docstr: Writes a classifier with two input features to the given path.
code: def _writeDummySavedModel(self, path, feature_name, tags):
      """Writes a classifier with two input features to the given path."""
      with ops.Graph().as_default():
          examples = array_ops.placeholder(
              dtypes.string, name="input_node"
          )
          feature_configs = {
              feature_name: parsing_ops.FixedLenFeature(
                  shape=[], dtype=dtypes.float32
              ),
          }
          features = parsing_ops.parse_example(
              examples, feature_configs
          )
          feature = features[feature_name]
  
          variable_node = variable_v1.VariableV1(
              1.0, name="variable_node"
          )
          scores = math_ops.multiply(
              variable_node, feature, name="output_node"
          )
          class_feature = array_ops.fill(
              array_ops.shape(feature), "class_%s" % feature_name
          )
          classes = array_ops.transpose(class_feature)
  
          with session.Session() as sess:
              sess.run(variables.global_variables_initializer())
              signature = (
                  signature_def_utils.classification_signature_def(
                      examples=examples,
                      classes=classes,
                      scores=scores,
                  )
              )
              builder = saved_model_builder.SavedModelBuilder(path)
              builder.add_meta_graph_and_variables(
                  sess,
                  tags,
                  signature_def_map={
                      signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY: signature,
                  },
              )
              builder.save(as_text=True)
  
imports: import os
  import re
  from absl.testing import parameterized
  from tensorflow.core.example import example_pb2
  from tensorflow.core.framework import graph_pb2
  from tensorflow.core.protobuf import saver_pb2
  from tensorflow.python.client import session
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import graph_io
  from tensorflow.python.framework import importer
  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 math_ops
  from tensorflow.python.ops import nn
  from tensorflow.python.ops import parsing_ops
  from tensorflow.python.ops import partitioned_variables
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variable_v1
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.saved_model import builder
  from tensorflow.python.saved_model import signature_constants
  from tensorflow.python.saved_model import signature_def_utils
  from tensorflow.python.saved_model import tag_constants
  from tensorflow.python.tools import freeze_graph
  from tensorflow.python.training import saver
label_desc: Use image node_id 3 for calling the FreezeGraphTest obj's underlying member method code with example usage: obj._writeDummySavedModel(path, feature_name, tags) without return types