class_docstr: FaceStylizer for building face stylization model.
  
  Attributes:
    w_avg: An average face latent code to regularize face generation in face
      stylization.
docstr: Creates and trains the face stylizer model.
  
  Args:
    train_data: Training data.
docstr_tok: ["Creates","and","trains","the","face","stylizer","model",".","Args",":","train_data",":","Training","data","."]
code: def _create_and_train_model(
      self, train_data: classification_ds.ClassificationDataset
  ):
      """Creates and trains the face stylizer model.
  
      Args:
        train_data: Training data.
      """
      self._create_model()
      self._train_model(
          train_data=train_data, preprocessor=self._preprocessor
      )
  
imports: import logging
  import os
  from typing import Any, Callable, Optional
  import zipfile
  import numpy
  import tensorflow
  from mediapipe.model_maker.python.core.data import classification_dataset
  from mediapipe.model_maker.python.core.utils import loss_functions
  from mediapipe.model_maker.python.core.utils import model_util
  from mediapipe.model_maker.python.vision.core import image_preprocessing
  from mediapipe.model_maker.python.vision.face_stylizer import constants
  from mediapipe.model_maker.python.vision.face_stylizer import face_stylizer_options
  from mediapipe.model_maker.python.vision.face_stylizer import hyperparameters
  from mediapipe.model_maker.python.vision.face_stylizer import model_options
  from mediapipe.model_maker.python.vision.face_stylizer import model_spec
  from mediapipe.tasks.python.metadata.metadata_writers import face_stylizer
label_desc: Use image node_id 4 for calling the FaceStylizer obj's underlying member method code with example usage: obj._create_and_train_model(train_data) without return types