Merge branch 'master' into Conv_1D

src/TensorFlowNET.Core/Binding.Util.cs

@@ -21,6 +21,7 @@ using System.Collections;
 using System.Collections.Generic;
 using System.ComponentModel;
 using System.Diagnostics;
+using System.IO;
 using System.Linq;
 
 namespace Tensorflow
@@ -112,16 +113,33 @@ namespace Tensorflow
             }
         }
 
+        private static TextWriter writer = null;
+
+        public static TextWriter tf_output_redirect { 
+            set
+            {
+                var originWriter = writer ?? Console.Out;
+                originWriter.Flush();
+                if (originWriter is StringWriter)
+                    (originWriter as StringWriter).GetStringBuilder().Clear();
+                writer = value;
+            }
+            get
+            {
+                return writer ?? Console.Out;
+            }
+        }
+
         public static void print(object obj)
         {
-            Console.WriteLine(_tostring(obj));
+            tf_output_redirect.WriteLine(_tostring(obj));
         }
 
         public static void print(string format, params object[] objects)
         {
             if (!format.Contains("{}"))
             {
-                Console.WriteLine(format + " " + string.Join(" ", objects.Select(x => x.ToString())));
+                tf_output_redirect.WriteLine(format + " " + string.Join(" ", objects.Select(x => x.ToString())));
                 return;
             }
 
@@ -130,7 +148,7 @@ namespace Tensorflow
 
             }
 
-            Console.WriteLine(format);
+            tf_output_redirect.WriteLine(format);
         }
 
         public static int len(object a)

src/TensorFlowNET.Core/Data/MnistDataSet.cs

@@ -24,7 +24,7 @@ namespace Tensorflow
             sw.Start();
             images = np.multiply(images, 1.0f / 255.0f);
             sw.Stop();
-            Console.WriteLine($"{sw.ElapsedMilliseconds}ms");
+            Binding.tf_output_redirect.WriteLine($"{sw.ElapsedMilliseconds}ms");
             Data = images;
 
             labels = labels.astype(dataType);

src/TensorFlowNET.Core/Data/Utils.cs

@@ -27,14 +27,14 @@ namespace Tensorflow
 
             if (showProgressInConsole)
             {
-                Console.WriteLine($"Downloading {fileName}");
+                Binding.tf_output_redirect.WriteLine($"Downloading {fileName}");
             }
 
             if (File.Exists(fileSaveTo))
             {
                 if (showProgressInConsole)
                 {
-                    Console.WriteLine($"The file {fileName} already exists");
+                    Binding.tf_output_redirect.WriteLine($"The file {fileName} already exists");
                 }
 
                 return;
@@ -64,12 +64,12 @@ namespace Tensorflow
             var destFilePath = Path.Combine(saveTo, destFileName);
 
             if (showProgressInConsole)
-                Console.WriteLine($"Unzippinng {Path.GetFileName(zipFile)}");
+                Binding.tf_output_redirect.WriteLine($"Unzippinng {Path.GetFileName(zipFile)}");
 
             if (File.Exists(destFilePath))
             {
                 if (showProgressInConsole)
-                    Console.WriteLine($"The file {destFileName} already exists");
+                    Binding.tf_output_redirect.WriteLine($"The file {destFileName} already exists");
             }
 
             using (GZipStream unzipStream = new GZipStream(File.OpenRead(zipFile), CompressionMode.Decompress))
@@ -107,7 +107,7 @@ namespace Tensorflow
             }
 
             await showProgressTask;
-            Console.WriteLine("Done.");
+            Binding.tf_output_redirect.WriteLine("Done.");
         }
 
         private static async Task ShowProgressInConsole(CancellationTokenSource cts)
@@ -119,17 +119,17 @@ namespace Tensorflow
             while (!cts.IsCancellationRequested)
             {
                 await Task.Delay(100);
-                Console.Write(".");
+                Binding.tf_output_redirect.Write(".");
                 cols++;
 
                 if (cols % 50 == 0)
                 {
-                    Console.WriteLine();
+                    Binding.tf_output_redirect.WriteLine();
                 }
             }
 
             if (cols > 0)
-                Console.WriteLine();
+                Binding.tf_output_redirect.WriteLine();
         }
     }
 }

src/TensorFlowNET.Core/Framework/c_api_util.cs

@@ -62,18 +62,18 @@ namespace Tensorflow
                 if (!File.Exists(file))
                 {
                     var wc = new WebClient();
-                    Console.WriteLine($"Downloading Tensorflow library from {url}...");
+                    Binding.tf_output_redirect.WriteLine($"Downloading Tensorflow library from {url}...");
                     var download = Task.Run(() => wc.DownloadFile(url, file));
                     while (!download.IsCompleted)
                     {
                         Thread.Sleep(1000);
-                        Console.Write(".");
+                        Binding.tf_output_redirect.Write(".");
                     }
-                    Console.WriteLine("");
-                    Console.WriteLine($"Downloaded successfully.");
+                    Binding.tf_output_redirect.WriteLine("");
+                    Binding.tf_output_redirect.WriteLine($"Downloaded successfully.");
                 }
 
