/// <summary>
/// Return the recommended gain value for the given nonlinearity function.
/// </summary>
public static double calculate_gain(NonlinearityType nonlinearity, double param = 0.0)
{
return(THSInit_calculate_gain((long)nonlinearity, param));
}
/// <summary>
/// Fills the input Tensor with values according to the method described in 'Delving deep into rectifiers: Surpassing human-level performance on ImageNet classification'
/// </summary>
public static Tensor kaiming_normal_(Tensor tensor, double a = 0, FanInOut mode = FanInOut.FanIn, NonlinearityType nonlinearity = NonlinearityType.LeakyReLU)
{
var res = THSInit_kaiming_normal_(tensor.Handle, a, (long)mode, (long)nonlinearity);
if (res == IntPtr.Zero)
{
torch.CheckForErrors();
}
return(new Tensor(res));
}
