code: def __post_init__(self):
      # Check if train data path exists
      if not os.path.exists(self.train_data):
          raise ValueError(f"{self.train_data} does not exist.")
  
      # Check if train data path contains at least 2 folders
      subfolders = [
          f.path for f in os.scandir(self.train_data) if f.is_dir()
      ]
      # list subfolders
      logger.info(f"🚀 Subfolders: {subfolders}")
      if len(subfolders) < 2:
          raise ValueError(
              f"{self.train_data} should contain at least 2 subfolders."
          )
  
      # Check if each subfolder contains at least 5 image files in jpeg, png or jpg format only
      for subfolder in subfolders:
          image_files = [
              f
              for f in os.listdir(subfolder)
              if f.endswith(ALLOWED_EXTENSIONS)
          ]
          if len(image_files) < 5:
              raise ValueError(
                  f"{subfolder} should contain at least 5 jpeg, png or jpg files."
              )
          # Check if there are no other files except image files in the subfolder
          if len(image_files) != len(os.listdir(subfolder)):
              raise ValueError(
                  f"{subfolder} should not contain any other files except image files."
              )
  
          # Check if there are no subfolders inside subfolders
          subfolders_in_subfolder = [
              f.path for f in os.scandir(subfolder) if f.is_dir()
          ]
          if len(subfolders_in_subfolder) > 0:
              raise ValueError(
                  f"{subfolder} should not contain any subfolders."
              )
  
      if self.valid_data:
          # Check if valid data path exists
          if not os.path.exists(self.valid_data):
              raise ValueError(f"{self.valid_data} does not exist.")
  
          # Check if valid data path contains at least 2 folders
          subfolders = [
              f.path for f in os.scandir(self.valid_data) if f.is_dir()
          ]
  
          # make sure that the subfolders in train and valid data are the same
          train_subfolders = set(
              os.path.basename(f.path)
              for f in os.scandir(self.train_data)
              if f.is_dir()
          )
          valid_subfolders = set(
              os.path.basename(f.path)
              for f in os.scandir(self.valid_data)
              if f.is_dir()
          )
          if train_subfolders != valid_subfolders:
              raise ValueError(
                  f"{self.valid_data} should have the same subfolders as {self.train_data}."
              )
  
          if len(subfolders) < 2:
              raise ValueError(
                  f"{self.valid_data} should contain at least 2 subfolders."
              )
  
          # Check if each subfolder contains at least 5 image files in jpeg, png or jpg format only
          for subfolder in subfolders:
              image_files = [
                  f
                  for f in os.listdir(subfolder)
                  if f.endswith(ALLOWED_EXTENSIONS)
              ]
              if len(image_files) < 5:
                  raise ValueError(
                      f"{subfolder} should contain at least 5 jpeg, png or jpg files."
                  )
  
              # Check if there are no other files except image files in the subfolder
              if len(image_files) != len(os.listdir(subfolder)):
                  raise ValueError(
                      f"{subfolder} should not contain any other files except image files."
                  )
  
              # Check if there are no subfolders inside subfolders
              subfolders_in_subfolder = [
                  f.path for f in os.scandir(subfolder) if f.is_dir()
              ]
              if len(subfolders_in_subfolder) > 0:
                  raise ValueError(
                      f"{subfolder} should not contain any subfolders."
                  )
  
file_path: autotrain-advanced/src/autotrain/preprocessor/vision.py
imports: import os
  import shutil
  import uuid
  from dataclasses import dataclass
  from typing import Optional
  import pandas
  from datasets import load_dataset
  from sklearn.model_selection import train_test_split
  from autotrain import logger
label_desc: Use image node_id 1 for calling the ImageClassificationPreprocessor obj's underlying member method code with example usage: obj.__post_init__() without return types