code: def test_uniform_unit_scaling_can_initialize(self):
      tensor = torch.zeros([10, 6])
      uniform_unit_scaling(tensor, "linear")
  
      assert tensor.data.max() < math.sqrt(3 / 10)
      assert tensor.data.min() > -math.sqrt(3 / 10)
  
      # Check that it gets the scaling correct for relu (1.43).
      uniform_unit_scaling(tensor, "relu")
      assert tensor.data.max() < math.sqrt(3 / 10) * 1.43
      assert tensor.data.min() > -math.sqrt(3 / 10) * 1.43
  
imports: from __future__ import division
  from __future__ import with_statement
  from __future__ import absolute_import
  import json
  import logging
  import math
  import numpy
  import pytest
  import torch
  import _jsonnet
  from allennlp.nn import InitializerApplicator, Initializer
  from allennlp.nn.initializers import block_orthogonal, uniform_unit_scaling
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.common.params import Params
label_desc: Use image node_id 7 for calling the TestInitializers obj's underlying member method code with example usage: obj.test_uniform_unit_scaling_can_initialize() without return types