-                Console.WriteLine($"Extracting...");
+                Binding.tf_output_redirect.WriteLine($"Extracting...");
                 var task = Task.Run(() =>
                 {
                     switch (Environment.OSVersion.Platform)
@@ -97,11 +97,11 @@ namespace Tensorflow
                 while (!task.IsCompleted)
                 {
                     Thread.Sleep(100);
-                    Console.Write(".");
+                    Binding.tf_output_redirect.Write(".");
                 }
 
-                Console.WriteLine("");
-                Console.WriteLine("Extraction is completed.");
+                Binding.tf_output_redirect.WriteLine("");
+                Binding.tf_output_redirect.WriteLine("Extraction is completed.");
             }
 
             isDllDownloaded = true;

src/TensorFlowNET.Core/Framework/meta_graph.cs

@@ -134,7 +134,7 @@ namespace Tensorflow
                                         }
                                         break;
                                     default:
-                                        Console.WriteLine($"import_scoped_meta_graph_with_return_elements {col.Key}");
+                                        Binding.tf_output_redirect.WriteLine($"import_scoped_meta_graph_with_return_elements {col.Key}");
                                         continue;
                                 }
                             }
@@ -142,7 +142,7 @@ namespace Tensorflow
 
                         break;
                     default:
-                        Console.WriteLine($"Cannot identify data type for collection {col.Key}. Skipping.");
+                        Binding.tf_output_redirect.WriteLine($"Cannot identify data type for collection {col.Key}. Skipping.");
                         break;
                 }
             }

src/TensorFlowNET.Core/Operations/Distributions/distribution.py.cs

@@ -166,7 +166,7 @@ namespace Tensorflow
 
         public void repr()
         {
-            Console.WriteLine($"<Reparameteriation Type: {this._rep_type}>");
+            Binding.tf_output_redirect.WriteLine($"<Reparameteriation Type: {this._rep_type}>");
         }
 
         public bool eq(ReparameterizationType other)

src/TensorFlowNET.Core/Training/Saving/Saver.cs

@@ -242,7 +242,7 @@ namespace Tensorflow
             if (!checkpoint_management.checkpoint_exists(save_path))
                 throw new ValueError($"The passed save_path is not a valid checkpoint: {save_path}");
 
-            Console.WriteLine($"Restoring parameters from {save_path}");
+            Binding.tf_output_redirect.WriteLine($"Restoring parameters from {save_path}");
 
             if (tf.Context.executing_eagerly())
 #pragma warning disable CS0642 // Possible mistaken empty statement

src/TensorFlowNET.Core/Training/Saving/saver.py.cs

@@ -78,7 +78,7 @@ namespace Tensorflow
                 else
                 {
                     // If no graph variables exist, then a Saver cannot be constructed.
-                    Console.WriteLine("Saver not created because there are no variables in the" +
+                    Binding.tf_output_redirect.WriteLine("Saver not created because there are no variables in the" +
                         " graph to restore");
                     return null;
                 }
@@ -102,7 +102,7 @@ namespace Tensorflow
                 var output_graph_def = tf.graph_util.convert_variables_to_constants(sess,
                     graph.as_graph_def(),
                     output_node_names);
-                Console.WriteLine($"Froze {output_graph_def.Node.Count} nodes.");
+                Binding.tf_output_redirect.WriteLine($"Froze {output_graph_def.Node.Count} nodes.");
                 File.WriteAllBytes(output_pb, output_graph_def.ToByteArray());
                 return output_pb;
             }

src/TensorFlowNET.Core/Util/CmdHelper.cs

@@ -31,7 +31,7 @@ namespace Tensorflow.Util
             proc.Start();
 
             while (!proc.StandardOutput.EndOfStream)
-                Console.WriteLine(proc.StandardOutput.ReadLine());
+                Binding.tf_output_redirect.WriteLine(proc.StandardOutput.ReadLine());
         }
 
         public static void Bash(string command)
@@ -44,7 +44,7 @@ namespace Tensorflow.Util
             proc.Start();
 
