code: def nchw_to_nlc(x):
      """Flatten [N, C, H, W] shape tensor to [N, L, C] shape tensor.
  
      Args:
          x (Tensor): The input tensor of shape [N, C, H, W] before conversion.
  
      Returns:
          Tensor: The output tensor of shape [N, L, C] after conversion.
      """
      assert len(x.shape) == 4
      return x.flatten(2).transpose(1, 2).contiguous()
  
imports: import math
  import warnings
  from typing import Optional, Sequence, Tuple, Union
  import torch
  import torch.nn.functional
  from mmcv.cnn import Linear, build_activation_layer, build_conv_layer, build_norm_layer
  from mmcv.cnn.bricks.drop import Dropout
  from mmengine.model import BaseModule, ModuleList
  from mmengine.utils import to_2tuple
  from torch import Tensor, nn
  from mmdet.registry import MODELS
  from mmdet.utils import OptConfigType, OptMultiConfig
label_desc: Use image node_id 2 for calling a global function with example usage: nchw_to_nlc(x) and returns: x