code: def forward(self, x):
      for conv in self.convs:
          x = conv(x)
      if self.upsample is not None:
          x = self.upsample(x)
          if self.upsample_method == "deconv":
              x = self.relu(x)
      mask_pred = self.conv_logits(x)
      return mask_pred
  
file_path: insightface/detection/scrfd/mmdet/models/roi_heads/mask_heads/fcn_mask_head.py
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import Conv2d, ConvModule, build_upsample_layer
  from mmcv.ops.carafe import CARAFEPack
  from mmcv.runner import auto_fp16, force_fp32
  from torch.nn.modules.utils import _pair
  from mmdet.core import mask_target
  from mmdet.models.builder import HEADS, build_loss
label_desc: Use image node_id 3 for calling the FCNMaskHead obj's underlying member method code with example usage: obj.forward(x) and returns: mask_pred