code: def test_general_neg_sample_dataloader_in_point_wise(self):
      train_batch_size = 6
      eval_batch_size = 100
      config_dict = {
          "model": "DMF",
          "dataset": "general_dataloader",
          "data_path": current_path,
          "load_col": None,
          "train_neg_sample_args": {
              "distribution": "uniform",
              "sample_num": 1,
          },
          "eval_args": {
              "split": {"RS": [0.8, 0.1, 0.1]},
              "order": "TO",
              "mode": "full",
          },
          "train_batch_size": train_batch_size,
          "eval_batch_size": eval_batch_size,
          "shuffle": False,
      }
      train_data, valid_data, test_data = new_dataloader(
          config_dict=config_dict
      )
  
      train_data.shuffle = False
      train_item_list = list(range(1, 41))
      pr = 0
      for batch_data in train_data:
          step = len(batch_data) // 2
          batch_item_list = train_item_list[pr : pr + step]
          assert (
              batch_data["item_id"][:step].numpy() == batch_item_list
          ).all()
          assert (40 < batch_data["item_id"][step:]).all()
          assert (batch_data["item_id"][step:] <= 100).all()
          assert (batch_data["item_id"] == batch_data["price"]).all()
          pr += step
  
file_path: RecBole/tests/data/test_dataloader.py
imports: import logging
  import os
  import pytest
  from recbole.data.dataloader.general_dataloader import NegSampleEvalDataLoader, FullSortEvalDataLoader
  from recbole.config import Config
  from recbole.data import create_dataset, data_preparation
  from recbole.utils import init_seed
label_desc: Use image node_id 3 for calling the TestGeneralDataloader obj's underlying member method code with example usage: obj.test_general_neg_sample_dataloader_in_point_wise() without return types