input: Write a python function to tokenize and pad sequences from a list of texts using the provided parameters.
  ```python
  assert (tokenize_and_pad(["This is a sample text.", "Another sample text."], 10000, "<OOV>", 120) == pad_sequences([[2, 3, 4, 5, 6, 7], [8, 3, 4, 5]], maxlen=120, padding='post', truncating='post')).all()
  assert (tokenize_and_pad(["Hello world!", "Test sentence for tokenization."], 5000, "<UNKNOWN>", 100) == pad_sequences([[2, 3], [4, 5, 6, 7, 8]], maxlen=100, padding='post', truncating='post')).all()
output: def tokenize_and_pad(texts, vocab_size, oov_token, max_length):
      from tensorflow.keras.preprocessing.text import Tokenizer
      from tensorflow.keras.preprocessing.sequence import pad_sequences
      
      tokenizer = Tokenizer(num_words=vocab_size, oov_token=oov_token)
      tokenizer.fit_on_texts(texts)
      sequences = tokenizer.texts_to_sequences(texts)
      padded_sequences = pad_sequences(sequences, maxlen=max_length, padding='post', truncating='post')
      
      return padded_sequences