TFMA and TF KERAS 2.0 model on pretrained model about model-analysis HOT 7 OPEN

`# Load model 
new_model = keras.models.load_model(model_name)
new_model.summary()
# keras model to estimator
estimator_model = tf.keras.estimator.model_to_estimator(new_model,model_dir=TF_MODEL_DIR)]]

# The receiver function for the estimator
def eval_input_receiver_1_fn():

  serialized_tf_example = tf.compat.v1.placeholder(dtype=tf.string, shape=[None], name='input_example_placeholder')

  receiver_tensors = {'examples': serialized_tf_example}
  validation_features_columns = [tf.feature_column.numeric_column("image",shape=(192,192)),
                                 tf.feature_column.categorical_column_with_vocabulary_list("label",["normal_healthy","sick"])]

  feature_spec =  tf.feature_column.make_parse_example_spec(validation_features_columns)
  features = tf.io.parse_example(serialized_tf_example, feature_spec)

  return tfma.export.EvalInputReceiver(
    features=features,
    receiver_tensors=receiver_tensors,
    labels=features['label'])

import os
import shutil
from pathlib import Path

def up_one_dir(path):
  """Move all file in path up one
  """
  parent_dir = str(Path(path).parents[0])
  for f in os.listdir(path):
    shutil.copy(os.path.join(path,f),parent_dir)
  #shutil.rmtree(path)
up_one_dir(KERAS_FOLDER)

tfma.export.export_eval_savedmodel(estimator=estimator_model,
                                   export_dir_base=EXPORT_DIR,
                                   eval_input_receiver_fn=eval_input_receiver_1_fn)

The following error is fired regarding the pre-trained model features:
KeyErrorTraceback (most recent call last)
<ipython-input-137-b275096a314a> in <module>()
      1 tfma.export.export_eval_savedmodel(estimator=estimator_model,
      2                                    export_dir_base=EXPORT_DIR,
----> 3                                    eval_input_receiver_fn=eval_input_receiver_1_fn)

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow_model_analysis/util.pyc in wrapped_fn(*args, **kwargs)
    171                       (fn.__name__, kwargs.keys()))
    172 
--> 173     return fn(**kwargs_to_pass)
    174 
    175   return wrapped_fn

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow_model_analysis/eval_saved_model/export.pyc in export_eval_savedmodel(estimator, export_dir_base, eval_input_receiver_fn, serving_input_receiver_fn, assets_extra, checkpoint_path)
    472       },
    473       assets_extra=assets_extra,
--> 474       checkpoint_path=checkpoint_path)
    475 
    476 

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow/python/util/deprecation.pyc in new_func(*args, **kwargs)
    322               'in a future version' if date is None else ('after %s' % date),
    323               instructions)
--> 324       return func(*args, **kwargs)
    325     return tf_decorator.make_decorator(
    326         func, new_func, 'deprecated',

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow_estimator/contrib/estimator/python/estimator/export.pyc in export_all_saved_models(estimator, export_dir_base, input_receiver_fn_map, assets_extra, as_text, checkpoint_path)
    206       assets_extra=assets_extra,
    207       as_text=as_text,
--> 208       checkpoint_path=checkpoint_path)

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow_estimator/python/estimator/estimator.pyc in experimental_export_all_saved_models(self, export_dir_base, input_receiver_fn_map, assets_extra, as_text, checkpoint_path)
    820         self._add_meta_graph_for_mode(
    821             builder, input_receiver_fn_map, checkpoint_path,
--> 822             save_variables, mode=model_fn_lib.ModeKeys.EVAL)
    823         save_variables = False
    824       if input_receiver_fn_map.get(model_fn_lib.ModeKeys.PREDICT):

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow_estimator/python/estimator/estimator.pyc in _add_meta_graph_for_mode(self, builder, input_receiver_fn_map, checkpoint_path, save_variables, mode, export_tags, check_variables)
    895           labels=getattr(input_receiver, 'labels', None),
    896           mode=mode,
--> 897           config=self.config)
    898 
    899       export_outputs = model_fn_lib.export_outputs_for_mode(

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow_estimator/python/estimator/estimator.pyc in _call_model_fn(self, features, labels, mode, config)
   1110 
   1111     logging.info('Calling model_fn.')
-> 1112     model_fn_results = self._model_fn(features=features, **kwargs)
   1113     logging.info('Done calling model_fn.')
   1114 

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow_estimator/python/estimator/keras.pyc in model_fn(features, labels, mode)
    276 
    277     model = _clone_and_build_model(mode, keras_model, custom_objects, features,
--> 278                                    labels)
    279     model_output_names = []
    280     # We need to make sure that the output names of the last layer in the model

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow_estimator/python/estimator/keras.pyc in _clone_and_build_model(mode, keras_model, custom_objects, features, labels)
    184   K.set_learning_phase(mode == model_fn_lib.ModeKeys.TRAIN)
    185   input_tensors, target_tensors = _convert_estimator_io_to_keras(
--> 186       keras_model, features, labels)
    187 
    188   compile_clone = (mode != model_fn_lib.ModeKeys.PREDICT)

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow_estimator/python/estimator/keras.pyc in _convert_estimator_io_to_keras(keras_model, features, labels)
    157 
    158   input_tensors = _to_ordered_tensor_list(
--> 159       features, input_names, 'features', 'inputs')
    160   target_tensors = _to_ordered_tensor_list(
    161       labels, output_names, 'labels', 'outputs')

/usr/local/envs/py2env/lib/python2.7/site-packages/tensorflow_estimator/python/estimator/keras.pyc in _to_ordered_tensor_list(obj, key_order, obj_name, order_name)
    139                 order_name=order_name, order_keys=set(key_order),
    140                 obj_name=obj_name, obj_keys=set(obj.keys()),
--> 141                 different_keys=different_keys))
    142 
    143       return [_convert_tensor(obj[key]) for key in key_order]

KeyError: "The dictionary passed into features does not have the expected inputs keys defined in the keras model.\n\tExpected keys: set([u'vgg16_input'])\n\tfeatures keys: set(['image', 'label'])\n\tDifference: set(['image', 'label', u'vgg16_input'])"