code: def test_uniformly_weighted(self):
      # Uniform weights
      w1 = np.ones(self.y.size, dtype="f")
  
      loss_w1 = compute_weighted_value_loss(
          self.y,
          self.t,
          clip_delta=self.clip_delta,
          batch_accumulator=self.batch_accumulator,
          weights=w1,
      ).array
      if self.batch_accumulator == "mean":
          gt_loss = self.gt_losses.mean()
      else:
          gt_loss = self.gt_losses.sum()
      self.assertAlmostEqual(loss_w1, gt_loss, places=5)
  
imports: import unittest
  from chainer import testing
  import numpy
  import basetest_dqn_like
  import chainerrl
  from chainerrl.agents.dqn import compute_value_loss
  from chainerrl.agents.dqn import compute_weighted_value_loss
  from chainerrl.agents.dqn import DQN
  from basetest_training import _TestBatchTrainingMixin
label_desc: Use image node_id 3 for calling the TestComputeValueLoss obj's underlying member method code with example usage: obj.test_uniformly_weighted() without return types