             while (!proc.StandardOutput.EndOfStream)
-                Console.WriteLine(proc.StandardOutput.ReadLine());
+                Binding.tf_output_redirect.WriteLine(proc.StandardOutput.ReadLine());
         }
     }
 }

src/TensorFlowNET.Keras/Datasets/MNIST.cs

@@ -61,7 +61,7 @@ namespace Tensorflow.Keras.Datasets
 
             if (File.Exists(fileSaveTo))
             {
-                Console.WriteLine($"The file {fileSaveTo} already exists");
+                Binding.tf_output_redirect.WriteLine($"The file {fileSaveTo} already exists");
                 return fileSaveTo;
             }
 

src/TensorFlowNET.Keras/Engine/Model.Evaluate.cs

@@ -46,7 +46,7 @@ namespace Tensorflow.Keras.Engine
                 StepsPerExecution = _steps_per_execution
             });
 
-            Console.WriteLine($"Testing...");
+            Binding.tf_output_redirect.WriteLine($"Testing...");
             foreach (var (epoch, iterator) in data_handler.enumerate_epochs())
             {
                 // reset_metrics();
@@ -58,7 +58,7 @@ namespace Tensorflow.Keras.Engine
                     // callbacks.on_train_batch_begin(step)
                     results = test_function(iterator);
                 }
-                Console.WriteLine($"iterator: {epoch + 1}, " + string.Join(", ", results.Select(x => $"{x.Item1}: {(float)x.Item2}")));
+                Binding.tf_output_redirect.WriteLine($"iterator: {epoch + 1}, " + string.Join(", ", results.Select(x => $"{x.Item1}: {(float)x.Item2}")));
             }
         }
 

src/TensorFlowNET.Keras/Engine/Model.Fit.cs

@@ -99,7 +99,7 @@ namespace Tensorflow.Keras.Engine
                     if (verbose == 1)
                     {
                         var result_pairs = string.Join(", ", results.Select(x => $"{x.Item1}: {(float)x.Item2:F6}"));
-                        Console.WriteLine($"Epoch: {epoch + 1:D3}/{epochs:D3}, Step: {step + 1:D4}/{data_handler.Inferredsteps:D4}, {result_pairs}");
+                        Binding.tf_output_redirect.WriteLine($"Epoch: {epoch + 1:D3}/{epochs:D3}, Step: {step + 1:D4}/{data_handler.Inferredsteps:D4}, {result_pairs}");
                     }
                 }
 

src/TensorFlowNET.Keras/Preprocessings/DatasetUtils.get_training_or_validation_split.cs

@@ -24,13 +24,13 @@ namespace Tensorflow.Keras.Preprocessings
             var num_val_samples = Convert.ToInt32(samples.Length * validation_split);
             if (subset == "training")
             {
-                Console.WriteLine($"Using {samples.Length - num_val_samples} files for training.");
+                Binding.tf_output_redirect.WriteLine($"Using {samples.Length - num_val_samples} files for training.");
                 samples = samples.Take(samples.Length - num_val_samples).ToArray();
                 labels = labels.Take(labels.Length - num_val_samples).ToArray();
             }
             else if (subset == "validation")
             {
-                Console.WriteLine($"Using {num_val_samples} files for validation.");
+                Binding.tf_output_redirect.WriteLine($"Using {num_val_samples} files for validation.");
                 samples = samples.Skip(samples.Length - num_val_samples).ToArray();
                 labels = labels.Skip(labels.Length - num_val_samples).ToArray();
             }

src/TensorFlowNET.Keras/Preprocessings/DatasetUtils.index_directory.cs

@@ -61,7 +61,7 @@ namespace Tensorflow.Keras.Preprocessings
                 }
             }
 
-            Console.WriteLine($"Found {return_file_paths.Length} files belonging to {class_names.Length} classes.");
+            Binding.tf_output_redirect.WriteLine($"Found {return_file_paths.Length} files belonging to {class_names.Length} classes.");
             return (return_file_paths, return_labels, class_names);
         }
     }

src/TensorFlowNET.Keras/Utils/Compress.cs

@@ -53,7 +53,7 @@ namespace Tensorflow.Keras.Utils
             var flag = gzArchiveName.Split(Path.DirectorySeparatorChar).Last().Split('.').First() + ".bin";
             if (File.Exists(Path.Combine(destFolder, flag))) return;
 
-            Console.WriteLine($"Extracting.");
+            Binding.tf_output_redirect.WriteLine($"Extracting.");
             var task = Task.Run(() =>
             {
                 ZipFile.ExtractToDirectory(gzArchiveName, destFolder);
@@ -62,12 +62,12 @@ namespace Tensorflow.Keras.Utils
             while (!task.IsCompleted)
             {
                 Thread.Sleep(200);
-                Console.Write(".");
+                Binding.tf_output_redirect.Write(".");
             }
 
