input: Write a function to generate a machine learning model using scikit-learn for classifying digits in the MNIST dataset. The function should import necessary libraries, load the MNIST dataset, split it into features and labels, reshape the data, create a Logistic Regression classifier, and fit the model to the data.
  assert mnist_classifier()==None
  assert type(mnist_classifier())==LogisticRegression
output: def mnist_classifier():
      from sklearn.datasets import load_digits
      from sklearn.model_selection import train_test_split
      from sklearn.linear_model import LogisticRegression
      from sklearn.preprocessing import StandardScaler
  
      digits = load_digits()
      X = digits.data
      y = digits.target
  
      scaler = StandardScaler()
      X = scaler.fit_transform(X)
  
      model = LogisticRegression()
      model.fit(X, y)
  
      return model