input: 
  def generate_response(utterance: str) -> str:
      """Generate a natural language response using a pre-trained neural network model.
  
      >>> generate_response("What time is it?")
      "The current time is 12:00 PM."
      """
  
output:     import torch
      from transformers import GPT2LMHeadModel, GPT2Tokenizer
  
      model_name = "gpt2"
      model = GPT2LMHeadModel.from_pretrained(model_name)
      tokenizer = GPT2Tokenizer.from_pretrained(model_name)
  
      inputs = tokenizer.encode(utterance, return_tensors="pt")
      outputs = model.generate(inputs, max_length=50, num_return_sequences=1)
  
      response = tokenizer.decode(outputs[0], skip_special_tokens=True)
      return response