You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: script_rfcn_VOC0712_ResNet101_OHEM_rpn.m
    path of file: ./repos/R-FCN/experiments
    
    the code of the file until where you have to start completion: function script_rfcn_VOC0712_ResNet101_OHEM_rpn()
% script_rfcn_VOC0712_ResNet101_OHEM_rpn()
% RFCN training and testing with OHEM using ResNet101 model and RPN
% proposals
% --------------------------------------------------------
% R-FCN implementation
% Modified from MATLAB Faster R-CNN (https://github.com/shaoqingren/faster_rcnn)
% Copyright (c) 2016, Jifeng Dai
% Licensed under The MIT License [see LICENSE for details]
% --------------------------------------------------------


clc;
clear mex;

    
function script_rfcn_VOC0712_ResNet101_OHEM_rpn()
% script_rfcn_VOC0712_ResNet101_OHEM_rpn()
% RFCN training and testing with OHEM using ResNet101 model and RPN
% proposals
% --------------------------------------------------------
% R-FCN implementation
% Modified from MATLAB Faster R-CNN (https://github.com/shaoqingren/faster_rcnn)
% Copyright (c) 2016, Jifeng Dai
% Licensed under The MIT License [see LICENSE for details]
% --------------------------------------------------------


clc;
clear mex;
clear is_valid_handle; % to clear init_key
run(fullfile(fileparts(fileparts(mfilename('fullpath'))), 'startup'));
%% -------------------- CONFIG --------------------
opts.caffe_version          = 'caffe_rfcn';
opts.gpu_id                 = auto_select_gpu;
active_caffe_mex(opts.gpu_id, opts.caffe_version);

% model
model                       = Model.ResNet101_for_RFCN_VOC0712_OHEM();
% cache name
opts.cache_name             = 'rfcn_VOC0712_ResNet101_OHEM_rpn_resnet101';
% config
conf                        = rfcn_config_ohem('image_means', model.mean_image);
% train/test data
fprintf('Loading dataset...')
dataset                     = [];
dataset                     = Dataset.voc0712_trainval_sp(dataset, 'train', conf.use_flipped, 'resnet101');
dataset                     = Dataset.voc2007_test_sp(dataset, 'test', false, 'resnet101');
fprintf('Done.\n');

% do validation, or not
opts.do_val                 = true; 

%% -------------------- TRAINING --------------------

opts.rfcn_model        = rfcn_train(conf, dataset.imdb_train, dataset.roidb_train, ...
                                'do_val',           opts.do_val, ...
                                'imdb_val',         dataset.imdb_test, ...
                                'roidb_val',        dataset.roidb_test, ...
                                'solver_def_file',  model.solver_def_file, ...
                                'net_file',         model.net_file, ...
                                'cache_name',       opts.cache_name, ...
                                'caffe_version',    opts.caffe_version);
assert(exist(opts.rfcn_model, 'file') ~= 0, 'not found trained model');

%% -------------------- TESTING --------------------
                          rfcn_test(conf, dataset.imdb_test, dataset.roidb_test, ...
                                'net_def_file',     model.test_net_def_file, ...
                                'net_file',         opts.rfcn_model, ...
                                'cache_name',       opts.cache_name,...
                                'ignore_cache',     true);

end