code: def from_pretrained(
      cls,
      cfg: ImagenPipelineConfig,
      trainer=None,
      device="cuda",
      megatron_loading=False,
      megatron_cfg=None,
  ):
      target_resolution = cfg.target_resolution
      assert target_resolution in [64, 256, 1024]
  
      # Set encoder_path which will be used when inst the model
      if cfg.encoder_path is not None:
          os.environ["ENCODER_PATH"] = cfg.encoder_path
  
      assert cfg.model_name is None, "No predefined model for now"
      assert (
          cfg.customized_model is not None
      ), "Need to provide customized models for inference"
      models = ImagenPipeline._load_customized_model(
          cfg, trainer, megatron_loading, megatron_cfg
      )
      assert len(models) >= 1, "Need to load at least one model"
      if cfg.inference_precision == "16":
          print("Running Inference in FP16.")
          print("Converting all difussion models to FP16..")
          for model in models:
              model.half()
  
      print("Loading text encoder")
      text_encoder = models[0].get_text_encoder(
          encoder_path=cfg.encoder_path
      )
      if cfg.inference_precision == "16":
          print("Converting text encoders to FP16..")
          text_encoder.half()
      return ImagenPipeline(
          models=models,
          text_encoder=text_encoder,
          cfg=cfg,
          device=device,
      )
  
imports: import os
  import time
  from dataclasses import dataclass, field
  from typing import Callable, List, Optional, Union
  import torch
  from omegaconf.omegaconf import OmegaConf
  from pytorch_lightning import Trainer
  from torch.cuda.amp import autocast
  from nemo.collections.multimodal.models.text_to_image.imagen.imagen import Imagen, MegatronImagen
  from nemo.collections.multimodal.parts.utils import numpy_to_pil, setup_trainer_and_models_for_inference
label_desc: Use image node_id 4 for calling the ImagenPipeline obj's underlying member method code with example usage: obj.from_pretrained(cls, cfg, trainer, device, megatron_loading, megatron_cfg) and returns: ImagenPipeline