caec2c73aad40c0e632e978964ec5c3cf4773c9e,examples/pytorch_integration.py,,,#,41

Before Change

// read training data
(X_train, y_train), (X_test, y_test) = mnist.load_data()
X_train = X_train.reshape(60000, 1, 28, 28).astype("float32") / 255.
X_test = X_test.reshape(10000, 1, 28, 28).astype("float32") / 255.
y_train = y_train.astype("long")
y_test  = y_test.astype("long")

After Change

mnist_data = MNIST(".", download=True, transform=ToTensor())
dataloader = DataLoader(mnist_data, shuffle=True, batch_size=60000)
X, y = next(iter(dataloader))

// read training data
X_train, X_test, y_train, y_test = X[:50000], X[50000:], y[:50000], y[50000:]
X_train = X_train.reshape(50000, 1, 28, 28)

Instances