code: def __init__(self, path: Path = Path("/opt/ml")) -> None:
      self.path = TrainPaths(path)
      self.inputdataconfig = self._load_inputdataconfig()
      self.channels = self._load_channels()
      self.current_host = self._get_current_host()
  
      hyperparameters, env = self._load_hyperparameters()
      self.hyperparameters = hyperparameters
      self.env = env
  
imports: import json
  import shutil
  from pathlib import Path
  from typing import Dict, Optional, Tuple
  from gluonts.pydantic import BaseModel
  from .dyn import install_and_restart
  from .params import decode_sagemaker_parameters
  from .nested_params import decode_nested_parameters
label_desc: Use image node_id 1 to create a new TrainEnv object  with example: obj = TrainEnv(path)