Mixture of experts Example

[kiranmaya]

need MoE example, ChatGPT wrote some thing ,but ,I don't thinking its a good gating network
`using System;
using Tensorflow;
using static Tensorflow.Binding;
using Tensorflow.Keras;
using Tensorflow.Keras.Layers;
using Tensorflow.Keras.Models;

class Program
{
static void Main(string[] args)
{
int inputDim = 10;
int outputDim = 1;
int numExperts = 3;

    // Create experts
    var experts = new Sequential[numExperts];
    for (int i = 0; i < numExperts; i++)
    {
        experts[i] = CreateExpert(inputDim, outputDim);
    }

    // Input tensor
    var inputLayer = keras.Input(shape: new int[] { inputDim });
    
    // Output from dynamic routing
    var output = DynamicRouting(inputLayer, experts, numExperts);
    
    // Build model
    var moeModel = keras.Model(inputLayer, output);
    moeModel.compile(optimizer: keras.optimizers.Adam(), loss: "mse");

    moeModel.summary(); // Optional: to view the model summary
}

static Sequential CreateExpert(int inputDim, int outputDim)
{
    var model = keras.Sequential();
    model.add(keras.Input(shape: new int[] { inputDim }));
    model.add(new Dense(64, activation: keras.activations.Relu));
    model.add(new Dense(outputDim, activation: keras.activations.Linear));
    return model;
}

static Tensor DynamicRouting(Tensor inputTensor, Sequential[] experts, int numExperts, int numActions = 2)
{
    // Policy network to select experts dynamically
    var policyLayer = new Dense(numActions, activation: keras.activations.Softmax).Apply(inputTensor);
    
    // Expert outputs
    var expertOutputs = new Tensor[numExperts];
    for (int i = 0; i < numExperts; i++)
    {
        expertOutputs[i] = experts[i].Apply(inputTensor);
    }

    // Selecting the expert with the highest probability
    var selectedExpert = tf.argmax(policyLayer, axis: 1);
    
    // Gather the output from the selected expert
    var output = tf.gather(expertOutputs, selectedExpert);
    
    return output;
}

}
`