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# torch.tile

torch.tile(input, dims) → Tensor

  Constructs a tensor by repeating the elements of `input`. The `dims` argument specifies the number of repetitions in each dimension.

  If `dims` specifies fewer dimensions than `input` has, then ones are prepended to `dims` until all dimensions are specified. For example, if `input` has shape (8, 6, 4, 2) and `dims` is (2, 2), then `dims` is treated as (1, 1, 2, 2).

  Analogously, if `input` has fewer dimensions than `dims` specifies, then `input` is treated as if it were unsqueezed at dimension zero until it has as many dimensions as `dims` specifies. For example, if `input` has shape (4, 2) and `dims` is (3, 3, 2, 2), then `input` is treated as if it had the shape (1, 1, 4, 2).

  Note

  This function is similar to NumPy’s tile function.

  Parameters:

    - input (Tensor) – the tensor whose elements to repeat.

    - dims (tuple) – the number of repetitions per dimension.

  Example:

      >>> x = torch.tensor([1, 2, 3])
      >>> x.tile((2,))
      tensor([1, 2, 3, 1, 2, 3])
      >>> y = torch.tensor([[1, 2], [3, 4]])
      >>> torch.tile(y, (2, 2))
      tensor([[1, 2, 1, 2],
              [3, 4, 3, 4],
              [1, 2, 1, 2],
              [3, 4, 3, 4]])

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