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# torch.index_select

torch.index_select(input, dim, index, *, out=None) → Tensor

  Returns a new tensor which indexes the `input` tensor along dimension `dim` using the entries in `index` which is a LongTensor.

  The returned tensor has the same number of dimensions as the original tensor (`input`). The `dim`th dimension has the same size as the length of `index`; other dimensions have the same size as in the original tensor.

  Note

  The returned tensor does not use the same storage as the original tensor. If `out` has a different shape than expected, we silently change it to the correct shape, reallocating the underlying storage if necessary.

  Parameters:

    - input (Tensor) – the input tensor.

    - dim (int) – the dimension in which we index

    - index (IntTensor or LongTensor) – the 1-D tensor containing the indices to index

  Keyword Arguments:

    out (Tensor, optional) – the output tensor.

  Example:

      >>> x = torch.randn(3, 4)
      >>> x
      tensor([[ 0.1427,  0.0231, -0.5414, -1.0009],
              [-0.4664,  0.2647, -0.1228, -1.1068],
              [-1.1734, -0.6571,  0.7230, -0.6004]])
      >>> indices = torch.tensor([0, 2])
      >>> torch.index_select(x, 0, indices)
      tensor([[ 0.1427,  0.0231, -0.5414, -1.0009],
              [-1.1734, -0.6571,  0.7230, -0.6004]])
      >>> torch.index_select(x, 1, indices)
      tensor([[ 0.1427, -0.5414],
              [-0.4664, -0.1228],
              [-1.1734,  0.7230]])

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