code: def test_set_input_tensor(self):
      config: TransformerConfig = self.bert_model.config
      sequence_length = self.bert_model.max_sequence_length
      micro_batch_size = 2
  
      # [sequence length, batch size, hidden size]
      input_tensor = torch.ones(
          (sequence_length, micro_batch_size, config.hidden_size)
      )
  
      self.bert_model.set_input_tensor(input_tensor)
  
      assert (
          self.bert_model.encoder.input_tensor.shape[0]
          == sequence_length
      )
      assert (
          self.bert_model.encoder.input_tensor.shape[1]
          == micro_batch_size
      )
      assert (
          self.bert_model.encoder.input_tensor.shape[2]
          == config.hidden_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 4 for calling the TestBertModel obj's underlying member method code with example usage: obj.test_set_input_tensor() without return types