class_docstr: Implementation of the OCR module:
  We aggregate the global object representation to update the representation for each pixel.
code: def forward(self, feats, proxy_feats):
      context = self.object_context_block(feats, proxy_feats)
  
      output = self.conv_bn_dropout(torch.cat([context, feats], 1))
  
      return output
  
imports: import os
  import logging
  import numpy
  import torch
  import torch.nn
  import torch._utils
  import torch.nn.functional
  from .bn_helper import BatchNorm2d, BatchNorm2d_class, relu_inplace
label_desc: Use image node_id 2 for calling the SpatialOCR_Module obj's underlying member method code with example usage: obj.forward(feats, proxy_feats) and returns: output