# coding=utf-8
# Copyright 2019 Inria, Facebook AI Research and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION.  All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
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# distributed under the License is distributed on an "AS IS" BASIS,
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"""PyTorch CamemBERT model. """

from .configuration_camembert import CamembertConfig
from .file_utils import add_start_docstrings
from .modeling_roberta import (
    RobertaForCausalLM,
    RobertaForMaskedLM,
    RobertaForMultipleChoice,
    RobertaForQuestionAnswering,
    RobertaForSequenceClassification,
    RobertaForTokenClassification,
    RobertaModel,
)
from .utils import logging


logger = logging.get_logger(__name__)

_TOKENIZER_FOR_DOC = "CamembertTokenizer"

CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST = [
    "camembert-base",
    "Musixmatch/umberto-commoncrawl-cased-v1",
    "Musixmatch/umberto-wikipedia-uncased-v1",
    # See all CamemBERT models at https://huggingface.co/models?filter=camembert
]

CAMEMBERT_START_DOCSTRING = r"""

    This model inherits from :class:`~transformers.PreTrainedModel`. Check the superclass documentation for the generic
    methods the library implements for all its model (such as downloading or saving, resizing the input embeddings,
    pruning heads etc.)

    This model is also a PyTorch `torch.nn.Module <https://pytorch.org/docs/stable/nn.html#torch.nn.Module>`__ subclass.
    Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general
    usage and behavior.

    Parameters:
        config (:class:`~transformers.CamembertConfig`): Model configuration class with all the parameters of the
            model. Initializing with a config file does not load the weights associated with the model, only the
            configuration.
            Check out the :meth:`~transformers.PreTrainedModel.from_pretrained` method to load the model weights.
"""


@add_start_docstrings(
    "The bare CamemBERT Model transformer outputting raw hidden-states without any specific head on top.",
    CAMEMBERT_START_DOCSTRING,
)
class CamembertModel(RobertaModel):
    """
    This class overrides :class:`~transformers.RobertaModel`. Please check the
    superclass for the appropriate documentation alongside usage examples.
    """

    config_class = CamembertConfig


@add_start_docstrings(
    """CamemBERT Model with a `language modeling` head on top. """,
    CAMEMBERT_START_DOCSTRING,
)
class CamembertForMaskedLM(RobertaForMaskedLM):
    """
    This class overrides :class:`~transformers.RobertaForMaskedLM`. Please check the
    superclass for the appropriate documentation alongside usage examples.
    """

    config_class = CamembertConfig


@add_start_docstrings(
    """CamemBERT Model transformer with a sequence classification/regression head on top (a linear layer
    on top of the pooled output) e.g. for GLUE tasks. """,
    CAMEMBERT_START_DOCSTRING,
)
class CamembertForSequenceClassification(RobertaForSequenceClassification):
    """
    This class overrides :class:`~transformers.RobertaForSequenceClassification`. Please check the
    superclass for the appropriate documentation alongside usage examples.
    """

    config_class = CamembertConfig


@add_start_docstrings(
    """CamemBERT Model with a multiple choice classification head on top (a linear layer on top of
    the pooled output and a softmax) e.g. for RocStories/SWAG tasks. """,
    CAMEMBERT_START_DOCSTRING,
)
class CamembertForMultipleChoice(RobertaForMultipleChoice):
    """
    This class overrides :class:`~transformers.RobertaForMultipleChoice`. Please check the
    superclass for the appropriate documentation alongside usage examples.
    """

    config_class = CamembertConfig


@add_start_docstrings(
    """CamemBERT Model with a token classification head on top (a linear layer on top of
    the hidden-states output) e.g. for Named-Entity-Recognition (NER) tasks. """,
    CAMEMBERT_START_DOCSTRING,
)
class CamembertForTokenClassification(RobertaForTokenClassification):
    """
    This class overrides :class:`~transformers.RobertaForTokenClassification`. Please check the
    superclass for the appropriate documentation alongside usage examples.
    """

    config_class = CamembertConfig


@add_start_docstrings(
    """CamemBERT Model with a span classification head on top for extractive question-answering tasks like SQuAD
    (a linear layers on top of the hidden-states output to compute `span start logits` and `span end logits` """,
    CAMEMBERT_START_DOCSTRING,
)
class CamembertForQuestionAnswering(RobertaForQuestionAnswering):
    """
    This class overrides :class:`~transformers.RobertaForQuestionAnswering`. Please check the
    superclass for the appropriate documentation alongside usage examples.
    """

    config_class = CamembertConfig


@add_start_docstrings(
    """CamemBERT Model with a `language modeling` head on top for CLM fine-tuning. """, CAMEMBERT_START_DOCSTRING
)
class CamembertForCausalLM(RobertaForCausalLM):
    """
    This class overrides :class:`~transformers.RobertaForCausalLM`. Please check the
    superclass for the appropriate documentation alongside usage examples.
    """

    config_class = CamembertConfig
