Merge pull request #487 from deepakkumar1984/master

Keras Implementaion .. WIP

.gitignore

@@ -336,3 +336,4 @@ test/TensorFlowNET.Examples/mnist
 
 # training model resources
 .resources
+/redist

TensorFlow.NET.sln

@@ -9,6 +9,8 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Benchmark", "src\TensorFlow
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "UnitTest", "test\TensorFlowNET.UnitTest\UnitTest.csproj", "{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}"
 EndProject
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Tensorflow.Keras", "src\TensorFlowNET.Keras\Tensorflow.Keras.csproj", "{6268B461-486A-460B-9B3C-86493CBBAAF7}"
+EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
 		Debug|Any CPU = Debug|Any CPU
@@ -41,6 +43,14 @@ Global
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Release|Any CPU.Build.0 = Release|Any CPU
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Release|x64.ActiveCfg = Release|Any CPU
 		{23C28035-2FCE-41F3-9A12-E73CE8A5AE32}.Release|x64.Build.0 = Release|Any CPU
+		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug|x64.ActiveCfg = Debug|Any CPU
+		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Debug|x64.Build.0 = Debug|Any CPU
+		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|Any CPU.Build.0 = Release|Any CPU
+		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|x64.ActiveCfg = Release|Any CPU
+		{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|x64.Build.0 = Release|Any CPU
 	EndGlobalSection
 	GlobalSection(SolutionProperties) = preSolution
 		HideSolutionNode = FALSE

src/TensorFlowNET.Keras/Activations.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras
+{
+    class Activations
+    {
+    }
+}

src/TensorFlowNET.Keras/Applications/Densenet.cs

@@ -0,0 +1,35 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class Densenet
+    {
+        public static Tensor dense_block(Tensor x, int blocks, string name) => throw new NotImplementedException();
+
+        public static Tensor transition_block(Tensor x, float reduction, string name) => throw new NotImplementedException();
+
+        public static Tensor conv_block(Tensor x, float growth_rate, string name) => throw new NotImplementedException();
+
+        public static Model DenseNet(int blocks, bool include_top=true, string weights = "imagenet",
+                                    Tensor input_tensor = null, TensorShape input_shape = null, 
+                                    string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model DenseNet121(int blocks, bool include_top = true, string weights = "imagenet",
+                                    Tensor input_tensor = null, TensorShape input_shape = null,
+                                    string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model DenseNet169(int blocks, bool include_top = true, string weights = "imagenet",
+                                   Tensor input_tensor = null, TensorShape input_shape = null,
+                                   string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model DenseNet201(int blocks, bool include_top = true, string weights = "imagenet",
+                                   Tensor input_tensor = null, TensorShape input_shape = null,
+                                   string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/Efficientnet.cs

@@ -0,0 +1,60 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class BlockArg
+    {
+
+    }
+
+    public class Efficientnet
+    {
+        public static Model EfficientNet(float width_coefficient, float depth_coefficient, int default_size, float dropout_rate = 0.2f,
+                                        float drop_connect_rate = 0.2f, int depth_divisor = 8, string activation = "swish",
+                                        BlockArg[] blocks_args = null, string model_name = "efficientnet", bool include_top = true,
+                                        string weights = "imagenet", Tensor input_tensor = null, TensorShape input_shape = null, 
+                                        string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor block(Tensor inputs, string activation= "swish", float drop_rate= 0f,string name= "",
+                                    int filters_in= 32, int filters_out= 16, int kernel_size= 3, int strides= 1,
+                                    int expand_ratio= 1, float se_ratio= 0, bool  id_skip= true) => throw new NotImplementedException();
+
+        public static Model EfficientNetB0(bool include_top = true, string weights = "imagenet",
+                                    Tensor input_tensor = null, TensorShape input_shape = null,
+                                    string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model EfficientNetB1(bool include_top = true, string weights = "imagenet",
+                                  Tensor input_tensor = null, TensorShape input_shape = null,
+                                  string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model EfficientNetB2(bool include_top = true, string weights = "imagenet",
+                                  Tensor input_tensor = null, TensorShape input_shape = null,
+                                  string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model EfficientNetB3(bool include_top = true, string weights = "imagenet",
+                                  Tensor input_tensor = null, TensorShape input_shape = null,
+                                  string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model EfficientNetB4(bool include_top = true, string weights = "imagenet",
+                                 Tensor input_tensor = null, TensorShape input_shape = null,
+                                 string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model EfficientNetB5(bool include_top = true, string weights = "imagenet",
+                                 Tensor input_tensor = null, TensorShape input_shape = null,
+                                 string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model EfficientNetB6(bool include_top = true, string weights = "imagenet",
+                                 Tensor input_tensor = null, TensorShape input_shape = null,
+                                 string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model EfficientNetB7(bool include_top = true, string weights = "imagenet",
+                                 Tensor input_tensor = null, TensorShape input_shape = null,
+                                 string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/ImagenetUtils.cs

