code: def scale_pinhole(pinholes: Tensor, scale: Tensor) -> Tensor:
      r"""Scale the pinhole matrix for each pinhole model.
  
      .. note::
          This method is going to be deprecated in version 0.2 in favour of
          :attr:`kornia.PinholeCamera.scale()`.
  
      Args:
          pinholes: tensor with the pinhole model.
          scale: tensor of scales.
  
      Returns:
          tensor of scaled pinholes.
  
      Shape:
          - Input: :math:`(N, 12)` and :math:`(N, 1)`
          - Output: :math:`(N, 12)`
  
      Example:
          >>> rng = torch.manual_seed(0)
          >>> pinhole_i = torch.rand(1, 12)  # Nx12
          >>> scales = 2.0 * torch.ones(1)   # N
          >>> scale_pinhole(pinhole_i, scales)  # Nx12
          tensor([[0.9925, 1.5364, 0.1770, 0.2641, 0.6148, 1.2682, 0.4901, 0.8964, 0.4556,
                   0.6323, 0.3489, 0.4017]])
      """
      # warnings.warn("scale_pinhole will be deprecated in version 0.2, "
      #              "use PinholeCamera.scale() instead",
      #              PendingDeprecationWarning)
      if not (len(pinholes.shape) == 2 and pinholes.shape[1] == 12):
          raise AssertionError(pinholes.shape)
      if len(scale.shape) != 1:
          raise AssertionError(scale.shape)
      pinholes_scaled = pinholes.clone()
      pinholes_scaled[..., :6] = pinholes[..., :6] * scale.unsqueeze(-1)
      return pinholes_scaled
  
imports: from typing import Iterable, List, Union
  import torch
  from kornia.core import Device, Tensor, eye, stack, zeros
  from kornia.core.check import KORNIA_CHECK_SAME_DEVICE
  from kornia.geometry.conversions import convert_points_from_homogeneous, convert_points_to_homogeneous
  from kornia.geometry.linalg import inverse_transformation, transform_points
  from kornia.utils.helpers import _torch_inverse_cast
label_desc: Use image node_id 3 for calling a global function with example usage: scale_pinhole(pinholes, scale) and returns: pinholes_scaled