code: def reset_bias_(
      bias: Optional[Tensor],
      in_channels: int,
      initializer: Optional[str] = None,
  ) -> Optional[Tensor]:
      if bias is None or in_channels <= 0:
          pass
      elif initializer == "zeros":
          inits.zeros(bias)
      elif initializer is None:
          inits.uniform(in_channels, bias)
      else:
          raise RuntimeError(
              f"Bias initializer '{initializer}' not supported"
          )
  
      return bias
  
imports: import copy
  import math
  from typing import Any, Dict, Optional, Union
  import torch
  import torch.nn.functional
  from torch import Tensor
  from torch.nn.parameter import Parameter
  import torch_geometric.backend
  import torch_geometric.typing
  from torch_geometric import is_compiling
  from torch_geometric.nn import inits
  from torch_geometric.typing import pyg_lib
  from torch_geometric.utils import index_sort, scatter
  from torch_geometric.utils.sparse import index2ptr
label_desc: Use image node_id 3 for calling a global function with example usage: reset_bias_(bias, in_channels, initializer) and returns: bias