From fcede418570708ef26f29f9c408ca7ce7941c83c Mon Sep 17 00:00:00 2001
From: Kacper Dudzic <kacdud1@st.amu.edu.pl>
Date: Mon, 25 Apr 2022 23:05:50 +0200
Subject: [PATCH] Update 'evaluate.py'

---
 evaluate.py | 70 ++++++++++++++++++++++++++---------------------------
 1 file changed, 35 insertions(+), 35 deletions(-)

diff --git a/evaluate.py b/evaluate.py
index 5c0b695..fcfb97d 100644
--- a/evaluate.py
+++ b/evaluate.py
@@ -1,36 +1,36 @@
-import tensorflow as tf
-from keras.models import load_model
-from matplotlib import pyplot as plt
-from matplotlib.ticker import MaxNLocator
-
-# Załadowanie modelu z pliku
-model = keras.models.load_model('lego_reg_model')
-
-# Załadowanie zbioru testowego
-test_piece_counts = np.array(data_test['piece_count'])
-test_prices = np.array(data_test['list_price'])
-
-# Prosta ewaluacja (mean absolute error)
-test_results = model.evaluate(
-    test_piece_counts,
-    test_prices, verbose=0)
-
-# Zapis wartości liczbowej metryki do pliku
-with open('eval_results.txt', 'a+') as f:
-    f.write(test_results)
-
-# Wygenerowanie i zapisanie do pliku wykresu
-with open('eval_results.txt') as f:
-    scores = []
-    for line in f:
-        scores.append(float(line))
-    builds = list(range(1, len(scores) + 1))
-
-    plot = plt.plot(builds, scores)
-    plt.xlabel('Build number')
-    plt.xticks(range(1, len(scores) + 1))
-    plt.ylabel('Mean absolute error')
-    plt.title('Model error by build')
-    plt.savefig('error_plot.jpg')
-    plt.show()
+import tensorflow as tf
+from tensorflow import keras
+from matplotlib import pyplot as plt
+from matplotlib.ticker import MaxNLocator
+
+# Załadowanie modelu z pliku
+model = keras.models.load_model('lego_reg_model')
+
+# Załadowanie zbioru testowego
+test_piece_counts = np.array(data_test['piece_count'])
+test_prices = np.array(data_test['list_price'])
+
+# Prosta ewaluacja (mean absolute error)
+test_results = model.evaluate(
+    test_piece_counts,
+    test_prices, verbose=0)
+
+# Zapis wartości liczbowej metryki do pliku
+with open('eval_results.txt', 'a+') as f:
+    f.write(test_results)
+
+# Wygenerowanie i zapisanie do pliku wykresu
+with open('eval_results.txt') as f:
+    scores = []
+    for line in f:
+        scores.append(float(line))
+    builds = list(range(1, len(scores) + 1))
+
+    plot = plt.plot(builds, scores)
+    plt.xlabel('Build number')
+    plt.xticks(range(1, len(scores) + 1))
+    plt.ylabel('Mean absolute error')
+    plt.title('Model error by build')
+    plt.savefig('error_plot.jpg')
+    plt.show()
     
\ No newline at end of file