github.com/alwaysproblem/mlserving-tutorial@v0.0.0-20221124033215-121cfddbfbf4/TFserving/ClientAPI/python/grpc_metadata.py (about)

     1  """Module for requesting server metadata python api example."""
     2  import grpc
     3  from tensorflow_serving.apis import prediction_service_pb2_grpc
     4  from tensorflow_serving.apis import get_model_metadata_pb2
     5  
     6  host = "0.0.0.0"
     7  port = 8500
     8  server = host + ":" + str(port)
     9  
    10  if __name__ == "__main__":
    11  
    12    import argparse
    13  
    14    parse = argparse.ArgumentParser(prog="the tensorflow client for python.")
    15    parse.add_argument(
    16        "-m", "--model", type=str, action="store", dest="model", default="Toy"
    17    )
    18    parse.add_argument(
    19        "-v", "--version", type=int, action="store", dest="version", default=-1
    20    )
    21  
    22    args = parse.parse_args()
    23  
    24    channel = grpc.insecure_channel(server)
    25    stub = prediction_service_pb2_grpc.PredictionServiceStub(channel)
    26  
    27    get_model_metadata_request = get_model_metadata_pb2.GetModelMetadataRequest()
    28    get_model_metadata_request.model_spec.name = args.model
    29    if args.version > -1:
    30      get_model_metadata_request.model_spec.version.value = args.version
    31    get_model_metadata_request.metadata_field.append("signature_def")
    32  
    33    resp = stub.GetModelMetadata(get_model_metadata_request)
    34    print(resp)