code: def __init__(self, cfg: DictConfig, trainer: Trainer):
      if not HAVE_APEX:
          raise ImportError(
              "Apex was not found. Please see the NeMo README for installation instructions: https://github.com/NVIDIA/NeMo#megatron-gpt."
          )
      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."
          )
  
      # this prevents base constructor from initializing tokenizer
      self.tokenizer = None
      super().__init__(cfg, trainer=trainer)
  
      self._validate_trainer()
  
      # megatron_amp_O2 is not yet supported in diffusion models
      self.megatron_amp_O2 = cfg.get("megatron_amp_O2", False)
      self.model = self.model_provider_func()
  
      if self.trainer.precision in ["bf16", "bf16-mixed"]:
          self.autocast_dtype = torch.bfloat16
      elif self.trainer.precision in [32, "32", "32-true"]:
          self.autocast_dtype = torch.float
      elif self.trainer.precision in [16, "16", "16-mixed"]:
          self.autocast_dtype = torch.half
      else:
          raise ValueError(
              'precision must be in ["32-true", "16-mixed", "bf16-mixed"]'
          )
  
imports: from functools import partial
  from typing import Any, Optional
  import torch
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from torch._inductor import config
  from nemo.collections.multimodal.data.dreambooth.dreambooth_dataset import DreamBoothDataset
  from nemo.collections.multimodal.modules.stable_diffusion.distributions.distributions import DiagonalGaussianDistribution
  from nemo.collections.multimodal.parts.utils import randn_like
  from nemo.collections.nlp.data.language_modeling.megatron.data_samplers import MegatronPretrainingRandomSampler
  from nemo.collections.nlp.models.language_modeling.megatron_base_model import MegatronBaseModel
  from nemo.collections.nlp.modules.common.megatron.module import Float16Module
  from nemo.collections.nlp.parts.utils_funcs import get_last_rank
  from nemo.core.classes.common import Serialization
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new MegatronDreamBooth object from inherited base classes: MegatronBaseModel with example: obj = MegatronDreamBooth(cfg, trainer)