input: Write a python function to tokenize and pad sequences using Keras Tokenizer and pad_sequences.
  ```python
  assert np.array_equal(tokenize_and_pad(["This is a test", "Another test"], 10), 
                        np.array([[4, 3, 2, 5, 0, 0, 0, 0, 0, 0],
                                  [6, 5, 0, 0, 0, 0, 0, 0, 0, 0]]))
  assert np.array_equal(tokenize_and_pad(["Hello World", "Machine Learning"], 5), 
                        np.array([[2, 3, 0, 0, 0],
                                  [4, 5, 0, 0, 0]]))
output: def tokenize_and_pad(texts, maxlen):
      from keras.preprocessing.text import Tokenizer
      from keras.preprocessing.sequence import pad_sequences
      import numpy as np
  
      tokenizer = Tokenizer()
      tokenizer.fit_on_texts(texts)
      sequences = tokenizer.texts_to_sequences(texts)
      padded_sequences = pad_sequences(sequences, maxlen=maxlen, padding='post')
      
      return np.array(padded_sequences)