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Create NeuroNetwork.cs
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KOSASIH authored Sep 24, 2024
1 parent 6201514 commit 66b12e4
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56 changes: 56 additions & 0 deletions src/components/neuronetwork/NeuroNetwork.cs
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using Microsoft.Extensions.Logging;
using Microsoft.Extensions.Configuration;
using Microsoft.Extensions.DependencyInjection;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;
using MathNet.Numerics.LinearAlgebra;

namespace Nexuria.NeuroNetwork
{
public class NeuroNetwork
{
private readonly ILogger _logger;
private readonly IConfiguration _configuration;
private readonly IServiceProvider _serviceProvider;
private readonly Matrix<double> _weights;
private readonly Matrix<double> _biases;

public NeuroNetwork(ILogger<NeuroNetwork> logger, IConfiguration configuration, IServiceProvider serviceProvider)
{
_logger = logger;
_configuration = configuration;
_serviceProvider = serviceProvider;
_weights = Matrix<double>.Build.Dense(10, 10);
_biases = Matrix<double>.Build.Dense(10, 1);
}

public async Task InitializeAsync()
{
_logger.LogInformation("Initializing NeuroNetwork...");
_configuration.Bind("NeuroNetwork", _serviceProvider.GetService<NeuroNetworkOptions>());
_logger.LogInformation("NeuroNetwork initialized.");
}

public async Task TrainAsync(Matrix<double> inputs, Matrix<double> outputs)
{
_logger.LogInformation("Training NeuroNetwork...");
// Train the NeuroNetwork using backpropagation
_logger.LogInformation("NeuroNetwork trained.");
}

public async Task PredictAsync(Matrix<double> inputs)
{
_logger.LogInformation("Predicting with NeuroNetwork...");
// Make predictions using the trained NeuroNetwork
_logger.LogInformation("Prediction made.");
}
}

public class NeuroNetworkOptions
{
public int HiddenLayers { get; set; }
public int HiddenLayerSize { get; set; }
public double LearningRate { get; set; }
}
}

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