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author | nunzip <np.scarh@gmail.com> | 2019-02-27 23:49:55 +0000 |
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committer | nunzip <np.scarh@gmail.com> | 2019-02-27 23:49:55 +0000 |
commit | 48a6fa973b65a696d087af35c1b410d73ecddde4 (patch) | |
tree | 94e47bacc1eeb125dc728c6fa9b7eb9718367ac2 | |
parent | a82ede1619aa57fe081805f10a799e1f8e3b53f9 (diff) | |
download | e4-gan-48a6fa973b65a696d087af35c1b410d73ecddde4.tar.gz e4-gan-48a6fa973b65a696d087af35c1b410d73ecddde4.tar.bz2 e4-gan-48a6fa973b65a696d087af35c1b410d73ecddde4.zip |
Fix accuracy plot
-rw-r--r-- | lenet.py | 2 |
1 files changed, 1 insertions, 1 deletions
@@ -116,7 +116,7 @@ def train_classifier(x_train, y_train, x_val, y_val, batch_size=128, epochs=100, model.compile(loss='categorical_crossentropy', metrics=metrics, optimizer=optimizer) history = model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, verbose=1, validation_data = (x_val, y_val)) - plot_history(history, metric=metrics) + plot_history(history, metrics) return model def test_classifier(model, x_test, y_true): |