code: def _generate_fancy_data_labels(self, sequence_len, batch_size):
      temps = list()
      for i in range(batch_size):
          if self.inds is None or self.data_idx >= len(self.inds):
              # hack as use of RNG will fall out of sync due to pipelines being different
              model_parallel_cuda_manual_seed(self.MANUAL_SEED)
              self.inds = torch.randperm(
                  effective_length, device="cuda"
              )
              self.MANUAL_SEED += 1
              self.data_idx = 0
          data_idx_ = self.data_idx
          offset = self.inds[data_idx_]
          self.data_idx += 1
          curr = (
              fancy_data[offset : offset + sequence_len + 1]
              .clone()
              .detach()
          )
          temps.append(curr)
      temp = torch.stack(temps, dim=0).cuda()
      return temp
  
imports: from functools import partial
  from typing import List
  import time
  import torch
  import unittest
  from apex.transformer._ucc_util import HAS_UCC
  from apex.transformer import parallel_state
  from apex.transformer.enums import ModelType
  from apex.transformer.tensor_parallel import model_parallel_cuda_manual_seed
  from apex.transformer.pipeline_parallel.utils import average_losses_across_data_parallel_group, unwrap_model, setup_microbatch_calculator, get_ltor_masks_and_position_ids
  from apex.transformer.pipeline_parallel.schedules.common import _get_params_for_weight_decay_optimization, build_model
  from apex.transformer.pipeline_parallel.schedules.fwd_bwd_pipelining_without_interleaving import forward_backward_pipelining_without_interleaving
  from apex.transformer.testing.standalone_gpt import gpt_model_provider
  from apex.transformer.testing import global_vars
  from apex.transformer.testing.distributed_test_base import UccDistributedTestBase, NcclDistributedTestBase
  from torch.testing._internal import common_utils
  from torch.testing._internal.common_device_type import instantiate_device_type_tests
label_desc: Use image node_id 2 for calling the GptTestBase obj's underlying member method code with example usage: obj._generate_fancy_data_labels(sequence_len, batch_size) and returns: temp