class_docstr: Test that SparseSoftmaxCrossEntropyWithLogits operates reproducibly.
  
  Inheriting from sparse_xent_op_test_base.SparseXentOpTestBase ensures that
  regular op functionality is correct when the deterministic code-path is
  selected.
  
  Note that because nn_ops.sparse_softmax_cross_entropy_with_logits_v2 calls
  nn_ops.sparse_softmax_cross_entropy_with_logits directly, the focus of
  testing is on the former in order to test both.
class_docstr_tok: ["Test","that","SparseSoftmaxCrossEntropyWithLogits","operates","reproducibly",".","Inheriting","from","sparse_xent_op_test_base.SparseXentOpTestBase","ensures","that","regular","op","functionality","is","correct","when","the","deterministic","code-path","is","selected",".","Note","that","because","nn_ops.sparse_softmax_cross_entropy_with_logits_v2","calls","nn_ops.sparse_softmax_cross_entropy_with_logits","directly",",","the","focus","of","testing","is","on","the","former","in","order","to","test","both","."]
code: def _randomFloats(self, shape, dtype):
      return constant_op.constant(
          (2 * np.random.random_sample(shape) - 1).astype(dtype)
      )
  
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.sparse_ops import sparse_xent_op_test_base
  from tensorflow.python.ops.nn_grad import _SparseSoftmaxCrossEntropyWithLogitsGrad
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the SparseXentOpDeterministicTest obj's underlying member method code with example usage: obj._randomFloats(shape, dtype) and returns: constant_op