notebooks/plot_utils.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2022 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

import os
import matplotlib.pyplot as plt


def plot_curves(history, checkpoint_dir):
    """
    Reads a pickle file and plots accuracy and loss curves

    :param history: Pickle file
    :return: None
    """
    if not history:
        raise FileNotFoundError("The pickle file {} does not exist".format(history))

    acc = history['acc']
    val_acc = history['val_acc']
    loss = history['loss']
    val_loss = history['val_loss']
    plt.figure(figsize=(7, 7))
    plt.subplot(2, 1, 1)
    plt.plot(acc, label='Training Accuracy')
    plt.plot(val_acc, label='Validation Accuracy')
    plt.legend(loc='lower right')
    plt.ylabel('Accuracy')
    plt.title('Training and Validation Accuracy')

    plt.subplot(2, 1, 2)
    plt.plot(loss, label='Training Loss')
    plt.plot(val_loss, label='Validation Loss')
    plt.legend(loc='upper right')
    plt.ylabel('Cross Entropy')
    plt.title('Training and Validation Loss')
    plt.xlabel('epoch')
    if not os.path.exists(os.path.join(checkpoint_dir, 'train_val_plot.png')):
        print("Saving plot in checkpoint_dir:", checkpoint_dir)
        plt.savefig(os.path.join(checkpoint_dir, 'train_val_plot.png'))