code: def _testXentND(self, np_labels, np_logits, dim=-1):
      np_loss, _ = self._npXent(np_labels, np_logits, dim=dim)
      loss = nn_ops.softmax_cross_entropy_with_logits(
          labels=np_labels, logits=np_logits, dim=dim
      )
      tf_loss = self.evaluate(loss)
      self.assertAllCloseAccordingToType(np_loss, tf_loss)
  
imports: import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops.nn_grad import _SoftmaxCrossEntropyWithLogitsGrad
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling the XentOpTestBase obj's underlying member method code with example usage: obj._testXentND(np_labels, np_logits, dim) without return types