/// <summary>
/// Initializes a new instance of the <see cref="NnLayer"/> class with the specified parameters.
/// </summary>
/// <param name="numberOfInputs">The number of inputs.</param>
/// <param name="numberOfOutputs">The number of outputs.</param>
/// <param name="activationFunction">The activation function.</param>
public NnLayer(int numberOfInputs, int numberOfOutputs, IActivationFunction activationFunction)
{
Contracts.ValueGreaterThanZero(numberOfInputs, nameof(numberOfInputs));
Contracts.ValueGreaterThanZero(numberOfOutputs, nameof(numberOfOutputs));
Contracts.ValueNotNull(activationFunction, nameof(activationFunction));
_numberOfInputs = numberOfInputs;
_numberOfOutputs = numberOfOutputs;
_activationFunction = activationFunction;
_weightMatrix = new WeightMatrix(_numberOfInputs, _numberOfOutputs);
_biasVector = new BiasVector(_numberOfOutputs);
}
/// <summary>
/// Initializes a new instance of the <see cref="NnLayer"/> class with the specified parameters.
/// </summary>
/// <param name="weightsRowCount">The number of row in the weight matrix.</param>
/// <param name="weightsColCount">The number of columns in the weight matrix.</param>
/// <param name="biasLength">The bias length.</param>
/// <param name="data">The values of the weights and biases.</param>
/// <param name="activationFunction">The activation function.</param>
public NnLayer(int weightsRowCount, int weightsColCount, int biasLength, double[] data, IActivationFunction activationFunction)
{
Contracts.ValueGreaterThanZero(weightsRowCount, nameof(weightsRowCount));
Contracts.ValueGreaterThanZero(weightsColCount, nameof(weightsColCount));
Contracts.ValueGreaterThanZero(biasLength, nameof(biasLength));
Contracts.ValueNotNull(activationFunction, nameof(activationFunction));
_numberOfInputs = weightsRowCount;
_numberOfOutputs = weightsColCount;
_weightMatrix = new WeightMatrix(VectorUtilities.CreateMatrix(weightsRowCount, weightsColCount, data));
var biasData = new double[biasLength];
Buffer.BlockCopy(data, weightsRowCount * weightsColCount * sizeof(double), biasData, 0, biasLength * sizeof(double));
_biasVector = new BiasVector(biasData);
_activationFunction = activationFunction;
}
