code: def test_keep_increasing_until_capped(self, strategy_fn):
      with strategy_fn().scope():
          init_loss_scale = np.finfo(np.float32).max / 4
          max_float = np.finfo(np.float32).max
  
          inputs = [True] * 6
          # Output is capped the 2nd time it doubles.
          expected_outputs = [
              init_loss_scale,
              init_loss_scale * 2,
              init_loss_scale * 2,
              max_float,
              max_float,
              max_float,
          ]
  
          self._test_helper(inputs, expected_outputs, init_loss_scale)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import mirrored_strategy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training.experimental import loss_scale
label_desc: Use image node_id 4 for calling the DynamicLossScaleTest obj's underlying member method code with example usage: obj.test_keep_increasing_until_capped(strategy_fn) without return types