code: def test_init_prompt_learning_dataset(self):
      tokenizer = get_nmt_tokenizer(
          library="megatron", model_name="GPT2BPETokenizer"
      )
      task_templates = get_task_templates()
      dataset_path = create_temp_dataset()
  
      # Setup virtual token place holders
      total_virtual_tokens = 10
      pseudo_tokens = get_pseudo_tokens(total_virtual_tokens)
      tokenizer.add_special_tokens(
          {"additional_special_tokens": pseudo_tokens}
      )
  
      dataset = get_prompt_tuning_dataset(
          dataset_path,
          tokenizer,
          VirtualPromptSource.PROMPT_ENCODER,
          task_templates,
          pseudo_tokens,
      )
  
      print(type(dataset))
  
      assert isinstance(dataset, Dataset)
  
      os.remove(dataset_path)
  
file_path: NeMo/tests/collections/nlp/test_prompt_learning.py
imports: import json
  import os
  import pytest
  import torch
  from nemo.collections.nlp.data.language_modeling.megatron.gpt_prompt_learning_dataset import GPTPromptLearningDataset
  from nemo.collections.nlp.models.language_modeling.megatron_gpt_prompt_learning_model import get_pseudo_tokens
  from nemo.collections.nlp.modules.common import VirtualPromptSource
  from nemo.collections.nlp.modules.common.tokenizer_utils import get_nmt_tokenizer
  from nemo.core import Dataset
label_desc: Use image node_id 1 for calling the TestMegatronGPTPromptLearningDataset obj's underlying member method code with example usage: obj.test_init_prompt_learning_dataset() without return types