code: def _get_embed_positions(self, position_ids):
      embed_positions = self.embed_positions
      if embed_positions.device != position_ids.device:
          embed_positions = embed_positions.to(position_ids.device)
          self.embed_positions = embed_positions
      return embed_positions.repeat(position_ids.shape[0], 1, 1)
  
imports: import warnings
  from typing import Optional, Tuple, Union
  import torch
  import torch.fx
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
  from ...activations import ACT2FN
  from ...modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast, QuestionAnsweringModelOutput, SequenceClassifierOutputWithPast
  from ...modeling_utils import PreTrainedModel
  from ...utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, is_torch_fx_proxy, logging
  from ...utils.model_parallel_utils import assert_device_map, get_device_map
  from .configuration_gptj import GPTJConfig
label_desc: Use image node_id 5 for calling the GPTJAttention obj's underlying member method code with example usage: obj._get_embed_positions(position_ids) and returns: embed_positions