def rotation_matrix_to_angle_axis(rotation_matrix: torch.Tensor) -> torch.Tensor:
    'Convert 3x3 rotation matrix to Rodrigues vector.\n\n    Args:\n        rotation_matrix (torch.Tensor): rotation matrix.\n\n    Returns:\n        torch.Tensor: Rodrigues vector transformation.\n\n    Shape:\n        - Input: :math:`(N, 3, 3)`\n        - Output: :math:`(N, 3)`\n\n    Example:\n        >>> input = torch.rand(2, 3, 3)  # Nx3x3\n        >>> output = rotation_matrix_to_angle_axis(input)  # Nx3\n    '
    if (not isinstance(rotation_matrix, torch.Tensor)):
        raise TypeError('Input type is not a torch.Tensor. Got {}'.format(type(rotation_matrix)))
    if (not (rotation_matrix.shape[(- 2):] == (3, 3))):
        raise ValueError('Input size must be a (*, 3, 3) tensor. Got {}'.format(rotation_matrix.shape))
    quaternion: torch.Tensor = rotation_matrix_to_quaternion(rotation_matrix)
    return quaternion_to_angle_axis(quaternion)
Convert 3x3 rotation matrix to Rodrigues vector.

Args:
    rotation_matrix (torch.Tensor): rotation matrix.

Returns:
    torch.Tensor: Rodrigues vector transformation.

Shape:
    - Input: :math:`(N, 3, 3)`
    - Output: :math:`(N, 3)`

Example:
    >>> input = torch.rand(2, 3, 3)  # Nx3x3
    >>> output = rotation_matrix_to_angle_axis(input)  # Nx3
def rotation_matrix_to_angle_axis(rotation_matrix: torch.Tensor) -> torch.Tensor:
    'Convert 3x3 rotation matrix to Rodrigues vector.\n\n    Args:\n        rotation_matrix (torch.Tensor): rotation matrix.\n\n    Returns:\n        torch.Tensor: Rodrigues vector transformation.\n\n    Shape:\n        - Input: :math:`(N, 3, 3)`\n        - Output: :math:`(N, 3)`\n\n    Example:\n        >>> input = torch.rand(2, 3, 3)  # Nx3x3\n        >>> output = rotation_matrix_to_angle_axis(input)  # Nx3\n    '
    if (not isinstance(rotation_matrix, torch.Tensor)):
        raise TypeError('Input type is not a torch.Tensor. Got {}'.format(type(rotation_matrix)))
    if (not (rotation_matrix.shape[(- 2):] == (3, 3))):
        raise ValueError('Input size must be a (*, 3, 3) tensor. Got {}'.format(rotation_matrix.shape))
    quaternion: torch.Tensor = rotation_matrix_to_quaternion(rotation_matrix)
    return quaternion_to_angle_axis(quaternion)