code: def __init__(
      self,
      in_channels,
      dim=256,
      num_convs=4,
      kernel_dim=128,
      act_cfg=dict(type="ReLU", inplace=True),
  ):
      super().__init__()
      self.mask_convs = _make_stack_3x3_convs(
          num_convs, in_channels, dim, act_cfg
      )
      self.projection = nn.Conv2d(dim, kernel_dim, kernel_size=1)
      self._init_weights()
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from mmengine.model.weight_init import caffe2_xavier_init, kaiming_init
  from torch.nn import init
  from mmdet.registry import MODELS
label_desc: Use image node_id 1 to create a new MaskBranch object from inherited base classes: nn with example: obj = MaskBranch(in_channels, dim, num_convs, kernel_dim, act_cfg)