML.Transforms.Text;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class ApplyWordEmbedding
     {
@@ -29,8 +30,8 @@ public static void Example()
             // The pipeline first normalizes and tokenizes text then applies word embedding transformation.
             var textPipeline = mlContext.Transforms.Text.NormalizeText("Text")
                 .Append(mlContext.Transforms.Text.TokenizeIntoWords("Tokens", "Text"))
-                .Append(mlContext.Transforms.Text.ApplyWordEmbedding("Features", "Tokens", 
-                    Transforms.Text.WordEmbeddingEstimator.PretrainedModelKind.SentimentSpecificWordEmbedding));
+                .Append(mlContext.Transforms.Text.ApplyWordEmbedding("Features", "Tokens",
+                    WordEmbeddingEstimator.PretrainedModelKind.SentimentSpecificWordEmbedding));
 
             // Fit to data.
             var textTransformer = textPipeline.Fit(emptyDataView);
@@ -55,12 +56,12 @@ public static void Example()
             //   Features: -1.2489 0.2384 -1.3034 -0.9135 -3.4978 -0.1784 -1.3823 -0.3863 -2.5262 -0.8950 ...
         }
 
-        public class TextData
+        private class TextData
         {
             public string Text { get; set; }
         }
 
-        public class TransformedTextData : TextData
+        private class TransformedTextData : TextData
         {
             public float[] Features { get; set; }
         }

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/FeaturizeText.cs

@@ -1,8 +1,8 @@
 using System;
 using System.Collections.Generic;
-using Microsoft.ML.Data;
+using Microsoft.ML;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class FeaturizeText
     {
@@ -60,12 +60,12 @@ public static void Example()
             //   Features: 0.0857  0.0857  0.0857  0.0857  0.0857  0.0857  0.0857  0.0857  0.0857  0.1715 ...
         }
 
-        public class TextData
+        private class TextData
         {
             public string Text { get; set; }
         }
 
-        public class TransformedTextData : TextData
+        private class TransformedTextData : TextData
         {
             public float[] Features { get; set; }
         }

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/FeaturizeTextWithOptions.cs

@@ -1,9 +1,9 @@
 using System;
 using System.Collections.Generic;
-using Microsoft.ML.Data;
+using Microsoft.ML;
 using Microsoft.ML.Transforms.Text;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class FeaturizeTextWithOptions
     {
@@ -67,12 +67,12 @@ public static void Example()
             //   Tokens: ml.net's,featurizetext,api,uses,composition,basic,transforms,convert,text,numeric,features.
         }
 
-        public class TextData
+        private class TextData
         {
             public string Text { get; set; }
         }
 
-        public class TransformedTextData : TextData
+        private class TransformedTextData : TextData
         {
             public float[] Features { get; set; }
             public string[] OutputTokens { get; set; }

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/LatentDirichletAllocation.cs

@@ -1,8 +1,8 @@
 using System;
 using System.Collections.Generic;
-using Microsoft.ML.Data;
+using Microsoft.ML;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class LatentDirichletAllocation
     {

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/NormalizeText.cs

@@ -1,8 +1,9 @@
 using System;
 using System.Collections.Generic;
-using System.Text;
+using Microsoft.ML;
+using Microsoft.ML.Transforms.Text;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class NormalizeText
     {
@@ -22,7 +23,7 @@ public static void Example()
 
             // A pipeline for normalizing text.
             var normTextPipeline = mlContext.Transforms.Text.NormalizeText("NormalizedText", "Text",
-                Transforms.Text.TextNormalizingEstimator.CaseMode.Lower,
+                TextNormalizingEstimator.CaseMode.Lower,
                 keepDiacritics: false,
                 keepPunctuations: false,
                 keepNumbers: false);
@@ -44,12 +45,12 @@ public static void Example()
             //   Normalized Text: mlnets normalizetext api changes the case of the text and removeskeeps diacritics punctuations andor numbers
         }
 
-        public class TextData
+        private class TextData
         {
             public string Text { get; set; }
         }
 
