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deepakkumar1984deepakkumar1984
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Optimizer and Regularizer classes skeleton added
1 parent 5b2d4cc commit 1c35292

17 files changed

Lines changed: 347 additions & 14 deletions

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‎TensorFlow.NET.sln‎

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@@ -11,6 +11,8 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "UnitTest", "test\TensorFlow
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EndProject
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Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Tensorflow.Keras", "src\TensorFlowNET.Keras\Tensorflow.Keras.csproj", "{6268B461-486A-460B-9B3C-86493CBBAAF7}"
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EndProject
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Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "Tensorflow.Keras.UnitTest", "test\Tensorflow.Keras.UnitTest\Tensorflow.Keras.UnitTest.csproj", "{EB92DD90-6346-41FB-B967-2B33A860AD98}"
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EndProject
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Global
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GlobalSection(SolutionConfigurationPlatforms) = preSolution
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Debug|Any CPU = Debug|Any CPU
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{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|Any CPU.Build.0 = Release|Any CPU
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{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|x64.ActiveCfg = Release|Any CPU
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{6268B461-486A-460B-9B3C-86493CBBAAF7}.Release|x64.Build.0 = Release|Any CPU
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{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug|x64.ActiveCfg = Debug|Any CPU
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{EB92DD90-6346-41FB-B967-2B33A860AD98}.Debug|x64.Build.0 = Debug|Any CPU
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{EB92DD90-6346-41FB-B967-2B33A860AD98}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{EB92DD90-6346-41FB-B967-2B33A860AD98}.Release|Any CPU.Build.0 = Release|Any CPU
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{EB92DD90-6346-41FB-B967-2B33A860AD98}.Release|x64.ActiveCfg = Release|Any CPU
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{EB92DD90-6346-41FB-B967-2B33A860AD98}.Release|x64.Build.0 = Release|Any CPU
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EndGlobalSection
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GlobalSection(SolutionProperties) = preSolution
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HideSolutionNode = FALSE

‎src/TensorFlowNET.Keras/Engine/CallContext.cs‎

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@@ -20,7 +20,7 @@ public CallContext()
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}
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public void enter(Layer layer, Tensor[] inputs, Graph build_graph, bool training, Saving saving = null) => throw new NotImplementedException();
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public void enter(Layer layer, Tensor[] inputs, Graph build_graph, bool training) => throw new NotImplementedException();
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public bool training_arg_passed_to_call(string[] argspec, Dictionary<string, object> args, Dictionary<string, object> kwargs) => throw new NotImplementedException();
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‎src/TensorFlowNET.Keras/Engine/Saving.cs‎

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This file was deleted.

‎src/TensorFlowNET.Keras/KwArgs.cs‎

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using System;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow.Keras
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{
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public class KwArgs
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{
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private Dictionary<string, object> args = new Dictionary<string, object>();
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public object this[string name]
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{
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get
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{
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return args.ContainsKey(name) ? args[name] : null;
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}
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set
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{
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args[name] = value;
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}
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}
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public T Get<T>(string name)
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{
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if (!args.ContainsKey(name))
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return default(T);
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return (T)args[name];
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}
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public static explicit operator KwArgs(ValueTuple<string, object>[] p)
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{
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KwArgs kwArgs = new KwArgs();
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kwArgs.args = new Dictionary<string, object>();
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foreach (var item in p)
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{
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kwArgs.args[item.Item1] = item.Item2;
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}
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return kwArgs;
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}
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}
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}

‎src/TensorFlowNET.Keras/Optimizer/Adadelta.cs‎

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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow.Keras
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{
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public class Adadelta : Optimizer
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{
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public Adadelta(float lr= 0.01f, float rho = 0.95f, float? epsilon = null, float decay = 0) : base(null)
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{
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throw new NotImplementedException();
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}
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public override Tensor[] get_updates(Tensor loss, variables @params)
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{
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throw new NotImplementedException();
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}
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public override Hashtable get_config()
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{
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throw new NotImplementedException();
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}
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}
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}

‎src/TensorFlowNET.Keras/Optimizer/Adagrad.cs‎

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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow.Keras
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{
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public class Adagrad : Optimizer
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{
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public Adagrad(float lr= 0.01f, float? epsilon = null, float decay = 0) : base(null)
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{
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throw new NotImplementedException();
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}
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public override Tensor[] get_updates(Tensor loss, variables @params)
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{
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throw new NotImplementedException();
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}
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public override Hashtable get_config()
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{
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throw new NotImplementedException();
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}
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}
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}

‎src/TensorFlowNET.Keras/Optimizer/Adam.cs‎

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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow.Keras
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{
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public class Adam : Optimizer
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{
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public Adam(float lr= 0.001f, float beta_1 = 0.9f, float beta_2 = 0.99f, float? epsilon = null, float decay = 0) : base(null)
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{
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throw new NotImplementedException();
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}
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public override Tensor[] get_updates(Tensor loss, variables @params)
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{
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throw new NotImplementedException();
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}
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public override Hashtable get_config()
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{
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throw new NotImplementedException();
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}
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}
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}

‎src/TensorFlowNET.Keras/Optimizer/Adamax.cs‎

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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow.Keras
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{
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public class Adamax : Optimizer
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{
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public Adamax(float lr = 0.002f, float beta_1 = 0.9f, float beta_2 = 0.999f, float? epsilon = null, float decay = 0) : base(null)
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{
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throw new NotImplementedException();
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}
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public override Tensor[] get_updates(Tensor loss, variables @params)
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{
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throw new NotImplementedException();
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}
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public override Hashtable get_config()
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{
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throw new NotImplementedException();
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}
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}
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}

‎src/TensorFlowNET.Keras/Optimizer/Nadam.cs‎

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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow.Keras
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{
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public class Nadam : Optimizer
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{
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public Nadam(float lr = 0.002f, float beta_1 = 0.9f, float beta_2 = 0.999f, float? epsilon = null, float schedule_decay = 0.004f) : base(null)
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{
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throw new NotImplementedException();
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}
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public override Tensor[] get_updates(Tensor loss, variables @params)
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{
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throw new NotImplementedException();
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}
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public override Hashtable get_config()
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{
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throw new NotImplementedException();
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}
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}
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}

‎src/TensorFlowNET.Keras/Optimizer/Optimizer.cs‎

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using NumSharp;
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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.Text;
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namespace Tensorflow.Keras
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{
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public class Optimizer
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{
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public Optimizer(KwArgs kwargs)
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{
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throw new NotImplementedException();
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}
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public virtual Tensor[] get_updates(Tensor loss, variables @params)
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{
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return null;
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}
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public virtual Tensor[] get_gradients(Tensor loss, variables @params) => throw new NotImplementedException();
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public virtual void set_weights(NDArray[] weights) => throw new NotImplementedException();
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public virtual NDArray[] get_weights() => throw new NotImplementedException();
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public virtual Hashtable get_config() => throw new NotImplementedException();
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public static string serialize(Optimizer optimizer) => throw new NotImplementedException();
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public static string deserialize(string config, object custom_objects = null) => throw new NotImplementedException();
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public static Optimizer get(object identifier) => throw new NotImplementedException();
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}
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}

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