code: def forward(self, x, encoder_out, mask=None):
      upsample_x = self.upconv(x)
      x_cat_encoder = torch.cat([encoder_out, upsample_x], dim=1)
      if self.attention is not None:
          x_cat_encoder = self.attention(x_cat_encoder, mask)
      return self.convs(x_cat_encoder)
  
imports: import torch
  from torch import nn
  from functools import partial
  from .basic_blocks import ConvBlock
  from ..ops import FeaturesConnector
label_desc: Use image node_id 2 for calling the UNetUpBlock obj's underlying member method code with example usage: obj.forward(x, encoder_out, mask) and returns: self