def evaluate_saved_model(directory, tag_set, signature_key): """Returns a function that evaluates the SavedModel on input data. Args: directory: SavedModel directory to convert. tag_set: Set of tags identifying the MetaGraphDef within the SavedModel to analyze. All tags in the tag set must be present. signature_key: Key identifying SignatureDef containing inputs and outputs. Returns: Lambda function ([np.ndarray data] : [np.ndarray result]). """ with _session.Session().as_default() as sess: if tag_set is None: tag_set = set([_tag_constants.SERVING]) if signature_key is None: signature_key = _signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY meta_graph = _loader.load(sess, tag_set, directory) signature_def = _convert_saved_model.get_signature_def( meta_graph, signature_key) inputs, outputs = _convert_saved_model.get_inputs_outputs( signature_def) return lambda input_data: sess.run(outputs, dict(zip(inputs, input_data)))
def evaluate_saved_model(directory, tag_set, signature_key): """Returns a function that evaluates the SavedModel on input data. Args: directory: SavedModel directory to convert. tag_set: Set of tags identifying the MetaGraphDef within the SavedModel to analyze. All tags in the tag set must be present. signature_key: Key identifying SignatureDef containing inputs and outputs. Returns: Lambda function ([np.ndarray data] : [np.ndarray result]). """ with _session.Session().as_default() as sess: if tag_set is None: tag_set = set([_tag_constants.SERVING]) if signature_key is None: signature_key = _signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY meta_graph = _loader.load(sess, tag_set, directory) signature_def = _convert_saved_model.get_signature_def( meta_graph, signature_key) inputs, outputs = _convert_saved_model.get_inputs_outputs(signature_def) return lambda input_data: sess.run(outputs, dict(zip(inputs, input_data)))