-        public class TransformedTextData : TextData
+        private class TransformedTextData : TextData
         {
             public string NormalizedText { get; set; }
         }

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/ProduceHashedNgrams.cs

@@ -1,9 +1,9 @@
 using System;
 using System.Collections.Generic;
+using Microsoft.ML;
 using Microsoft.ML.Data;
-using Microsoft.ML.Transforms.Text;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class ProduceHashedNgrams
     {

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/ProduceHashedWordBags.cs

@@ -1,10 +1,9 @@
 using System;
 using System.Collections.Generic;
-using System.Text;
+using Microsoft.ML;
 using Microsoft.ML.Data;
-using Microsoft.ML.Transforms.Text;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class ProduceHashedWordBags
     {

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/ProduceNgrams.cs

@@ -1,9 +1,10 @@
 using System;
 using System.Collections.Generic;
+using Microsoft.ML;
 using Microsoft.ML.Data;
 using Microsoft.ML.Transforms.Text;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class ProduceNgrams
     {

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/ProduceWordBags.cs

@@ -1,10 +1,10 @@
 using System;
 using System.Collections.Generic;
-using System.Text;
+using Microsoft.ML;
 using Microsoft.ML.Data;
 using Microsoft.ML.Transforms.Text;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class ProduceWordBags
     {

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/RemoveDefaultStopWords.cs

@@ -1,8 +1,9 @@
 using System;
 using System.Collections.Generic;
+using Microsoft.ML;
 using Microsoft.ML.Transforms.Text;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class RemoveDefaultStopWords
     {
@@ -47,12 +48,12 @@ public static void Example()
             //   Words without stop words: ML.NET's,RemoveDefaultStopWords,API,removes,stop,words,text/string.,requires,text/string,tokenized,beforehand.
         }
 
-        public class TextData
+        private class TextData
         {
             public string Text { get; set; }
         }
 
-        public class TransformedTextData : TextData
+        private class TransformedTextData : TextData
         {
             public string[] WordsWithoutStopWords { get; set; }
         }

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/RemoveStopWords.cs

@@ -1,8 +1,8 @@
 using System;
 using System.Collections.Generic;
-using Microsoft.ML.Transforms.Text;
+using Microsoft.ML;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class RemoveStopWords
     {
@@ -47,12 +47,12 @@ public static void Example()
             //   Words without stop words: ML.NET's,RemoveStopWords,API,removes,stop,words,text/string,using,list,of,stop,words,provided,user.
         }
 
-        public class TextData
+        private class TextData
         {
             public string Text { get; set; }
         }
 
-        public class TransformedTextData : TextData
+        private class TransformedTextData : TextData
         {
             public string[] WordsWithoutStopWords { get; set; }
         }

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/TokenizeIntoCharactersAsKeys.cs

@@ -1,8 +1,8 @@
 using System;
 using System.Collections.Generic;
-using System.Text;
+using Microsoft.ML;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class TokenizeIntoCharactersAsKeys
     {
@@ -50,12 +50,12 @@ public static void Example()
             // <?>: is a unicode control character used instead of spaces ('\u2400').
         }
 
-        public class TextData
+        private class TextData
         {
             public string Text { get; set; }
         }
 
-        public class TransformedTextData : TextData
+        private class TransformedTextData : TextData
         {
             public string[] CharTokens { get; set; }
         }

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Text/TokenizeIntoWords.cs

@@ -1,8 +1,8 @@
 using System;
 using System.Collections.Generic;
-using System.Text;
+using Microsoft.ML;
 
-namespace Microsoft.ML.Samples.Dynamic
+namespace Samples.Dynamic
 {
     public static class TokenizeIntoWords
     {
@@ -46,12 +46,12 @@ public static void Example()
             //   Words: ML.NET's,TokenizeIntoWords,API,splits,text/string,into,words,using,the,list,of,characters,provided,as,separators.
         }
 
-        public class TextData
+        private class TextData
         {
             public string Text { get; set; }
         }
 
-        public class TransformedTextData : TextData
+        private class TransformedTextData : TextData
         {
             public string[] Words { get; set; }
         }