Commit 40ac340b authored by Liezl Puzon's avatar Liezl Puzon Committed by Facebook Github Bot
Browse files

Eval and log on a subset of directions for multimodel training (#605) 

Summary:
Pull Request resolved: https://github.com/pytorch/fairseq/pull/605

Eval and log on a subset of directions for multimodel training

This reduces code duplication in PyTorch Translate's semi_supervised task and will enable clean multitask setups in the future.

Reviewed By: pipibjc, dpacgopinath

Differential Revision: D14672779

fbshipit-source-id: 1342c71781f0824cc56a38ad1c1822e34eaef337
parent f492db25

fairseq/tasks/multilingual_translation.py

+8 −2
Original line number Diff line number Diff line
@@ -77,6 +77,12 @@ class MultilingualTranslationTask(FairseqTask): 
        super().__init__(args)

        self.dicts = dicts

        self.lang_pairs = args.lang_pairs

        # eval_lang_pairs for multilingual translation is usually all of the

        # lang_pairs. However for other multitask settings or when we want to

        # optimize for certain languages we want to use a different subset. Thus

        # the eval_lang_pairs class variable is provided for classes that extend

        # this class.

        self.eval_lang_pairs = args.lang_pairs

        self.langs = list(dicts.keys())

        self.training = training
@@ -205,7 +211,7 @@ class MultilingualTranslationTask(FairseqTask): 
        model.eval()

        with torch.no_grad():

            agg_loss, agg_sample_size, agg_logging_output = 0., 0., {}

            for lang_pair in self.args.lang_pairs:

            for lang_pair in self.eval_lang_pairs:

                if sample[lang_pair] is None or len(sample[lang_pair]) == 0:

                    continue

                loss, sample_size, logging_output = criterion(model.models[lang_pair], sample[lang_pair])
@@ -236,7 +242,7 @@ class MultilingualTranslationTask(FairseqTask): 
            lang_pair: criterion.__class__.aggregate_logging_outputs([

                logging_output.get(lang_pair, {}) for logging_output in logging_outputs

            ])

            for lang_pair in self.args.lang_pairs

            for lang_pair in self.eval_lang_pairs

        }



        def sum_over_languages(key):