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This commit is contained in:
Jakub Zaręba 2023-05-10 21:13:53 +02:00
parent d1d20f6968
commit e089fb1453
2 changed files with 39 additions and 56 deletions
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31
evaluate.py
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@ -1,18 +1,3 @@
from sacred import Experiment
from sacred.observers import MongoObserver, FileStorageObserver
ex = Experiment('s487187-evaluate', interactive=True)
ex.observers.append(MongoObserver(url='mongodb://admin:IUM_2021@172.17.0.1:27017', db_name='sacred'))
@ex.config
def my_config():
model_path = 'model.h5'
test_data_path = 'data.csv'
metrics_file_path = 'metrics.txt'
plot_path = 'plot.png'
@ex.capture
def evaluate_model(model_path, test_data_path, metrics_file_path, plot_path):
import tensorflow as tf import tensorflow as tf
import pandas as pd import pandas as pd
import numpy as np import numpy as np
@ -20,6 +5,12 @@ def evaluate_model(model_path, test_data_path, metrics_file_path, plot_path):
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import os import os
model_path = 'model.h5'
test_data_path = 'data.csv'
metrics_file_path = 'metrics.txt'
plot_path = 'plot.png'
model = tf.keras.models.load_model(model_path) model = tf.keras.models.load_model(model_path)
test_data = pd.read_csv(test_data_path, sep=';') test_data = pd.read_csv(test_data_path, sep=';')
@ -55,13 +46,3 @@ def evaluate_model(model_path, test_data_path, metrics_file_path, plot_path):
plt.plot(metrics_df['top_5_accuracy'], label='Top-5 Accuracy') plt.plot(metrics_df['top_5_accuracy'], label='Top-5 Accuracy')
plt.legend() plt.legend()
plt.savefig(plot_path) plt.savefig(plot_path)
ex.log_scalar('top_1_accuracy', np.mean(top_1_accuracy.numpy()))
ex.log_scalar('top_5_accuracy', np.mean(top_5_accuracy.numpy()))
ex.add_artifact(model_path)
ex.add_artifact(metrics_file_path)
ex.add_artifact(plot_path)
@ex.automain
def main():
evaluate_model()

4
train.py
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@ -1,7 +1,7 @@
from sacred import Experiment from sacred import Experiment
from sacred.observers import MongoObserver, FileStorageObserver from sacred.observers import MongoObserver, FileStorageObserver
ex = Experiment('s487187-training') ex = Experiment('s487187-training', interactive=True)
ex.observers.append(MongoObserver(url='mongodb://admin:IUM_2021@172.17.0.1:27017', db_name='sacred')) ex.observers.append(MongoObserver(url='mongodb://admin:IUM_2021@172.17.0.1:27017', db_name='sacred'))
@ex.config @ex.config
@ -65,3 +65,5 @@ def run_experiment():
accuracy = train_model() accuracy = train_model()
ex.log_scalar('accuracy', accuracy) ex.log_scalar('accuracy', accuracy)
ex.add_artifact('model.h5') ex.add_artifact('model.h5')
ex.run()