class_docstr: Megatron encoder-decoder base class
class_docstr_tok: ["Megatron","encoder-decoder","base","class"]
docstr: Micro batch returned by MegatronT5 dataloader
docstr_tok: ["Micro","batch","returned","by","MegatronT5","dataloader"]
code: def process_micro_batch(self, micro_batch):
      """Micro batch returned by MegatronT5 dataloader"""
  
      data_b = micro_batch
  
      # Unpack.
      tokens_enc = data_b["text_enc"].long()
      tokens_dec = data_b["text_dec"].long()
      labels = data_b["labels"].long()
      loss_mask = data_b["loss_mask"].float()
  
      enc_mask = data_b["enc_mask"]
      dec_mask = data_b["dec_mask"]
  
      return (
          tokens_enc,
          tokens_dec,
          loss_mask,
          labels,
          enc_mask,
          dec_mask,
      )
  
imports: import copy
  import functools
  import inspect
  from typing import Any, Dict, List, Optional
  import torch
  from omegaconf import OmegaConf, open_dict
  from omegaconf.dictconfig import DictConfig
  from pytorch_lightning.accelerators import CPUAccelerator
  from pytorch_lightning.trainer.trainer import Trainer
  from nemo.collections.nlp.data.language_modeling.megatron.data_samplers import MegatronPretrainingRandomSampler, MegatronPretrainingSampler
  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.token_level_encoder_decoder import MegatronTokenLevelEncoderDecoderModule
  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.modules.common.text_generation_utils import compute_beam_search_len_penalty, get_sampling_token_fn
  from nemo.collections.nlp.parts.utils_funcs import get_last_rank
  from nemo.utils import AppState, logging
label_desc: Use image node_id 29 for calling the MegatronLMEncoderDecoderModel obj's underlying member method code with example usage: obj.process_micro_batch(micro_batch) and returns: tokens_enc,  tokens_dec,  loss_mask,  labels,  enc_mask,  dec_mask