class_docstr: Standard heads for FPN-based models
  
  Arguments:
      in_channels (int): number of input channels
      representation_size (int): size of the intermediate representation
class_docstr_tok: ["Standard","heads","for","FPN-based","models","Arguments",":","in_channels","(","int",")",":","number","of","input","channels","representation_size","(","int",")",":","size","of","the","intermediate","representation"]
code: def forward(self, x):
      x = x.flatten(start_dim=1)
  
      x = F.relu(self.fc6(x))
      x = F.relu(self.fc7(x))
  
      return x
  
imports: import warnings
  from collections import OrderedDict
  from typing import Tuple, List, Dict, Optional, Union
  import torch
  from torch import nn, Tensor
  import torch.nn.functional
  from torchvision.ops import MultiScaleRoIAlign
  from .roi_head import RoIHeads
  from .transform import GeneralizedRCNNTransform
  from .rpn_function import AnchorsGenerator, RPNHead, RegionProposalNetwork
label_desc: Use image node_id 2 for calling the TwoMLPHead obj's underlying member method code with example usage: obj.forward(x) and returns: x