/// <summary>
/// Densely-connected layer class. aka fully-connected<br></br>
/// `outputs = activation(inputs * kernel + bias)`
/// </summary>
/// <param name="inputs"></param>
/// <param name="units">Python integer, dimensionality of the output space.</param>
/// <param name="activation"></param>
/// <param name="use_bias">Boolean, whether the layer uses a bias.</param>
/// <param name="kernel_initializer"></param>
/// <param name="bias_initializer"></param>
/// <param name="trainable"></param>
/// <param name="name"></param>
/// <param name="reuse"></param>
/// <returns></returns>
public Tensor dense(Tensor inputs,
int units,
Activation activation = null,
bool use_bias = true,
IInitializer kernel_initializer = null,
IInitializer bias_initializer = null,
bool trainable = true,
string name = null,
bool?reuse = null)
{
if (bias_initializer == null)
{
bias_initializer = tf.zeros_initializer;
}
var layer = new Dense(new DenseArgs
{
Units = units,
Activation = activation,
UseBias = use_bias,
BiasInitializer = bias_initializer,
KernelInitializer = kernel_initializer,
Trainable = trainable,
Name = name
});
return(layer.Apply(inputs));
}