def translate_valid():
translations_fn = output_files_dict["valid_translation_output"] # save_prefix + ".test.out"
control_src_fn = output_files_dict["valid_src_output"] # save_prefix + ".test.src.out"
return translate_to_file(encdec, eos_idx, valid_src_data, mb_size, tgt_indexer,
translations_fn, test_references=valid_references, control_src_fn=control_src_fn,
src_indexer=src_indexer, gpu=gpu, nb_steps=50, reverse_src=reverse_src, reverse_tgt=reverse_tgt,
s_unk_tag=s_unk_tag, t_unk_tag=t_unk_tag)
def __call__(self, trainer):
encdec = trainer.updater.get_optimizer("main").target
# translations_fn = output_files_dict["dev_translation_output"] #save_prefix + ".test.out"
# control_src_fn = output_files_dict["dev_src_output"] #save_prefix + ".test.src.out"
bleu_stats = translate_to_file(encdec,
self.eos_idx,
self.src_data,
self.mb_size,
self.tgt_indexer,
self.translations_fn,
test_references=self.references,
control_src_fn=self.control_src_fn,
src_indexer=self.src_indexer,
gpu=self.gpu,
nb_steps=50,
reverse_src=self.reverse_src,
reverse_tgt=self.reverse_tgt,
s_unk_tag=self.s_unk_tag,
t_unk_tag=self.t_unk_tag)
bleu = bleu_stats.bleu()
chainer.reporter.report({
self.observation_name: bleu,
self.observation_name + "_details": repr(bleu)
})
if self.best_bleu is None or self.best_bleu < bleu:
log.info("%s improvement: %r -> %r" %
(self.observation_name, self.best_bleu, bleu))
self.best_bleu = bleu
if self.save_best_model_to is not None:
log.info("saving best bleu (%s) model to %s" % (
self.observation_name,
self.save_best_model_to,
))
serializers.save_npz(self.save_best_model_to, encdec)
if self.config_training is not None:
config_session = self.config_training.copy(readonly=False)
config_session.add_section("model_parameters",
keep_at_bottom="metadata")
config_session["model_parameters"][
"filename"] = self.save_best_model_to
config_session["model_parameters"]["type"] = "model"
config_session["model_parameters"][
"description"] = "best_bleu"
config_session["model_parameters"][
"infos"] = argument_parsing_tools.OrderedNamespace()
config_session["model_parameters"]["infos"][
"bleu_stats"] = str(bleu_stats)
config_session["model_parameters"]["infos"][
"iteration"] = trainer.updater.iteration
config_session.set_metadata_modified_time()
config_session.save_to(self.save_best_model_to + ".config")
# json.dump(config_session, open(self.save_best_model_to + ".config",
# "w"), indent=2, separators=(',', ': '))
else:
log.info("no bleu (%s) improvement: %f >= %f" %
(self.observation_name, self.best_bleu, bleu))