# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Unsupervised Cross-lingual Representation Learning at Scale
"""

from fairseq.models import register_model

from .hub_interface import RobertaHubInterface
from .model import RobertaModel


@register_model("xlmr")
class XLMRModel(RobertaModel):
    @classmethod
    def hub_models(cls):
        return {
            "xlmr.base": "http://dl.fbaipublicfiles.com/fairseq/models/xlmr.base.tar.gz",
            "xlmr.large": "http://dl.fbaipublicfiles.com/fairseq/models/xlmr.large.tar.gz",
            "xlmr.xl": "http://dl.fbaipublicfiles.com/fairseq/models/xlmr/xlmr.xl.tar.gz",
            "xlmr.xxl": "http://dl.fbaipublicfiles.com/fairseq/models/xlmr/xlmr.xxl.tar.gz",
        }

    @classmethod
    def from_pretrained(
        cls,
        model_name_or_path,
        checkpoint_file="model.pt",
        data_name_or_path=".",
        bpe="sentencepiece",
        **kwargs
    ):
        from fairseq import hub_utils

        x = hub_utils.from_pretrained(
            model_name_or_path,
            checkpoint_file,
            data_name_or_path,
            archive_map=cls.hub_models(),
            bpe=bpe,
            load_checkpoint_heads=True,
            **kwargs,
        )
        return RobertaHubInterface(x["args"], x["task"], x["models"][0])