input: Write a python function to initialize, train, and predict using a RandomForestClassifier from sklearn. 
  assert type(train_random_forest(train_x, train_y, test_x))==np.ndarray
  assert len(train_random_forest(train_x, train_y, test_x))==len(test_x)
output: def train_random_forest(train_x, train_y, test_x):
      from sklearn.ensemble import RandomForestClassifier
      import numpy as np
  
      # Initialize the RandomForestClassifier
      model = RandomForestClassifier()
  
      # Train the model
      model.fit(train_x, train_y)
  
      # Predict using the trained model
      predictions = model.predict(test_x)
  
      return predictions