input: Write a function to generate natural language responses using the given input utterance. The function will use a deep learning model with Embedding and GRU layers and return the predicted response. The model should be trained with sample inputs and outputs for a specified number of epochs. 
  
  def generate_response(utterance, model):
      prediction = model.predict(utterance)
      return prediction
  
  import tensorflow as tf
  from tensorflow.keras.layers import Input, Dense, Embedding, GRU
  from tensorflow.keras.models import Model
  
  inputs1 = Input(shape=(20,))
  x1 = Embedding(1000, 64)(inputs1)
  x1 = GRU(128)(x1)
  y1 = Dense(1000, activation='softmax')(x1)
  model = Model(inputs=[inputs1], outputs=[y1])
  model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
  
  assert generate_response("What time is it?", model) is not None
  assert generate_response("What is the weather today?", model) is not None
output: def generate_response(utterance, model):
      prediction = model.predict(utterance)
      return prediction