code: def flatten_to_single_vector(tensor):
      """Collapse the C x H x W values per representation into a single long vector.
  
      Reshape a tensor of size (N, C, H, W) into (N, C * H * W).
  
      Args:
          tensor (torch.tensor): batch of data.
  
      Returns:
          torch.Tensor: Reshaped view of that data (analogous to numpy.reshape)
  
      """
      N = tensor.shape[0]  # read in N, C, H, W
      return tensor.view(N, -1)
  
imports: import copy
  import math
  import warnings
  import torch
  from torch import nn
  import torch.nn.functional
label_desc: Use image node_id 10 for calling a global function with example usage: flatten_to_single_vector(tensor) and returns: tensor