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)))
