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# torch.argwhere

torch.argwhere(input) → Tensor

  Returns a tensor containing the indices of all non-zero elements of `input`. Each row in the result contains the indices of a non-zero element in `input`. The result is sorted lexicographically, with the last index changing the fastest (C-style).

  If `input` has n n n dimensions, then the resulting indices tensor `out` is of size (z×n)(z \times n)(z×n), where z z z is the total number of non-zero elements in the `input` tensor.

  Note

  This function is similar to NumPy’s argwhere.

  When `input` is on CUDA, this function causes host-device synchronization.

  Parameters:

    {input} –

  Example:

      >>> t = torch.tensor([1, 0, 1])
      >>> torch.argwhere(t)
      tensor([[0],
              [2]])
      >>> t = torch.tensor([[1, 0, 1], [0, 1, 1]])
      >>> torch.argwhere(t)
      tensor([[0, 0],
              [0, 2],
              [1, 1],
              [1, 2]])

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