def METHOD_NAME(self, start_server_single_model_onnx):
    """
    <b>Description</b>
    Submit request to gRPC interface serving a single resnet model
    <b>input data</b>
    - directory with the model in ONNX format
    - docker image with ovms service
    <b>fixtures used</b>
    - model downloader
    - service launching
    <b>Expected results</b>
    - response contains proper numpy shape
    """
    _, ports = start_server_single_model_onnx
    # Connect to grpc service
    stub = create_channel(port=ports["grpc_port"])
    imgs_v1_224 = np.ones(ResnetONNX.input_shape, ResnetONNX.dtype)
    output = infer(imgs_v1_224, input_tensor=ResnetONNX.input_name, grpc_stub=stub,
                   model_spec_name=ResnetONNX.name,
                   model_spec_version=None,
                   output_tensors=[ResnetONNX.output_name])
    logger.info("Output shape: {}".format(output[ResnetONNX.output_name].shape))
    assert output[ResnetONNX.output_name].shape == ResnetONNX.output_shape, ERROR_SHAPE