def get_metadata(self): try: sess = InferenceSession(self.saved_path + self.file_name) except os.error as err: print("OS error: {0}".format(err)) sys.exit() except: print("Error: Load " + self.file_name + " model first.") sys.exit() try: meta = sess.get_modelmeta() except os.error as err: print("OS error: {0}".format(err)) sys.exit() except: print("Error: " + self.file_name + " model metadata is too big.") sys.exit() if meta is not None: print("custom_metadata_map={}".format(meta.custom_metadata_map)) print("description={}".format(meta.description)) print("domain={}".format(meta.domain, meta.domain)) print("graph_name={}".format(meta.graph_name)) print("producer_name={}".format(meta.producer_name)) print("version={}".format(meta.version)) else: print("Metadata does not exist")
*scikit-learn* and converted with *onnxmltools*. """ from onnxruntime.datasets import get_example example = get_example("logreg_iris.onnx") import onnx model = onnx.load(example) print("doc_string={}".format(model.doc_string)) print("domain={}".format(model.domain)) print("ir_version={}".format(model.ir_version)) print("metadata_props={}".format(model.metadata_props)) print("model_version={}".format(model.model_version)) print("producer_name={}".format(model.producer_name)) print("producer_version={}".format(model.producer_version)) ############################# # With *ONNX Runtime*: from onnxruntime import InferenceSession sess = InferenceSession(example) meta = sess.get_modelmeta() print("custom_metadata_map={}".format(meta.custom_metadata_map)) print("description={}".format(meta.description)) print("domain={}".format(meta.domain, meta.domain)) print("graph_name={}".format(meta.graph_name)) print("producer_name={}".format(meta.producer_name)) print("version={}".format(meta.version))