@@ -0,0 +1,22 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class ImagenetUtils
+    {
+        public static Tensor preprocess_input(Tensor x, string data_format= null, string mode= "caffe") => throw new NotImplementedException();
+        
+        public static Tensor decode_predictions(Tensor preds, int top= 5) => throw new NotImplementedException();
+
+        public static Tensor _preprocess_numpy_input(Tensor x, string data_format, string mode) => throw new NotImplementedException();
+
+        public static Tensor _preprocess_symbolic_input(Tensor x, string data_format, string mode) => throw new NotImplementedException();
+
+        public static TensorShape obtain_input_shape(TensorShape input_shape, int default_size, int min_size,
+                       string data_format, bool require_flatten, string weights= null) => throw new NotImplementedException();
+
+        public static ((int, int), (int, int)) correct_pad(Tensor inputs, (int, int) kernel_size) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/InceptionResnetV2.cs

@@ -0,0 +1,22 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class InceptionResnetV2
+    {
+        public static Model InceptionResNetV2(bool include_top = true, string weights = "imagenet",
+                                   Tensor input_tensor = null, TensorShape input_shape = null,
+                                   string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor conv2d_bn(Tensor x, int filters, (int, int) kernel_size, (int, int) strides, string padding= "same",
+                                        string activation= "relu", bool use_bias= false, string name= null) => throw new NotImplementedException();
+
+        public static Tensor inception_resnet_block(Tensor x, float scale, string block_type, int block_idx, string activation= "relu") => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/InceptionV3.cs

@@ -0,0 +1,19 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class InceptionV3
+    {
+        public static Model Inceptionv3(bool include_top = true, string weights = "imagenet",
+                                  Tensor input_tensor = null, TensorShape input_shape = null,
+                                  string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor conv2d_bn(Tensor x, int filters, int num_row, int num_col, string padding = "same", (int, int)? strides = null, string name = null) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/Mobilenet.cs

@@ -0,0 +1,18 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class Mobilenet
+    {
+        public static Model MobileNet(TensorShape input_shape= null, float alpha= 1.0f, int depth_multiplier= 1, float dropout= 1e-3f,
+                                    bool include_top= true, string weights= "imagenet", Tensor input_tensor= null, string pooling= null, int classes= 1000) => throw new NotImplementedException();
+
+        public static Tensor conv2d_bn(Tensor x, int filters, float alpha, (int, int)? kernel = null, (int, int)? strides = null) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/MobilenetV2.cs

@@ -0,0 +1,21 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class MobilenetV2
+    {
+        public static Model MobileNetV2(TensorShape input_shape = null, float alpha = 1.0f, bool include_top = true, 
+                                        string weights = "imagenet", Tensor input_tensor = null, string pooling = null,
+                                        int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor _inverted_res_block(Tensor inputs, int expansion, (int, int) stride, float alpha, int filters, string block_id) => throw new NotImplementedException();
+
+        public static Tensor _make_divisible(Tensor v, Tensor divisor, Tensor min_value= null) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/Nasnet.cs

@@ -0,0 +1,31 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class Nasnet
+    {
+        public static Model NASNet(TensorShape input_shape = null, int penultimate_filters = 4032, int num_blocks = 6, int stem_block_filters = 96,
+                                bool skip_reduction = true, int filter_multiplier = 2, bool include_top = true, string weights = null,
+                                Tensor input_tensor = null, string pooling = null, int classes = 1000, int? default_size = null) => throw new NotImplementedException();
+
+        public static Model NASNetMobile(TensorShape input_shape = null, bool include_top = true, string weights = "imagenet",
+                                    Tensor input_tensor = null, string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model NASNetLarge(TensorShape input_shape = null, bool include_top = true, string weights = "imagenet",
+                                    Tensor input_tensor = null, string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor _separable_conv_block(Tensor ip, int filters, (int, int)? kernel_size= null, (int, int)? strides= null, string block_id= null) => throw new NotImplementedException();
+
+        public static Tensor _adjust_block(Tensor p, Tensor ip, int filters, string block_id= null) => throw new NotImplementedException();
+
+        public static Tensor _normal_a_cell(Tensor p, Tensor ip, int filters, string block_id = null) => throw new NotImplementedException();
+
+        public static Tensor _reduction_a_cell(Tensor p, Tensor ip, int filters, string block_id = null) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/Resnet.cs

