input: def generate_mnist_classifier():
      """Generate a machine learning model in Python using scikit-learn for classifying digits in the MNIST dataset.
      >>> generate_mnist_classifier()
      ((70000, 784), (70000,))
      """
      from sklearn.datasets import fetch_openml
      import numpy as np
      from sklearn.linear_model import LogisticRegression
      
      # Load the dataset
      mnist = fetch_openml('mnist_784')
      
      # Split into features and labels
      X = mnist.data
      y = mnist.target
      
      # Reshape data to be valid
      X = X.reshape((X.shape[0], -1))
      print(X.shape, y.shape)
      
      # Create a Logistic Regression classifier
      clf = LogisticRegression()
      
      # Fit the model to the data
      clf.fit(X, y)
      
      # Return the shape of the data as output
      return X.shape, y.shape
output:     return X.shape, y.shape