feat: use DeepNNLayer in Autoencoder

2026-03-28 02:07:23 +01:00
parent a50a09b337
commit e5520bf050
2 changed files with 28 additions and 18 deletions
--- a/mnist_test.py
+++ b/mnist_test.py
@@ -26,8 +26,17 @@ def mnist_test(
    x_train = np.divide(x_train, 255)
    x_test = np.divide(x_train, 255)
    in_len = x_train[0].shape[0] * x_train[0].shape[0]
-    autoencoder = Autoencoder(in_len, bottleneck, 0.001, relu)
-    autoencoder.train_dataset(x_train, max_epoch, patience, display_loss=True)
+    autoencoder = Autoencoder(
+        [in_len, bottleneck],
+        [bottleneck, in_len],
+        0.1,
+        relu
+    )
+    autoencoder.train_dataset(
+        x_train,
+        max_epoch,
+        patience,
+        display_loss=True)
    example: np.ndarray = x_test[np.random.randint(0, len(x_test))]
    code = autoencoder.encode(example.flatten())
    output = autoencoder.decode(code)