code: def _generate_params_and_first_order_output(self):
      a = torch.rand(3, requires_grad=True)
      b = torch.rand(1, requires_grad=True)
      params = [a, b]
      y = torch.sum(a, dim=0, keepdims=True) * 3 + b
      return params, y
  
imports: import os
  import tempfile
  import unittest
  import numpy
  import pytest
  import torch
  from torch import nn
  import pfrl
  from pfrl.agents import trpo
  from pfrl.envs.abc import ABC
  from pfrl.experiments import train_agent_batch_with_evaluation, train_agent_with_evaluation
  from pfrl.experiments.evaluator import batch_run_evaluation_episodes, run_evaluation_episodes
  from pfrl.nn import RecurrentSequential
  from pfrl.policies import GaussianHeadWithStateIndependentCovariance, SoftmaxCategoricalHead
  from pfrl.testing import torch_assert_allclose
label_desc: Use image node_id 1 for calling the TestHessianVectorProduct obj's underlying member method code with example usage: obj._generate_params_and_first_order_output() and returns: params,  y