code: def on_epoch_end(self, epoch, log):
      # log a value repeated which creates a list
      run.log("Loss", log["loss"])
      run.log("Accuracy", log["accuracy"])
  
file_path: MachineLearningNotebooks/how-to-use-azureml/work-with-data/datasets-tutorial/pipeline-with-datasets/keras-mnist-fashion/train.py
imports: from tensorflow.keras.models import Sequential
  from tensorflow.keras.layers import Dense, Dropout, Flatten
  from tensorflow.keras.layers import Conv2D, MaxPooling2D
  from tensorflow.keras.layers import BatchNormalization
  from tensorflow.keras.losses import categorical_crossentropy
  from tensorflow.keras.optimizers import Adam
  from tensorflow.keras.utils import to_categorical
  from tensorflow.keras.callbacks import Callback
  import numpy
  import pandas
  import os
  import matplotlib.pyplot
  from sklearn.model_selection import train_test_split
  from azureml.core import Run
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