code: def rotate_every_two(x):
      x1 = x[:, :, :, ::2]
      x2 = x[:, :, :, 1::2]
      x = torch.stack((-x2, x1), axis=-1)
      return x.flatten(-2)
  
imports: from typing import Tuple
  import numpy
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import CrossEntropyLoss
  from transformers.activations import ACT2FN
  from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast
  from transformers.modeling_utils import PreTrainedModel
  from transformers.utils import logging
  from transformers.utils.model_parallel_utils import assert_device_map, get_device_map
  from .configuration_codegen import CodeGenConfig
label_desc: Use image node_id 2 for calling a global function with example usage: rotate_every_two(x) and returns: x