Source code for transformers.modeling_xlm_roberta

# coding=utf-8
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"""PyTorch XLM-RoBERTa model. """

from .configuration_xlm_roberta import XLMRobertaConfig
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__)

XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST = [
    "xlm-roberta-base",
    "xlm-roberta-large",
    "xlm-roberta-large-finetuned-conll02-dutch",
    "xlm-roberta-large-finetuned-conll02-spanish",
    "xlm-roberta-large-finetuned-conll03-english",
    "xlm-roberta-large-finetuned-conll03-german",
    # See all XLM-RoBERTa models at https://huggingface.co/models?filter=xlm-roberta
]


XLM_ROBERTA_START_DOCSTRING = r"""

    This model is a PyTorch `torch.nn.Module <https://pytorch.org/docs/stable/nn.html#torch.nn.Module>`_ sub-class.
    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.XLMRobertaConfig`): 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.
"""


[docs]@add_start_docstrings( "The bare XLM-RoBERTa Model transformer outputting raw hidden-states without any specific head on top.", XLM_ROBERTA_START_DOCSTRING, ) class XLMRobertaModel(RobertaModel): """ This class overrides :class:`~transformers.RobertaModel`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = XLMRobertaConfig
[docs]@add_start_docstrings( "XLM-RoBERTa Model with a `language modeling` head on top for CLM fine-tuning.", XLM_ROBERTA_START_DOCSTRING, ) class XLMRobertaForCausalLM(RobertaForCausalLM): """ This class overrides :class:`~transformers.RobertaForCausalLM`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = XLMRobertaConfig
[docs]@add_start_docstrings( """XLM-RoBERTa Model with a `language modeling` head on top. """, XLM_ROBERTA_START_DOCSTRING, ) class XLMRobertaForMaskedLM(RobertaForMaskedLM): """ This class overrides :class:`~transformers.RobertaForMaskedLM`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = XLMRobertaConfig
[docs]@add_start_docstrings( """XLM-RoBERTa Model transformer with a sequence classification/regression head on top (a linear layer on top of the pooled output) e.g. for GLUE tasks. """, XLM_ROBERTA_START_DOCSTRING, ) class XLMRobertaForSequenceClassification(RobertaForSequenceClassification): """ This class overrides :class:`~transformers.RobertaForSequenceClassification`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = XLMRobertaConfig
[docs]@add_start_docstrings( """XLM-RoBERTa 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. """, XLM_ROBERTA_START_DOCSTRING, ) class XLMRobertaForMultipleChoice(RobertaForMultipleChoice): """ This class overrides :class:`~transformers.RobertaForMultipleChoice`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = XLMRobertaConfig
[docs]@add_start_docstrings( """XLM-RoBERTa 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. """, XLM_ROBERTA_START_DOCSTRING, ) class XLMRobertaForTokenClassification(RobertaForTokenClassification): """ This class overrides :class:`~transformers.RobertaForTokenClassification`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = XLMRobertaConfig
[docs]@add_start_docstrings( """XLM-RoBERTa 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`).""", XLM_ROBERTA_START_DOCSTRING, ) class XLMRobertaForQuestionAnswering(RobertaForQuestionAnswering): """ This class overrides :class:`~transformers.RobertaForQuestionAnswering`. Please check the superclass for the appropriate documentation alongside usage examples. """ config_class = XLMRobertaConfig