def get_eval_metric(self, args, name="metric", ds=None):
""" Returns a neurst.metrics.metric.Metric object for evaluation."""
if ds is not None and hasattr(ds, "trg_lang") and ds.trg_lang is not None:
return build_metric(args[name + ".class"], language=ds.trg_lang,
**args[name + ".params"])
return build_metric(args[name + ".class"], language=self._trg_data_pipeline.meta["language"],
**args[name + ".params"])
def _main(_):
arg_parser = flags_core.define_flags(FLAG_LIST, with_config_file=False)
args, remaining_argv = flags_core.intelligent_parse_flags(
FLAG_LIST, arg_parser)
flags_core.verbose_flags(FLAG_LIST, args, remaining_argv)
metric = build_metric(args)
evaluate(metric, args["hypo_file"], args["ref_file"])
def get_eval_metric(self, args, name="metric"):
""" Returns a neurst.metrics.metric.Metric object for evaluation."""
return build_metric(args[name + ".class"], language=self._trg_data_pipeline.meta["language"],
**args[name + ".params"])