class_docstr: This class is used for saving the validation loss and the training loss per epoch.
docstr: Initialise the lists where the loss of training and validation will be saved.
code: def on_train_begin(self, logs={}):
      """Initialise the lists where the loss of training and validation will be saved."""
      self.losses = []
      self.val_losses = []
  
imports: import numpy
  import matplotlib.pyplot
  import seaborn
  import tensorflow
  from tensorflow.keras.layers import *
  from tensorflow.keras.models import Model
  from tensorflow.keras.losses import binary_crossentropy
  from tensorflow.keras import backend
  from tensorflow.keras.callbacks import ReduceLROnPlateau, Callback
  from recommenders.evaluation.python_evaluation import ndcg_at_k
label_desc: Use image node_id 1 for calling the LossHistory obj's underlying member method code with example usage: obj.on_train_begin(logs) without return types