code: def _to_torch_data_type(precision):
      if precision in ["bf16", "bf16-mixed"]:
          return torch.bfloat16
      elif precision in [16, "16", "16-mixed"]:
          return torch.float16
      elif precision in [32, "32", "32-true"]:
          return torch.float32
      else:
          raise ValueError(f"Cannot recognize precision {precision}")
  
imports: import random
  import numpy
  import torch
  from PIL import Image, ImageFilter, ImageOps
  from torch.utils.data import Dataset
  from nemo.collections.multimodal.data.common.data_samplers import SharedEpoch
  from nemo.collections.vision.data.megatron.autoaugment import ImageNetPolicy
  from nemo.collections.vision.data.megatron.image_folder import ImageFolder
label_desc: Use image node_id 1 for calling a global function with example usage: _to_torch_data_type(precision) and returns: torch, torch, torch