@@ -0,0 +1,41 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class Resnet
+    {
+        public static Model ResNet(Func<Tensor, Tensor> stack_fn, bool preact, bool use_bias, string model_name= "resnet", bool include_top= true,
+                                    string weights= "imagenet", Tensor input_tensor= null, TensorShape input_shape= null, string pooling= null,
+                                    int classes= 1000) => throw new NotImplementedException();
+
+        public static Tensor block1(Tensor x, int filters, int kernel_size= 3, int stride= 1, bool conv_shortcut= true, string name= null) => throw new NotImplementedException();
+
+        public static Tensor stack1(Tensor x, int filters, int blocks, int stride1 = 2, string name = null) => throw new NotImplementedException();
+
+        public static Tensor block2(Tensor x, int filters, int kernel_size = 3, int stride = 1, bool conv_shortcut = true, string name = null) => throw new NotImplementedException();
+
+        public static Tensor stack2(Tensor x, int filters, int blocks, int stride1 = 2, string name = null) => throw new NotImplementedException();
+
+        public static Tensor block3(Tensor x, int filters, int kernel_size = 3, int stride = 1, int groups = 32, bool conv_shortcut = true, string name = null) => throw new NotImplementedException();
+
+        public static Tensor stack3(Tensor x, int filters, int blocks, int stride1 = 2, int groups = 32, string name = null) => throw new NotImplementedException();
+
+        public static Model ResNet50(bool include_top = true, string weights = "imagenet",
+                                  Tensor input_tensor = null, TensorShape input_shape = null,
+                                  string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model ResNet101(bool include_top = true, string weights = "imagenet",
+                                  Tensor input_tensor = null, TensorShape input_shape = null,
+                                  string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model ResNet152(bool include_top = true, string weights = "imagenet",
+                                  Tensor input_tensor = null, TensorShape input_shape = null,
+                                  string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/ResnetV2.cs

@@ -0,0 +1,25 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class ResnetV2
+    {
+        public static Model ResNet50V2(bool include_top = true, string weights = "imagenet",
+                                   Tensor input_tensor = null, TensorShape input_shape = null,
+                                   string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model ResNet101V2(bool include_top = true, string weights = "imagenet",
+                                  Tensor input_tensor = null, TensorShape input_shape = null,
+                                  string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Model ResNet152V2(bool include_top = true, string weights = "imagenet",
+                                  Tensor input_tensor = null, TensorShape input_shape = null,
+                                  string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/Vgg16.cs

@@ -0,0 +1,17 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class Vgg16
+    {
+        public static Model VGG16(bool include_top = true, string weights = "imagenet",
+                                Tensor input_tensor = null, TensorShape input_shape = null,
+                                string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/Vgg19.cs

@@ -0,0 +1,17 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class Vgg19
+    {
+        public static Model VGG19(bool include_top = true, string weights = "imagenet",
+                                Tensor input_tensor = null, TensorShape input_shape = null,
+                                string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Applications/Xception.cs

@@ -0,0 +1,17 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Applications
+{
+    public class Xception
+    {
+        public static Model XCeption(bool include_top = true, string weights = "imagenet",
+                                Tensor input_tensor = null, TensorShape input_shape = null,
+                                string pooling = null, int classes = 1000) => throw new NotImplementedException();
+
+        public static Tensor preprocess_input(Tensor x, string data_format = null) => throw new NotImplementedException();
+
+        public static Tensor decode_predictions(Tensor preds, int top = 5) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Backend.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras
+{
+    class Backend
+    {
+    }
+}

src/TensorFlowNET.Keras/BackendConfig.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras
+{
+    class BackendConfig
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/BaseLogger.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class BaseLogger
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/CSVLogger.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class CSVLogger
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/Callback.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class Callback
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/CallbackList.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class CallbackList
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/EarlyStopping.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class EarlyStopping
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/History.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class History
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/LambdaCallback.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class LambdaCallback
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/LearningRateScheduler.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class LearningRateScheduler
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/ModelCheckpoint.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class ModelCheckpoint
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/ProgbarLogger.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class ProgbarLogger
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/ReduceLROnPlateau.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class ReduceLROnPlateau
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/RemoteMonitor.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class RemoteMonitor
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/TensorBoard.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class TensorBoard
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/TensorBoardV1.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class TensorBoardV1
+    {
+    }
+}

