code: def get_prompt_tuning_dataset(
      dataset_path,
      tokenizer,
      virtual_prompt_source,
      task_templates,
      pseudo_tokens,
  ):
      dataset = GPTPromptLearningDataset(
          data=[dataset_path],
          tokenizer=tokenizer,
          virtual_prompt_source=virtual_prompt_source,
          task_templates=task_templates,
          pseudo_tokens=pseudo_tokens,
          pad_token_id=tokenizer.unk_id,
          max_seq_length=512,
          min_seq_length=1,
      )
  
      return dataset
  
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 a global function with example usage: get_prompt_tuning_dataset(dataset_path, tokenizer, virtual_prompt_source, task_templates, pseudo_tokens) and returns: dataset