class_docstr: Megatron Bert pretraining.
  Model returns [batch, seq, hidden] shape
class_docstr_tok: ["Megatron","Bert","pretraining",".","Model","returns","[","batch",",","seq",",","hidden","]","shape"]
docstr: PTL hook: https://pytorch-lightning.readthedocs.io/en/latest/common/lightning_module.html#transfer-batch-to-device
  When using pipeline parallelism, we need the global batch to remain on the CPU,
  since the memory overhead will be too high when using a large number of microbatches.
  Microbatches are transferred from CPU to GPU inside the pipeline.
code: def transfer_batch_to_device(
      self, batch: Any, device: torch.device, dataloader_idx: int
  ) -> Any:
      """PTL hook: https://pytorch-lightning.readthedocs.io/en/latest/common/lightning_module.html#transfer-batch-to-device
      When using pipeline parallelism, we need the global batch to remain on the CPU,
      since the memory overhead will be too high when using a large number of microbatches.
      Microbatches are transferred from CPU to GPU inside the pipeline.
      """
      return batch
  
imports: import itertools
  from typing import Any, Dict, List, Optional
  import torch
  import torch.nn.functional
  from omegaconf.dictconfig import DictConfig
  from pytorch_lightning.trainer.trainer import Trainer
  from nemo.collections.nlp.data.language_modeling.megatron import dataset_utils
  from nemo.collections.nlp.data.language_modeling.megatron.data_samplers import MegatronPretrainingRandomSampler, MegatronPretrainingSampler
  from nemo.collections.nlp.models.language_modeling.megatron.bert_model import BertModel
  from nemo.collections.nlp.models.language_modeling.megatron_base_model import MegatronBaseModel
  from nemo.collections.nlp.modules.common.megatron.build_model import build_model
  from nemo.collections.nlp.modules.common.megatron.module import Float16Module
  from nemo.collections.nlp.modules.common.megatron.utils import ApexGuardDefaults, average_losses_across_data_parallel_group, get_params_for_weight_decay_optimization
  from nemo.collections.nlp.parts.nlp_overrides import GradScaler
  from nemo.collections.nlp.parts.utils_funcs import get_last_rank
  from nemo.core.classes.common import PretrainedModelInfo
  from nemo.core.neural_types import ChannelType, MaskType, NeuralType
  from nemo.utils import AppState, logging
label_desc: Use image node_id 26 for calling the MegatronBertModel obj's underlying member method code with example usage: obj.transfer_batch_to_device(batch, device, dataloader_idx) and returns: batch