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feat: loss method + mv data reshaping out of Autoencoder class

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Lenoctambule
2026-03-28 02:40:10 +01:00
parent e5520bf050
commit 6155649655
3 changed files with 25 additions and 11 deletions
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12
mnist_test.py
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@@ -4,7 +4,7 @@ from autoencoder import Autoencoder
from utils import relu
def load_mnist():
def load_mnist() -> list[np.ndarray]:
import os
import requests
@@ -23,9 +23,13 @@ def mnist_test(
patience: int,
):
x_train, _, x_test, _ = load_mnist()
in_len = x_train[0].shape[0] * x_train[0].shape[0]
img_shape = x_train[0].shape
x_train.resize(x_train.shape[0], in_len)
x_test.resize(x_test.shape[0], in_len)
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]
x_train = x_train[:1000]
autoencoder = Autoencoder(
[in_len, bottleneck],
[bottleneck, in_len],
@@ -41,9 +45,9 @@ def mnist_test(
code = autoencoder.encode(example.flatten())
output = autoencoder.decode(code)
plt.subplot(1, 2, 1)
plt.matshow(example, fignum=False)
plt.matshow(example.reshape(img_shape), fignum=False)
plt.subplot(1, 2, 2)
plt.matshow(output.reshape(example.shape), fignum=False)
plt.matshow(output.reshape(img_shape), fignum=False)
plt.show()