/// <summary>
/// Creates 1-D tensor of size [(end - start) / step] with values from interval [start, end) and
/// common difference step, starting from start.
/// </summary>
/// <remarks>In the case of complex element types, 'arange' will create a complex tensor with img=0 in all elements.</remarks>
static public Tensor arange(Scalar start, Scalar stop, Scalar step, torch.Device device = null, bool requiresGrad = false)
{
device = torch.InitializeDevice(device);
var handle = THSTensor_arange(start.Handle, stop.Handle, step.Handle, (sbyte)ScalarType.Float32, (int)device.type, device.index, requiresGrad);
if (handle == IntPtr.Zero)
{
GC.Collect();
GC.WaitForPendingFinalizers();
handle = THSTensor_arange(start.Handle, stop.Handle, step.Handle, (sbyte)ScalarType.Float32, (int)device.type, device.index, requiresGrad);
}
if (handle == IntPtr.Zero)
{
torch.CheckForErrors();
}
var res = THSTensor_to_type(handle, (sbyte)ScalarType.ComplexFloat32);
if (res == IntPtr.Zero)
{
torch.CheckForErrors();
}
return(new Tensor(res));
}
public static Device InitializeDevice(torch.Device device)
{
if (device == null)
{
device = torch.CPU;
}
InitializeDeviceType(device.type);
return(device);
}
/// <summary>
/// Moves the parameters and buffers.
/// </summary>
/// <param name="device">The target device</param>
/// <returns></returns>
public Module to(torch.Device device)
{
return(to(device.type, device.index));
}
public Generator(ulong seed = 0, torch.Device?device = null) :
this(THSGenerator_new(seed, (long)(device?.type ?? DeviceType.CPU), device?.index ?? -1))
{
this.device = device ?? torch.CPU;
}
internal Generator(IntPtr nativeHandle)
{
Handle = nativeHandle;
device = torch.CPU;
}
