class_docstr: Transformation that merges linear layers that take the same input into one big linear layer.
class_docstr_tok: ["Transformation","that","merges","linear","layers","that","take","the","same","input","into","one","big","linear","layer","."]
code: def _get_bias(linear: torch.nn.Linear) -> torch.Tensor:
      if linear.bias is not None:
          return linear.bias
      return torch.zeros(
          linear.out_features, dtype=linear.weight.dtype
      ).to(linear.weight.device)
  
imports: import collections
  import copy
  import functools
  import itertools
  import operator
  import warnings
  from abc import ABC, abstractmethod
  from typing import TYPE_CHECKING, List
  import torch
  from transformers.file_utils import add_end_docstrings
  from transformers.utils.fx import _gen_constructor_wrapper
label_desc: Use image node_id 1 for calling the MergeLinears obj's underlying member method code with example usage: obj._get_bias(linear) and returns: torch, linear