code: def permute_and_flatten(
      layer: Tensor, N: int, A: int, C: int, H: int, W: int
  ) -> Tensor:
      layer = layer.view(N, -1, C, H, W)
      layer = layer.permute(0, 3, 4, 1, 2)
      layer = layer.reshape(N, -1, C)
      return layer
  
imports: from typing import Dict, List, Optional, Tuple
  import torch
  from torch import nn, Tensor
  from torch.nn import functional
  from torchvision.ops import boxes, Conv2dNormActivation
  from .None import _utils
  from .anchor_utils import AnchorGenerator
  from .image_list import ImageList
label_desc: Use image node_id 1 for calling a global function with example usage: permute_and_flatten(layer, N, A, C, H, W) and returns: layer