code: def create_temp_dataset():
      example_dataset_a = [
          {
              "taskname": "task name A",
              "text": "Test sentence one, Answer: ",
              "answer": "test",
          }
          for i in range(24)
      ]
      example_dataset_b = [
          {
              "taskname": "task name B",
              "question": "This is a question",
              "answer": "test",
          }
          for i in range(13)
      ]
      example_dataset = example_dataset_a + example_dataset_b
      temp_file_name = "temp_dataset_file.jsonl"
  
      with open(temp_file_name, "w") as temp:
          for example in example_dataset:
              temp.write(json.dumps(example) + "\n")
  
      return temp_file_name
  
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 2 for calling a global function with example usage: create_temp_dataset() and returns: temp_file_name