code: def testRange(self):
      batch_size = 3
      height, width = 4, 4
      np.random.seed(1)  # Make it reproducible.
      inputs = np.random.uniform(
          size=(batch_size, height, width, 3)
      ).astype(np.float32)
      inputs = _get_weak_tensor(inputs)
  
      outputs = nn_ops.leaky_relu(inputs)
      self.assertEqual(inputs.shape, outputs.shape)
      self.assertIsInstance(outputs, weak_tensor.WeakTensor)
  
      inputs, outputs = self.evaluate([inputs, outputs])
  
      self.assertGreaterEqual(outputs.min(), 0.0)
      self.assertLessEqual(outputs.max(), 1.0)
      self.assertAllClose(inputs, outputs)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.framework import weak_tensor
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_impl
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import weak_tensor_ops
  from tensorflow.python.ops import weak_tensor_test_util
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the LeakyReluTest obj's underlying member method code with example usage: obj.testRange() without return types