def convert_affinematrix_to_homography(A: torch.Tensor) -> torch.Tensor:
    'Function that converts batch of affine matrices from [Bx2x3] to [Bx3x3].\n\n    Examples::\n\n        >>> input = torch.rand(2, 2, 3)  # Bx2x3\n        >>> output = convert_affinematrix_to_homography(input)  # Bx3x3\n    '
    if (not isinstance(A, torch.Tensor)):
        raise TypeError('Input type is not a torch.Tensor. Got {}'.format(type(A)))
    if (not ((len(A.shape) == 3) and (A.shape[(- 2):] == (2, 3)))):
        raise ValueError('Input matrix must be a Bx2x3 tensor. Got {}'.format(A.shape))
    return _convert_affinematrix_to_homography_impl(A)
Function that converts batch of affine matrices from [Bx2x3] to [Bx3x3].

Examples::

    >>> input = torch.rand(2, 2, 3)  # Bx2x3
    >>> output = convert_affinematrix_to_homography(input)  # Bx3x3
def convert_affinematrix_to_homography(A: torch.Tensor) -> torch.Tensor:
    'Function that converts batch of affine matrices from [Bx2x3] to [Bx3x3].\n\n    Examples::\n\n        >>> input = torch.rand(2, 2, 3)  # Bx2x3\n        >>> output = convert_affinematrix_to_homography(input)  # Bx3x3\n    '
    if (not isinstance(A, torch.Tensor)):
        raise TypeError('Input type is not a torch.Tensor. Got {}'.format(type(A)))
    if (not ((len(A.shape) == 3) and (A.shape[(- 2):] == (2, 3)))):
        raise ValueError('Input matrix must be a Bx2x3 tensor. Got {}'.format(A.shape))
    return _convert_affinematrix_to_homography_impl(A)