code: def transpose_for_scores(self, x: torch.Tensor) -> torch.Tensor:
      new_x_shape = x.size()[:-1] + (
          self.num_attention_heads,
          self.attention_head_size,
      )
      x = x.view(new_x_shape)
      return x.permute(0, 2, 1, 3)
  
imports: import math
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn, tensor
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
  from ...activations import ACT2FN
  from ...modeling_outputs import BaseModelOutputWithPastAndCrossAttentions, BaseModelOutputWithPoolingAndCrossAttentions, MultipleChoiceModelOutput, QuestionAnsweringModelOutput, SequenceClassifierOutput, TokenClassifierOutput
  from ...modeling_utils import PreTrainedModel
  from ...pytorch_utils import find_pruneable_heads_and_indices, prune_linear_layer
  from ...utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, logging
  from .configuration_ernie_m import ErnieMConfig
label_desc: Use image node_id 2 for calling the ErnieMSelfAttention obj's underlying member method code with example usage: obj.transpose_for_scores(x) and returns: x