code: def setUp(self, clip_delta, batch_accumulator):
      self.clip_delta = clip_delta
      self.batch_accumulator = batch_accumulator
  
      self.y = torch.FloatTensor([1.0, 2.0, 3.0, 4.0])
      self.t = torch.FloatTensor([2.1, 2.2, 2.3, 2.4])
      if self.clip_delta:
          self.gt_losses = torch.FloatTensor(
              [_huber_loss_1(a) for a in self.y - self.t]
          )
      else:
          self.gt_losses = torch.FloatTensor(
              [0.5 * a**2 for a in self.y - self.t]
          )
  
imports: import unittest
  import basetest_dqn_like
  import pytest
  import torch
  from basetest_training import _TestActorLearnerTrainingMixin, _TestBatchTrainingMixin
  import pfrl
  from pfrl.agents.dqn import DQN, compute_value_loss, compute_weighted_value_loss
label_desc: Use image node_id 1 for calling the TestComputeValueLoss obj's underlying member method code with example usage: obj.setUp(clip_delta, batch_accumulator) without return types