input: Write a function to generate a machine learning model using scikit-learn for classifying digits in the MNIST dataset. The function should load the dataset, split it into features and labels, reshape the data, create a Logistic Regression classifier, and fit the model to the data.
  
  assert generate_mnist_classifier(fetch_openml('mnist_784'))==None
  assert type(generate_mnist_classifier(fetch_openml('mnist_784')))==LogisticRegression
  assert generate_mnist_classifier(fetch_openml('mnist_784')).coef_.shape[0]==10
output: def generate_mnist_classifier(dataset):
      X, y = dataset.data, dataset.target
      X = X.reshape(-1, 28*28)
      model = LogisticRegression(max_iter=200)
      model.fit(X, y)
      return model