             File.Create(Path.Combine(destFolder, flag));
-            Console.WriteLine("");
-            Console.WriteLine("Extracting is completed.");
+            Binding.tf_output_redirect.WriteLine("");
+            Binding.tf_output_redirect.WriteLine("Extracting is completed.");
         }
 
         public static void ExtractTGZ(String gzArchiveName, String destFolder)
@@ -75,7 +75,7 @@ namespace Tensorflow.Keras.Utils
             var flag = gzArchiveName.Split(Path.DirectorySeparatorChar).Last().Split('.').First() + ".bin";
             if (File.Exists(Path.Combine(destFolder, flag))) return;
 
-            Console.WriteLine($"Extracting.");
+            Binding.tf_output_redirect.WriteLine($"Extracting.");
             var task = Task.Run(() =>
             {
                 using (var inStream = File.OpenRead(gzArchiveName))
@@ -91,12 +91,12 @@ namespace Tensorflow.Keras.Utils
             while (!task.IsCompleted)
             {
                 Thread.Sleep(200);
-                Console.Write(".");
+                Binding.tf_output_redirect.Write(".");
             }
 
             File.Create(Path.Combine(destFolder, flag));
-            Console.WriteLine("");
-            Console.WriteLine("Extracting is completed.");
+            Binding.tf_output_redirect.WriteLine("");
+            Binding.tf_output_redirect.WriteLine("Extracting is completed.");
         }
     }
 }

src/TensorFlowNET.Keras/Utils/Web.cs

@@ -36,20 +36,20 @@ namespace Tensorflow.Keras.Utils
 
             if (File.Exists(relativeFilePath))
             {
-                Console.WriteLine($"{relativeFilePath} already exists.");
+                Binding.tf_output_redirect.WriteLine($"{relativeFilePath} already exists.");
                 return false;
             }
 
             var wc = new WebClient();
-            Console.WriteLine($"Downloading from {url}");
+            Binding.tf_output_redirect.WriteLine($"Downloading from {url}");
             var download = Task.Run(() => wc.DownloadFile(url, relativeFilePath));
             while (!download.IsCompleted)
             {
                 Thread.Sleep(1000);
-                Console.Write(".");
+                Binding.tf_output_redirect.Write(".");
             }
-            Console.WriteLine("");
-            Console.WriteLine($"Downloaded to {relativeFilePath}");
+            Binding.tf_output_redirect.WriteLine("");
+            Binding.tf_output_redirect.WriteLine($"Downloaded to {relativeFilePath}");
 
             return true;
         }

test/TensorFlowNET.Keras.UnitTest/OutputTest.cs

@@ -0,0 +1,55 @@
+using Microsoft.VisualStudio.TestTools.UnitTesting;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+using static Tensorflow.Binding;
+using static Tensorflow.KerasApi;
+using Tensorflow.Keras;
+
+namespace Tensorflow.Keras.UnitTest
+{
+    [TestClass]
+    public class OutputTest
+    {
+        [TestMethod]
+        public void OutputRedirectTest()
+        {
+            using var newOutput = new System.IO.StringWriter();
+            tf_output_redirect = newOutput;
+            var model = keras.Sequential();
+            model.add(keras.Input(shape: 16));
+            model.summary();
+            string output = newOutput.ToString();
+            Assert.IsTrue(output.StartsWith("Model: sequential"));
+            tf_output_redirect = null; // don't forget to change it to null !!!!
+        }
+
+        [TestMethod]
+        public void SwitchOutputsTest()
+        {
+            using var newOutput = new System.IO.StringWriter();
+            var model = keras.Sequential();
+            model.add(keras.Input(shape: 16));
+            model.summary(); // Console.Out
+
+            tf_output_redirect = newOutput; // change to the custom one
+            model.summary();
+            string firstOutput = newOutput.ToString();
+            Assert.IsTrue(firstOutput.StartsWith("Model: sequential"));
+
+            // if tf_output_reditect is StringWriter, calling "set" will make the writer clear.
+            tf_output_redirect = null; // null means Console.Out
+            model.summary();
+
+            tf_output_redirect = newOutput; // again, to test whether the newOutput is clear.
+            model.summary();
+            string secondOutput = newOutput.ToString();
+            Assert.IsTrue(secondOutput.StartsWith("Model: sequential"));
+
+            Assert.IsTrue(firstOutput == secondOutput);
+            tf_output_redirect = null; // don't forget to change it to null !!!!
+        }
+    }
+}