/// <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 TorchTensor arange(TorchScalar start, TorchScalar stop, TorchScalar step, 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 TorchTensor(res));
}
/// <summary>
/// Fills the input Tensor with the value 'val'
/// </summary>
public static TorchTensor constant(TorchTensor tensor, TorchScalar val)
{
var res = THSInit_constant_(tensor.Handle, val.Handle);
if (res == IntPtr.Zero)
{
Torch.CheckForErrors();
}
return(new TorchTensor(res));
}
/// <summary>
/// Returns the cross product of vectors in dimension dim of input and other.
/// input and other must have the same size, and the size of their dim dimension should be 3.
/// </summary>
public TorchTensor cross(TorchScalar other, long dim)
{
var res = THSTensor_cross(handle, other.Handle, dim);
if (res == IntPtr.Zero)
{
Torch.CheckForErrors();
}
return(new TorchTensor(res));
}
