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keras update acc > accuracy
1 parent c9cf104 commit e3b4d0b

15 files changed

+52
-47
lines changed

‎ann_class2/keras_example.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -75,8 +75,8 @@
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plt.show()
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# accuracies
78-
plt.plot(r.history['acc'], label='acc')
79-
plt.plot(r.history['val_acc'], label='val_acc')
78+
plt.plot(r.history['accuracy'], label='acc')
79+
plt.plot(r.history['val_accuracy'], label='val_acc')
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plt.legend()
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plt.show()
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‎ann_class2/keras_functional.py

Lines changed: 2 additions & 2 deletions
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@@ -70,8 +70,8 @@
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plt.show()
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# accuracies
73-
plt.plot(r.history['acc'], label='acc')
74-
plt.plot(r.history['val_acc'], label='val_acc')
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plt.plot(r.history['accuracy'], label='acc')
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plt.plot(r.history['val_accuracy'], label='val_acc')
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plt.legend()
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plt.show()
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‎cnn_class/keras_example.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -113,8 +113,8 @@ def rearrange(X):
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plt.show()
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# accuracies
116-
plt.plot(r.history['acc'], label='acc')
117-
plt.plot(r.history['val_acc'], label='val_acc')
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plt.plot(r.history['accuracy'], label='acc')
117+
plt.plot(r.history['val_accuracy'], label='val_acc')
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plt.legend()
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plt.show()
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‎cnn_class2/fashion.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -101,8 +101,8 @@ def y2indicator(Y):
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plt.show()
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# accuracies
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plt.plot(r.history['acc'], label='acc')
105-
plt.plot(r.history['val_acc'], label='val_acc')
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plt.plot(r.history['accuracy'], label='acc')
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plt.plot(r.history['val_accuracy'], label='val_acc')
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plt.legend()
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plt.show()
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‎cnn_class2/fashion2.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -96,8 +96,8 @@ def y2indicator(Y):
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plt.show()
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# accuracies
99-
plt.plot(r.history['acc'], label='acc')
100-
plt.plot(r.history['val_acc'], label='val_acc')
99+
plt.plot(r.history['accuracy'], label='acc')
100+
plt.plot(r.history['val_accuracy'], label='val_acc')
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plt.legend()
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plt.show()
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‎cnn_class2/use_pretrained_weights_resnet.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -173,8 +173,8 @@ def get_confusion_matrix(data_path, N):
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plt.show()
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# accuracies
176-
plt.plot(r.history['acc'], label='train acc')
177-
plt.plot(r.history['val_acc'], label='val acc')
176+
plt.plot(r.history['accuracy'], label='train acc')
177+
plt.plot(r.history['val_accuracy'], label='val acc')
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plt.legend()
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plt.show()
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‎cnn_class2/use_pretrained_weights_vgg.py

Lines changed: 7 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -31,10 +31,10 @@
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# valid_path = '../large_files/blood_cell_images/TEST'
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# https://www.kaggle.com/moltean/fruits
34-
# train_path = '../large_files/fruits-360/Training'
35-
# valid_path = '../large_files/fruits-360/Validation'
36-
train_path = '../large_files/fruits-360-small/Training'
37-
valid_path = '../large_files/fruits-360-small/Validation'
34+
train_path = '../large_files/fruits-360/Training'
35+
valid_path = '../large_files/fruits-360/Validation'
36+
# train_path = '../large_files/fruits-360-small/Training'
37+
# valid_path = '../large_files/fruits-360-small/Validation'
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# useful for getting number of files
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image_files = glob(train_path + '/*/*.jp*g')
@@ -45,7 +45,7 @@
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# look at an image for fun
48-
plt.imshow(image.load_img(np.random.choice(image_files)))
48+
plt.imshow(image.img_to_array(image.load_img(np.random.choice(image_files))).astype('uint8'))
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plt.show()
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@@ -76,7 +76,6 @@
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)
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# create an instance of ImageDataGenerator
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gen = ImageDataGenerator(
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rotation_range=20,
@@ -172,8 +171,8 @@ def get_confusion_matrix(data_path, N):
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plt.show()
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# accuracies
175-
plt.plot(r.history['acc'], label='train acc')
176-
plt.plot(r.history['val_acc'], label='val acc')
174+
plt.plot(r.history['accuracy'], label='train acc')
175+
plt.plot(r.history['val_accuracy'], label='val acc')
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plt.legend()
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plt.show()
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‎nlp_class2/pos_ner_keras.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -217,8 +217,8 @@ def get_data_ner(split_sequences=False):
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plt.show()
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# accuracies
220-
plt.plot(r.history['acc'], label='acc')
221-
plt.plot(r.history['val_acc'], label='val_acc')
220+
plt.plot(r.history['accuracy'], label='acc')
221+
plt.plot(r.history['val_accuracy'], label='val_acc')
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plt.legend()
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plt.show()
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‎nlp_class3/attention.py

Lines changed: 8 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -34,10 +34,10 @@ def softmax_over_time(x):
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# config
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BATCH_SIZE = 64
37-
EPOCHS = 100
38-
LATENT_DIM = 256
39-
LATENT_DIM_DECODER = 256 # idea: make it different to ensure things all fit together properly!
40-
NUM_SAMPLES = 10000
37+
EPOCHS = 30
38+
LATENT_DIM = 400
39+
LATENT_DIM_DECODER = 400 # idea: make it different to ensure things all fit together properly!
40+
NUM_SAMPLES = 20000
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MAX_SEQUENCE_LENGTH = 100
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MAX_NUM_WORDS = 20000
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EMBEDDING_DIM = 100
@@ -190,7 +190,8 @@ def softmax_over_time(x):
190190
# assign the values
191191
for i, d in enumerate(decoder_targets):
192192
for t, word in enumerate(d):
193-
decoder_targets_one_hot[i, t, word] = 1
193+
if word > 0:
194+
decoder_targets_one_hot[i, t, word] = 1
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@@ -367,8 +368,8 @@ def acc(y_true, y_pred):
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plt.show()
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# accuracies
370-
plt.plot(r.history['acc'], label='acc')
371-
plt.plot(r.history['val_acc'], label='val_acc')
371+
plt.plot(r.history['accuracy'], label='acc')
372+
plt.plot(r.history['val_accuracy'], label='val_acc')
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plt.legend()
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plt.show()
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‎nlp_class3/bilstm_mnist.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -97,8 +97,8 @@ def get_mnist(limit=None):
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plt.show()
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# accuracies
100-
plt.plot(r.history['acc'], label='acc')
101-
plt.plot(r.history['val_acc'], label='val_acc')
100+
plt.plot(r.history['accuracy'], label='acc')
101+
plt.plot(r.history['val_accuracy'], label='val_acc')
102102
plt.legend()
103103
plt.show()
104104

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