class_docstr: Test that SoftmaxCrossEntropyWithLogits operates reproducibly.
  
  Inheriting from xent_op_test_base.XentTestBase ensures that regular op
  functionality is correct when the deterministic code-path is selected.
  
  Note that because nn_ops.softmax_cross_entropy_with_logits calls
  nn_ops.cross_entropy_with_logits_v2, the focus of testing is on the
  former in order to test both.
code: def _randomFloats(self, shape, dtype, normalized_rows=False):
      a = (2 * np.random.random_sample(shape) - 1).astype(dtype)
  
      if normalized_rows:
  
          def normalize(row):
              return row / row.sum()
  
          a = np.apply_along_axis(normalize, 1, a)
  
      return constant_op.constant(a)
  
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 errors_impl
  from tensorflow.python.framework import test_util
  from tensorflow.python.kernel_tests.nn_ops import xent_op_test_base
  from tensorflow.python.ops import gen_nn_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 1 for calling the XentOpDeterministicTest obj's underlying member method code with example usage: obj._randomFloats(shape, dtype, normalized_rows) and returns: constant_op, unknown