class_docstr: The SavedModel fingerprint.
  
  Each attribute of this class is named after a field name in the
  FingerprintDef proto and contains the value of the respective field in the
  protobuf.
  
  Attributes:
    saved_model_checksum: A uint64 containing the `saved_model_checksum`.
    graph_def_program_hash: A uint64 containing `graph_def_program_hash`.
    signature_def_hash: A uint64 containing the `signature_def_hash`.
    saved_object_graph_hash: A uint64 containing the `saved_object_graph_hash`.
    checkpoint_hash: A uint64 containing the`checkpoint_hash`.
    version: An int32 containing the producer field of the VersionDef.
docstr: Constructs Fingerprint object from protocol buffer message.
code: def from_proto(
      cls, proto: fingerprint_pb2.FingerprintDef
  ) -> "Fingerprint":
      """Constructs Fingerprint object from protocol buffer message."""
      if isinstance(proto, bytes):
          proto = fingerprint_pb2.FingerprintDef.FromString(proto)
      try:
          return Fingerprint(
              proto.saved_model_checksum,
              proto.graph_def_program_hash,
              proto.signature_def_hash,
              proto.saved_object_graph_hash,
              proto.checkpoint_hash,
              proto.version,
          )
      except AttributeError as e:
          raise ValueError(
              f"Given proto could not be deserialized as fingerprint."
              f"{e}"
          ) from None
  
file_path: tensorflow-upstream/tensorflow/python/saved_model/fingerprinting.py
imports: from typing import Any
  from tensorflow.core.protobuf import fingerprint_pb2
  from tensorflow.python.saved_model.pywrap_saved_model import fingerprinting
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling the Fingerprint obj's underlying member method code with example usage: obj.from_proto(cls, proto) and returns: Fingerprint