def __init__(self, config, **opt): # Load config used for training and merge with testing options self.config = yaml.load(open(config, "r")) self.config = Namespace(**{**self.config, **opt}) # Load training data.pkl for src and tgt vocabs self.data = load_data(self.config) # Load trained model checkpoints device, devices_ids = misc_utils.set_cuda(self.config) self.model, _ = build_model(None, self.config, device) self.model.eval()
output = [] for rule in app.url_map.iter_rules(): options = {} for arg in rule.arguments: options[arg] = "[{0}]".format(arg) methods = ','.join(rule.methods) url = url_for(rule.endpoint, **options) print(url) output.append(url) return jsonify(' '.join(output)) CORS(app) http_server = WSGIServer((host, port), app) logger.info("Model loaded, serving deepsegment on port %d" % port) http_server.serve_forever() if __name__ == '__main__': opt = opts.model_opts() config = yaml.load(open(opt.config, "r")) config = Namespace(**config, **vars(opt)) device, devices_id = misc_utils.set_cuda(config) config.device = device # stdout_handler = prepare_global_logging(args.serialization_dir, args.file_friendly_logging) start(config, url_root=config.url_root, host=config.ip, port=config.port) # cleanup_global_logging(stdout_handler)