code: def test_ab_relu_relu(self, same_inputs, do_stabilize):
      key = random.PRNGKey(1)
      X0_1 = random.normal(key, (3, 2))
      fc = stax.Dense(5, 1, 0)
  
      # Test that ABRelu(0, 1) == ReLU
      init_fn, apply_relu, kernel_fn_relu = stax.serial(fc, stax.Relu())
      _, params = init_fn(key, input_shape=X0_1.shape)
  
      X0_2 = None if same_inputs else random.normal(key, (4, 2))
  
      for a, b in [(0, 1), (0, -1), (-1, 0), (1, 0)]:
          with self.subTest(a=a, b=b):
              _, apply_ab_relu, kernel_fn_ab_relu = stax.serial(
                  fc, stax.ABRelu(a, b, do_stabilize=do_stabilize)
              )
  
              X1_1_relu = (b - a) * apply_relu(
                  params, X0_1 * (-1 if a != 0 else 1)
              )
              X1_1_ab_relu = apply_ab_relu(params, X0_1)
              self.assertAllClose(X1_1_relu, X1_1_ab_relu)
  
              kernels_relu = kernel_fn_relu(X0_1, X0_2)
              kernels_ab_relu = kernel_fn_ab_relu(X0_1, X0_2)
              self.assertAllClose(kernels_relu, kernels_ab_relu)
  
imports: import itertools
  import random
  from absl.testing import absltest
  from jax import config
  from jax import default_backend
  from jax import grad, jacfwd, jacrev, jit, jvp, value_and_grad
  from jax import random
  import jax.numpy
  import neural_tangents
  from neural_tangents import stax
  from neural_tangents._src.empirical import _DEFAULT_TESTING_NTK_IMPLEMENTATION
  from tests import test_utils
label_desc: Use image node_id 1 for calling the ABReluTest obj's underlying member method code with example usage: obj.test_ab_relu_relu(same_inputs, do_stabilize) without return types