code: def clamp_values(vector: Tensor) -> Tensor:
      """Clamp the values of a vector to the range [-MAX_CLAMP_VALUE,
      MAX_CLAMP_VALUE].
  
      Args:
          vector (Tensor): Tensor of shape (N, C, H, W).
  
      Returns:
          Tensor: A Tensor of shape (N, C, H, W) with clamped values.
      """
      vector = torch.clamp(
          vector, min=-MAX_CLAMP_VALUE, max=MAX_CLAMP_VALUE
      )
      return vector
  
imports: import math
  from typing import Dict, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from mmcv.cnn.bricks import DropPath
  from torch import Tensor
label_desc: Use image node_id 2 for calling a global function with example usage: clamp_values(vector) and returns: vector