docstr: Merges attn_head_size dim and num_attn_heads dim into hidden_size
docstr_tok: ["Merges","attn_head_size","dim","and","num_attn_heads","dim","into","hidden_size"]
code: def _merge_heads(self, tensor, num_heads, attn_head_size):
      """
      Merges attn_head_size dim and num_attn_heads dim into hidden_size
      """
      tensor = tensor.permute(0, 2, 1, 3).contiguous()
      new_shape = tensor.size()[:-2] + (num_heads * attn_head_size,)
      return tensor.view(new_shape)
  
imports: from dataclasses import dataclass
  from typing import Optional, Tuple
  from .configuration_gpt2 import GPT2Config
  from fastNLP.transformers.torch.activations import ACT2FN
  from fastNLP.transformers.torch.file_utils import ModelOutput, add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, replace_return_docstrings
  from fastNLP.transformers.torch.modeling_outputs import BaseModelOutputWithPastAndCrossAttentions, CausalLMOutputWithCrossAttentions, SequenceClassifierOutputWithPast, TokenClassifierOutput
  from fastNLP.transformers.torch.modeling_utils import Conv1D, PreTrainedModel, SequenceSummary, find_pruneable_heads_and_indices, prune_conv1d_layer
  from fastNLP.transformers.torch.utils.model_parallel_utils import assert_device_map, get_device_map
  from fastNLP.envs.imports import _NEED_IMPORT_TORCH
  from fastNLP.core.log import logger
label_desc: Use image node_id 5 for calling the GPT2Attention obj's underlying member method code with example usage: obj._merge_heads(tensor, num_heads, attn_head_size) and returns: tensor