code: def test_post_process_forward(self):
      config: TransformerConfig = self.bert_model.config
      sequence_length = self.bert_model.max_sequence_length
      micro_batch_size = 2
  
      self.bert_model.cuda()
  
      data = list(range(sequence_length))
      input_ids = (
          torch.tensor(data, dtype=torch.int64)
          .repeat((micro_batch_size, 1))
          .cuda()
      )
      position_ids = (
          torch.tensor(data, dtype=torch.int64)
          .repeat((micro_batch_size, 1))
          .cuda()
      )
      attention_mask = torch.ones(
          (micro_batch_size, sequence_length), dtype=bool
      ).cuda()
  
      logits = self.bert_model.forward(
          input_ids=input_ids, attention_mask=attention_mask
      )
  
      assert logits[0].shape[0] == micro_batch_size
      assert logits[0].shape[1] == sequence_length
      assert logits[0].shape[2] == self.bert_model.vocab_size
  
file_path: megatron-lm/tests/unit_tests/models/test_bert_model.py
imports: import pytest
  import torch
  from megatron.core.transformer.transformer_config import TransformerConfig
  from megatron.core.models.bert.bert_model import BertModel
  from tests.unit_tests.test_utilities import Utils
  from megatron.core.tensor_parallel.random import model_parallel_cuda_manual_seed
  from megatron.core.models.bert.bert_layer_specs import bert_layer_with_transformer_engine_spec
label_desc: Use image node_id 5 for calling the TestBertModel obj's underlying member method code with example usage: obj.test_post_process_forward() without return types