src/TensorFlowNET.Keras/Callbacks/TerminateOnNaN.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Callbacks
+{
+    class TerminateOnNaN
+    {
+    }
+}

src/TensorFlowNET.Keras/Constraints/ConstraintBase.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Constraints
+{
+    public abstract class ConstraintBase
+    {
+    }
+}

src/TensorFlowNET.Keras/Constraints/MaxNorm.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Constraints
+{
+    class MaxNorm
+    {
+    }
+}

src/TensorFlowNET.Keras/Constraints/MinMaxNorm.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Constraints
+{
+    class MinMaxNorm
+    {
+    }
+}

src/TensorFlowNET.Keras/Constraints/NonNeg.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Constraints
+{
+    class NonNeg
+    {
+    }
+}

src/TensorFlowNET.Keras/Constraints/RadialConstraint.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Constraints
+{
+    class RadialConstraint
+    {
+    }
+}

src/TensorFlowNET.Keras/Constraints/UnitNorm.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Constraints
+{
+    class UnitNorm
+    {
+    }
+}

src/TensorFlowNET.Keras/Datasets/BostonHousing.cs

@@ -0,0 +1,11 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Datasets
+{
+    public class BostonHousing
+    {
+        public static ((Tensor, Tensor), (Tensor, Tensor)) load_data(string path = "boston_housing.npz", float test_split = 0.2f, int seed = 113) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Datasets/Cifar.cs

@@ -0,0 +1,11 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Datasets
+{
+    public class Cifar
+    {
+        public (Tensor, Tensor) load_batch(string fpath, string label_key = "labels") => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Datasets/Cifar10.cs

@@ -0,0 +1,11 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Datasets
+{
+    public class Cifar10
+    {
+        public static ((Tensor, Tensor), (Tensor, Tensor)) load_data() => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Datasets/Cifar100.cs

@@ -0,0 +1,11 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Datasets
+{
+    public class Cifar100
+    {
+        public static ((Tensor, Tensor), (Tensor, Tensor)) load_data(string label_mode = "fine") => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Datasets/FashionMNIST.cs

@@ -0,0 +1,11 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Datasets
+{
+    public class FashionMNIST
+    {
+        public static ((Tensor, Tensor), (Tensor, Tensor)) load_data() => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Datasets/IMDB.cs

@@ -0,0 +1,15 @@
+using Newtonsoft.Json.Linq;
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Datasets
+{
+    public class IMDB
+    {
+        public static ((Tensor, Tensor), (Tensor, Tensor)) load_data(string path= "imdb.npz", int? num_words= null, int skip_top= 0, int? maxlen= null,
+                                                            int seed= 113,int start_char= 1, int oov_char= 2, int index_from= 3) => throw new NotImplementedException();
+
+        public static JObject get_word_index(string path= "imdb_word_index.json") => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Datasets/MNIST.cs

@@ -0,0 +1,11 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Datasets
+{
+    public class MNIST
+    {
+        public static ((Tensor, Tensor), (Tensor, Tensor)) load_data(string path = "mnist.npz") => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Datasets/Reuters.cs

@@ -0,0 +1,12 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Datasets
+{
+    public class Reuters
+    {
+        public static ((Tensor, Tensor), (Tensor, Tensor)) load_data(string path = "reuters.npz", int? num_words= null, int skip_top= 0,
+                                                int? maxlen= null,float test_split= 0.2f, int seed= 113,int start_char= 1,int oov_char= 2,int index_from= 3) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Distribute/DistributedTrainingUtils.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class DistributedTrainingUtils
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/KerasCorrectnessTestBase.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class KerasCorrectnessTestBase
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/KerasDnnCorrectnessTest.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class KerasDnnCorrectnessTest
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/KerasEmbeddingModelCorrectnessTest.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class KerasEmbeddingModelCorrectnessTest
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/KerasImageModelCorrectnessTest.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class KerasImageModelCorrectnessTest
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/KerasOptimizerV2Test.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class KerasOptimizerV2Test
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/KerasPremadeModelsTest.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class KerasPremadeModelsTest
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/KerasRnnModelCorrectnessTest.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class KerasRnnModelCorrectnessTest
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/KerasStatefulLstmModelCorrectnessTest.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class KerasStatefulLstmModelCorrectnessTest
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/KerasUtilsTest.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class KerasUtilsTest
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/MultiWorkerCallbackTF1Test.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class MultiWorkerCallbackTF1Test
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/MultiWorkerCallbackTf2Test.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class MultiWorkerCallbackTf2Test
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/MultiWorkerFaultToleranceTest.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class MultiWorkerFaultToleranceTest
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/MultiWorkerTest.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class MultiWorkerTest
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/MultiWorkerTestingUtils.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class MultiWorkerTestingUtils
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/MultiWorkerTrainingState.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class MultiWorkerTrainingState
+    {
+    }
+}

