Preet-Sojitra
commented
1 year ago This is the code that worked for me:
filename="my_mnist.data"
m, n = X_train.shape # Make sure you have loaded MNIST dataset, for loading refer the code snippet below
X_mm = np.memmap(filename, dtype='float32', mode="write", shape=(m, n))
X_mm[:] = X_train
del X_mm
X_mm = np.memmap(filename, dtype='float32', mode="readonly", shape=(m, n))
batch_size = m // n_batches
inc_pca = IncrementalPCA(n_components=154, batch_size=batch_size)
inc_pca.fit(X_mm)# Fetching MNIST data
from sklearn.datasets import fetch_openml
from sklearn.model_selection import train_test_split
mnist = fetch_openml('mnist_784', version=1, as_frame=False)
mnist.target = mnist.target.astype(np.uint8)
X = mnist["data"]
y = mnist["target"]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
OSError: [Errno 22] Invalid argument: 'my_mnist.data' Does anyone know how to fix this error?