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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 byout[i] = input[i + 1] - input[i]. Higher-orderdifferences are calculated by usingtorch.diff() recursively.

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 toinput alongdim before computing the difference.Their dimensions must be equivalent to that of input, and their shapesmust match input’s shape except ondim.

  • append (Tensor,optional) – values to prepend or append toinput alongdim before computing the difference.Their dimensions must be equivalent to that of input, and their shapesmust 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]])