gistfile1.txt

model = base_model()

# Iterate over epochs
epochs = 10
epochs_val_losses, epochs_train_losses = [], []
for epoch in range(epochs):
    print('Start of epoch %d' % (epoch,))
    
    #Perform training using gradient tape
    losses_train = train_data_for_one_epoch()
    train_acc = train_acc_metric.result()
    
    #Perform validation
    losses_val = perform_validation()
    val_acc = val_acc_metric.result()
    
    #Compute mean training and validation loss in the epoch 
    losses_train_mean = np.mean(losses_train)
    losses_val_mean = np.mean(losses_val)
    epochs_val_losses.append(losses_val_mean)
    epochs_train_losses.append(losses_train_mean)

    print('\n Epoch %s: Train loss: %.4f  Validation Loss: %.4f, Train Accuracy: %.4f, Validation Accuracy %.4f' % (epoch, float(losses_train_mean), float(losses_val_mean), float(train_acc), float(val_acc)))
  
    train_acc_metric.reset_states()
    val_acc_metric.reset_states()