src/TensorFlowNET.Keras/Distribute/MultiWorkerTrainingStateTest.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Distribute
+{
+    class MultiWorkerTrainingStateTest
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/BaseLayer.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    public class Layer
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/BaseLayerUtils.cs

@@ -0,0 +1,24 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+using Tensorflow.Keras.Initializers;
+using Tensorflow.Keras.Metrics;
+
+namespace Tensorflow.Keras.Engine
+{
+    public class BaseLayerUtils
+    {
+        public static (Metric, Metric) create_mean_metric(Tensor value, string name = null) => throw new NotImplementedException();
+
+        public static VariableV1 make_variable(string name, TensorShape shape= null, TF_DataType dtype= TF_DataType.TF_FLOAT, Initializer initializer= null,
+                            bool trainable= true, string caching_device= null, bool validate_shape= true, Constraints.ConstraintBase constraint= null,
+                            bool use_resource= false, Graph[] collections= null, VariableSynchronization synchronization= VariableSynchronization.Auto,
+                            VariableAggregation aggregation= VariableAggregation.None) => throw new NotImplementedException();
+
+        public static Tensor[] collect_previous_mask(TensorArray input_tensors) => throw new NotImplementedException();
+
+        public bool have_all_keras_metadata(Tensor[] tensors) => throw new NotImplementedException();
+
+        public static dynamic generate_placeholders_from_shape(TensorShape shape) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Engine/BasePreprocessingLayer.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class BasePreprocessingLayer
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/BasePreprocessingLayerV1.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class BasePreprocessingLayerV1
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/CompileUtils.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class CompileUtils
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/DataAdapter.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class DataAdapter
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/InputLayer.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class InputLayer
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/InputSpec.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class InputSpec
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/Network.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class Network
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/Node.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class Node
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/PartialBatchPaddingHandler.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class PartialBatchPaddingHandler
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/Saving.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class Saving
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/Sequential.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class Sequential
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/Training.cs

@@ -0,0 +1,24 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    public class Training
+    {
+        public class Model
+        {
+
+        }
+
+        public class _TrainingEndpoint
+        {
+
+        }
+
+        public class _TrainingTarget
+        {
+
+        }
+    }
+}

src/TensorFlowNET.Keras/Engine/TrainingArrays.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class TrainingArrays
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/TrainingDistributed.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class TrainingDistributed
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/TrainingEager.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class TrainingEager
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/TrainingGenerator.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class TrainingGenerator
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/TrainingUtils.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class TrainingUtils
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/TrainingV1.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class TrainingV1
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/TrainingV2.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class TrainingV2
+    {
+    }
+}

src/TensorFlowNET.Keras/Engine/TrainingV2Utils.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Engine
+{
+    class TrainingV2Utils
+    {
+    }
+}

src/TensorFlowNET.Keras/Estimator.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras
+{
+    class Estimator
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializer/BaseInitializer.cs

@@ -1,7 +0,0 @@
-namespace Keras.Initializer
-{
-    class BaseInitializer : IInitializer
-    {
-        public int seed;
-    }
-}

src/TensorFlowNET.Keras/Initializers/Constant.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class Constant
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/ConstantV2.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class ConstantV2
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/GlorotNormal.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class GlorotNormal
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/GlorotNormalV2.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class GlorotNormalV2
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/GlorotUniform.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class GlorotUniform
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/GlorotUniformV2.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class GlorotUniformV2
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/HeNormal.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class HeNormal
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/HeNormalV2.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class HeNormalV2
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/HeUniform.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class HeUniform
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/HeUniformV2.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class HeUniformV2
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/Identity.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class Identity
+    {
+    }
+}

src/TensorFlowNET.Keras/Initializers/IdentityV2.cs

@@ -0,0 +1,10 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.Initializers
+{
+    class IdentityV2
+    {
+    }
+}