code: def testZeroDimension(self):
      labels = np.zeros([0, 2, 4]).astype(np.float32)
      logits = np.zeros([0, 2, 4]).astype(np.float32)
      np_loss, _ = self._npXent(labels=labels, logits=logits)
      loss = nn_ops.softmax_cross_entropy_with_logits(
          labels=labels, logits=logits
      )
      tf_loss = self.evaluate(loss)
      self.assertAllEqual(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 19 for calling the XentOpTestBase obj's underlying member method code with example usage: obj.testZeroDimension() without return types