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#!/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'))
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