code: def get_linear_layer(
      rows, columns, init_method, perform_initialization=True
  ):
      """Simple linear layer with weight initialization."""
      layer = torch.nn.Linear(rows, columns)
      if perform_initialization:  # Take from modelparallel config
          init_method(layer.weight)
      with torch.no_grad():
          layer.bias.zero_()
      return layer
  
file_path: megatron-lm/megatron/core/transformer/utils.py
imports: from operator import itemgetter
  from typing import Any, Dict, Iterable, Optional, Tuple, Union
  import torch
  from megatron.core import parallel_state
  from megatron.core.dist_checkpointing.mapping import ShardedObject, StateDict
  from megatron.core.utils import make_sharded_tensor_for_checkpoint, make_tp_sharded_tensor_for_checkpoint
label_desc: Use image node_id 1 for calling a global function with example usage: get_linear_layer(rows, columns, init_method, perform_initialization) and returns: layer