code: def on_epoch_end(self, epoch, log):
      # log a value repeated which creates a list
      run.log("Loss", log["val_loss"])
      run.log("Accuracy", log["val_accuracy"])
  
file_path: MachineLearningNotebooks/how-to-use-azureml/ml-frameworks/keras/train-hyperparameter-tune-deploy-with-keras/keras_mnist.py
imports: import numpy
  import argparse
  import os
  import glob
  import matplotlib.pyplot
  import keras
  from keras.models import Sequential, model_from_json
  from keras.layers import Dense
  from keras.optimizers import RMSprop
  from keras.callbacks import Callback
  import tensorflow
  from azureml.core import Run
  from utils import load_data, one_hot_encode
label_desc: Use image node_id 1 for calling the LogRunMetrics obj's underlying member method code with example usage: obj.on_epoch_end(epoch, log) without return types