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()
  
      self.conditioning_keys = []
  
      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 typing import Any
  import einops
  import torch
  import torch.nn
  from einops import rearrange, repeat
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from pytorch_lightning.utilities.rank_zero import rank_zero_only
  from torch._inductor import config
  from nemo.collections.multimodal.data.controlnet.controlnet_dataset import build_train_valid_datasets
  from nemo.collections.multimodal.models.text_to_image.stable_diffusion.ldm.ddpm import LatentDiffusion
  from nemo.collections.multimodal.models.text_to_image.stable_diffusion.samplers.ddim import DDIMSampler
  from nemo.collections.multimodal.modules.stable_diffusion.attention import SpatialTransformer
  from nemo.collections.multimodal.modules.stable_diffusion.diffusionmodules.openaimodel import AttentionBlock, Downsample, ResBlock, TimestepEmbedSequential, UNetModel
  from nemo.collections.multimodal.modules.stable_diffusion.diffusionmodules.util import conv_nd, linear, timestep_embedding, zero_module
  from nemo.collections.multimodal.parts.stable_diffusion.utils import exists, log_txt_as_img
  from nemo.collections.nlp.models.language_modeling.megatron_base_model import MegatronBaseModel
  from nemo.collections.nlp.modules.common.megatron.module import Float16Module
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new MegatronControlNet object from inherited base classes: MegatronBaseModel with example: obj = MegatronControlNet(cfg, trainer)