code: def testFloat(self):
      for label_dtype in np.int32, np.int64:
          self._testXent(
              np_labels=np.array([3, 0]).astype(label_dtype),
              np_logits=np.array(
                  [[1.0, 1.0, 1.0, 1.0], [1.0, 2.0, 3.0, 4.0]]
              ).astype(np.float32),
          )
  
imports: import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  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_v2
  from tensorflow.python.ops import nn_ops
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 15 for calling the SparseXentOpTestBase obj's underlying member method code with example usage: obj.testFloat() without return types