code: def testLogisticOutputMultiDim(self):
      for use_gpu in [True, False]:
          for dtype in [dtypes.float32, dtypes.float16]:
              with self.cached_session(use_gpu=use_gpu):
                  logits, targets, losses = self._Inputs(
                      dtype=dtype, sizes=[2, 2, 2]
                  )
                  loss = nn_impl.sigmoid_cross_entropy_with_logits(
                      labels=targets, logits=logits
                  )
                  np_loss = np.array(losses).astype(np.float32)
                  tf_loss = self.evaluate(loss)
              self.assertAllClose(np_loss, tf_loss, atol=0.001)
  
imports: import math
  import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import nn_impl
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 5 for calling the SigmoidCrossEntropyWithLogitsTest obj's underlying member method code with example usage: obj.testLogisticOutputMultiDim() without return types