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

Before Change

n_queries = 10
for idx in range(n_queries):
    query_idx, query_instance = learner.query(X_pool, n_instances=100)
    print(query_idx)
    learner.teach(X_pool[query_idx], y_pool[query_idx], only_new=True)
    // remove queried instance from pool
    X_pool = np.delete(X_pool, query_idx, axis=0)
    y_pool = np.delete(y_pool, query_idx, axis=0)

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