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# torch.unflatten

torch.unflatten(input, dim, sizes) → Tensor

  Expands a dimension of the input tensor over multiple dimensions.

  See also

  `torch.flatten()` the inverse of this function. It coalesces several dimensions into one.

  Parameters:

    - input (Tensor) – the input tensor.

    - dim (int) – Dimension to be unflattened, specified as an index into `input.shape`.

    - sizes (Tuple[int]) – New shape of the unflattened dimension. One of its elements can be -1 in which case the corresponding output dimension is inferred. Otherwise, the product of `sizes` must equal `input.shape[dim]`.

  Returns:

    A View of input with the specified dimension unflattened.

  Examples::

        >>> torch.unflatten(torch.randn(3, 4, 1), 1, (2, 2)).shape
        torch.Size([3, 2, 2, 1])
        >>> torch.unflatten(torch.randn(3, 4, 1), 1, (-1, 2)).shape
        torch.Size([3, 2, 2, 1])
        >>> torch.unflatten(torch.randn(5, 12, 3), -2, (2, 2, 3, 1, 1)).shape
        torch.Size([5, 2, 2, 3, 1, 1, 3])

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