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add relu6 · MSavameri/TensorFlow.NET@ec4f372 · GitHub

/ TensorFlow.NET Public
forked from SciSharp/TensorFlow.NET

Commit ec4f372

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dogvane
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add relu6
1 parent 9e3654b commit ec4f372

6 files changed

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‎src/TensorFlowNET.Core/APIs/tf.nn.cs‎

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@@ -101,6 +101,8 @@ public Tensor embedding_lookup(Tensor @params,
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name: name);
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public IActivation relu() => new relu();
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public IActivation swish() => new swish();
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public IActivation tanh() => new tanh();
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@@ -111,6 +113,9 @@ public Tensor tanh(Tensor x, string name = null)
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public Tensor relu(Tensor features, string name = null)
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=> gen_nn_ops.relu(features, name);
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public Tensor relu6(Tensor features, string name = null)
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=> gen_nn_ops.relu6(features, name);
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public Tensor[] fused_batch_norm(Tensor x,
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Tensor scale,
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Tensor offset,

‎src/TensorFlowNET.Core/Keras/Activations/Activations.cs‎

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@@ -32,6 +32,7 @@ public interface IActivationsApi
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Activation Linear { get; }
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Activation Relu { get; }
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Activation Relu6 { get; }
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Activation Sigmoid { get; }
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‎src/TensorFlowNET.Core/Keras/Layers/ILayersApi.cs‎

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@@ -180,6 +180,9 @@ public ILayer LayerNormalization(Axis? axis,
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public ILayer Normalization(Shape? input_shape = null, int? axis = -1, float? mean = null, float? variance = null, bool invert = false);
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public ILayer LeakyReLU(float alpha = 0.3f);
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public ILayer ReLU6();
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public IRnnCell LSTMCell(int uints,
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string activation = "tanh",
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string recurrent_activation = "sigmoid",

‎src/TensorFlowNET.Keras/Activations.cs‎

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@@ -20,6 +20,11 @@ public class Activations: IActivationsApi
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Name = "relu",
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ActivationFunction = (features, name) => tf.Context.ExecuteOp("Relu", name, new ExecuteOpArgs(features))
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};
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private static Activation _relu6 = new Activation()
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{
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Name = "relu6",
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ActivationFunction = (features, name) => tf.Context.ExecuteOp("Relu6", name, new ExecuteOpArgs(features))
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};
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private static Activation _sigmoid = new Activation()
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{
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Name = "sigmoid",
@@ -55,6 +60,7 @@ static Activations()
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_nameActivationMap = new Dictionary<string, Activation>();
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RegisterActivation(_relu);
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RegisterActivation(_relu6);
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RegisterActivation(_linear);
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RegisterActivation(_sigmoid);
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RegisterActivation(_softmax);
@@ -65,6 +71,7 @@ static Activations()
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public Activation Linear => _linear;
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public Activation Relu => _relu;
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public Activation Relu6 => _relu6;
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public Activation Sigmoid => _sigmoid;
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‎src/TensorFlowNET.Keras/Layers/Activation/ReLu6.cs‎

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@@ -0,0 +1,25 @@
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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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using Tensorflow.Keras.ArgsDefinition;
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using Tensorflow.Keras.Engine;
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using Tensorflow.Common.Types;
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using static Tensorflow.Binding;
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namespace Tensorflow.Keras.Layers
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{
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/// <summary>
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/// Leaky version of a Rectified Linear Unit.
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/// </summary>
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public class ReLu6 : Layer
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{
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public ReLu6() : base(new LayerArgs { })
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{
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}
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protected override Tensors Call(Tensors inputs, Tensors state = null, bool? training = null, IOptionalArgs? optional_args = null)
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{
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return tf.nn.relu6(inputs);
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}
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}
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}

‎src/TensorFlowNET.Keras/Layers/LayersApi.cs‎

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@@ -735,6 +735,15 @@ public ILayer LeakyReLU(float alpha = 0.3f)
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});
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/// <summary>
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/// Leaky version of a Rectified Linear Unit.
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/// </summary>
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/// <param name="alpha">Negative slope coefficient.</param>
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/// <returns></returns>
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public ILayer ReLU6()
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=> new ReLu6();
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public IRnnCell SimpleRNNCell(
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int units,
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string activation = "tanh",

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