input: Write a python function to build a sequential model with Embedding, GRU, Dropout, and Dense layers using TensorFlow.
  assert build_model(10000, 64).summary() == None
  assert build_model(5000, 128).layers[1].units == 128
  assert build_model(20000, 32).layers[3].activation.__name__ == 'softmax'
output: def build_model(vocab_size, embedding_dim):
      import tensorflow as tf
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Embedding, GRU, Dropout, Dense
  
      model = Sequential([
          Embedding(input_dim=vocab_size, output_dim=embedding_dim),
          GRU(units=embedding_dim),
          Dropout(rate=0.5),
          Dense(units=vocab_size, activation='softmax')
      ])
  
      return model