class_docstr: The base trainer class. Given an object of `hparams`, a trainer
  creates and initializes a model. After initialization, the method
  `model_train` can be used to train the model.
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code: def _init_model(self):
      flags = self.hparams.__dict__
      # Define TF model graph
      model = make_model(input_shape=self.input_shape, **flags)
      model.set_device(None)
      self.model = model
  
imports: from collections import OrderedDict
  import logging
  import math
  import time
  import os
  import numpy
  import six
  import tensorflow
  from cleverhans.utils_tf import batch_indices
  from cleverhans.utils_mnist import data_mnist
  import utils_cifar
  import utils_svhn
  from utils import preprocess_batch
  from make_model import make_model
  from evaluator import Evaluator
  from evaluator import create_adv_by_name
  from model import clone_variable
label_desc: Use image node_id 5 for calling the TrainManager obj's underlying member method code with example usage: obj._init_model() without return types