code: def __init__(
      self,
      cfg,
      tokenizer,
      name,
      num_samples,
      seq_length,
      seed,
  ):
      if not HAVE_MEGATRON_CORE:
          raise ImportError(
              "Megatron core was not found. Please see the NeMo README for installation instructions: https://github.com/NVIDIA/NeMo#megatron-gpt."
          )
  
      super().__init__()
      self.name = name
      self.seq_length = seq_length
      self.vocab_size = tokenizer.vocab_size
      self.length = num_samples
      self.seed = seed
      self.get_attention_mask_from_fusion = cfg.get(
          "get_attention_mask_from_fusion", True
      )
  
      self.attention_mask = torch.tril(
          torch.ones((self.seq_length, self.seq_length))
      ).unsqueeze(0)
      self.attention_mask = self.attention_mask < 0.5
      self.loss_mask = torch.ones(self.seq_length, dtype=torch.float)
      self.position_ids = torch.arange(
          self.seq_length, dtype=torch.int64
      )
  
imports: import os
  import time
  import numpy
  import torch
  from omegaconf.dictconfig import DictConfig
  from nemo.collections.nlp.data.language_modeling.megatron.base_dataset_utils import get_datasets_weights_and_num_samples, get_train_valid_test_split_
  from nemo.collections.nlp.data.language_modeling.megatron.blendable_dataset import BlendableDataset
  from nemo.collections.nlp.data.language_modeling.megatron.indexed_dataset import deallocate_indexed_dataset_memory
  from nemo.collections.nlp.data.language_modeling.megatron.indexed_dataset import make_dataset
  from nemo.core import Dataset
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new MockGPTDataset object from inherited base classes: Dataset with example: obj = MockGPTDataset(cfg, tokenizer, name, num_samples, seq_length, seed)