func.return %3, %3#1 : tensor<8x8x8x8xf32>, tensor<8xf32>

// CHECK-LABEL: fusedBatchNormV3
// CHECK-DAG:  %[[CONSTANT:.*]] = arith.constant dense<1.000000e-03>
// CHECK-DAG:  %[[CONSTANT1:.*]] = arith.constant dense<0.000000e+00> : tensor<4xf32>
//              variance + epsilon
// CHECK:  %[[ADD1:.*]] = "tf.Add"(%[[ARG4:.*]], %[[CONSTANT]])
//              rsqrt(variance + epsilon)

  "tf_device.cluster"() ({

    // CHECK: "tf.Const"() <{value = dense<(1.000000e+00,0.000000e+00)> : tensor<complex<f32>>}> : () -> tensor<complex<f32>>
    // CHECK-NOT: tf.ResourceApplyAdam

	SECURITY_WORLD_SID_AUTHORITY       = SidIdentifierAuthority{[6]byte{0, 0, 0, 0, 0, 1}}
	SECURITY_LOCAL_SID_AUTHORITY       = SidIdentifierAuthority{[6]byte{0, 0, 0, 0, 0, 2}}
	SECURITY_CREATOR_SID_AUTHORITY     = SidIdentifierAuthority{[6]byte{0, 0, 0, 0, 0, 3}}
	SECURITY_NON_UNIQUE_AUTHORITY      = SidIdentifierAuthority{[6]byte{0, 0, 0, 0, 0, 4}}

    )

    # Indirectly tests that the model is not quantized by asserting that there
    # are negligible numeric difference.
    self.assertAllClose(new_outputs, expected_outputs, rtol=0.000001)

    # Due to other meta data, the compression is not exactly 1/4.
    self.assertLess(
        testing.get_size_ratio(
            self._output_saved_model_path, self._input_saved_model_path
        ),