code: def test_classify_scores_must_be_float(self):
      with context.graph_mode():
          scores = array_ops.placeholder(
              dtypes.string, 1, name="output-tensor-1"
          )
          with self.assertRaisesRegex(
              ValueError,
              "Classification scores must be a float32 Tensor",
          ):
              export_output_lib.ClassificationOutput(scores=scores)
  
imports: from tensorflow.core.framework import tensor_shape_pb2
  from tensorflow.core.framework import types_pb2
  from tensorflow.core.protobuf import meta_graph_pb2
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import metrics
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.saved_model import signature_constants
  from tensorflow.python.saved_model.model_utils import export_output
label_desc: Use image node_id 3 for calling the ExportOutputTest obj's underlying member method code with example usage: obj.test_classify_scores_must_be_float() without return types