torch.diff¶
-
torch.
diff
(input, n=1, dim=- 1, prepend=None, append=None) → Tensor¶ Computes the n-th forward difference along the given dimension.
The first-order differences are given by out[i] = input[i + 1] - input[i]. Higher-order differences are calculated by using
torch.diff()
recursively.Note
Only n = 1 is currently supported
- Parameters
input (Tensor) – the tensor to compute the differences on
n (int, optional) – the number of times to recursively compute the difference
dim (int, optional) – the dimension to compute the difference along. Default is the last dimension.
prepend (Tensor, optional) – values to prepend or append to
input
alongdim
before computing the difference. Their dimensions must be equivalent to that of input, and their shapes must match input’s shape except ondim
.append (Tensor, optional) – values to prepend or append to
input
alongdim
before computing the difference. Their dimensions must be equivalent to that of input, and their shapes must match input’s shape except ondim
.
- Keyword Arguments
out (Tensor, optional) – the output tensor.
Example:
>>> a = torch.tensor([1, 3, 2]) >>> torch.diff(a) tensor([ 2, -1]) >>> b = torch.tensor([4, 5]) >>> torch.diff(a, append=b) tensor([ 2, -1, 2, 1]) >>> c = torch.tensor([[1, 2, 3], [3, 4, 5]]) >>> torch.diff(c, dim=0) tensor([[2, 2, 2]]) >>> torch.diff(c, dim=1) tensor([[1, 1], [1, 1]])