code: def SwiGLU(x):
      """Gated linear unit activation function.
      Args:
          x : input array
          axis: the axis along which the split should be computed (default: -1)
      """
      size = x.shape[-1]
      assert size % 2 == 0, "axis size must be divisible by 2"
      x1, x2 = torch.split(x, size // 2, -1)
      return x1 * (x2 * torch.sigmoid(x2))
  
imports: import contextlib
  import os
  from typing import Any, Callable, Dict, List, Optional, Tuple
  import torch
  import torch.distributed
  import torch.nn
  import torch.nn.functional
  from colossalai.moe.manager import MOE_MANAGER
  from colossalai.tensor.moe_tensor.api import get_dp_group, get_dp_group_ranks, get_ep_size, is_moe_tensor
  from colossalai.utils import get_current_device
label_desc: Use image node_id 4 for calling a global function with example usage: SwiGLU(x) and returns: unknown