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# torch.Tensor.index_copy_

Tensor.index_copy_(dim, index, tensor) → Tensor

  Copies the elements of `tensor` into the `self` tensor by selecting the indices in the order given in `index`. For example, if `dim == 0` and `index[i] == j`, then the `i`th row of `tensor` is copied to the `j`th row of `self`.

  The `dim`th dimension of `tensor` must have the same size as the length of `index` (which must be a vector), and all other dimensions must match `self`, or an error will be raised.

  Note

  If `index` contains duplicate entries, multiple elements from `tensor` will be copied to the same index of `self`. The result is nondeterministic since it depends on which copy occurs last.

  Parameters:

    - dim (int) – dimension along which to index

    - index (LongTensor) – indices of `tensor` to select from

    - tensor (Tensor) – the tensor containing values to copy

  Example:

      >>> x = torch.zeros(5, 3)
      >>> t = torch.tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=torch.float)
      >>> index = torch.tensor([0, 4, 2])
      >>> x.index_copy_(0, index, t)
      tensor([[ 1.,  2.,  3.],
              [ 0.,  0.,  0.],
              [ 7.,  8.,  9.],
              [ 0.,  0.,  0.],
              [ 4.,  5.,  6.]])

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