code: def forward(self, x):
      reduce_x = self.conv_reduce(x)
      attention = self.attention(reduce_x)
      n, c, h, w = attention.size()
      attention = attention.view(n, c, -1)
      reduce_x = reduce_x.view(n, self.reduced_channels, -1)
      fm = torch.bmm(reduce_x, torch.softmax(attention, dim=1))
      fm = fm.view(n, self.reduced_channels, h, w)
  
      return fm
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from pywick.models.segmentation.da_basenets.basic import _ConvBNReLU
  from pywick.models.segmentation.da_basenets.segbase import SegBaseModel
  from pywick.models.segmentation.da_basenets.fcn import _FCNHead
label_desc: Use image node_id 2 for calling the _AttentionGeneration obj's underlying member method code with example usage: obj.forward(x) and returns: fm