Source code for transformers.configuration_longformer

# coding=utf-8
# Copyright 2020 The Allen Institute for AI team and The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
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""" Longformer configuration """

from typing import List, Union

from .configuration_roberta import RobertaConfig
from .utils import logging


logger = logging.get_logger(__name__)

LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP = {
    "allenai/longformer-base-4096": "https://s3.amazonaws.com/models.huggingface.co/bert/allenai/longformer-base-4096/config.json",
    "allenai/longformer-large-4096": "https://s3.amazonaws.com/models.huggingface.co/bert/allenai/longformer-large-4096/config.json",
    "allenai/longformer-large-4096-finetuned-triviaqa": "https://s3.amazonaws.com/models.huggingface.co/bert/allenai/longformer-large-4096-finetuned-triviaqa/config.json",
    "allenai/longformer-base-4096-extra.pos.embd.only": "https://s3.amazonaws.com/models.huggingface.co/bert/allenai/longformer-base-4096-extra.pos.embd.only/config.json",
    "allenai/longformer-large-4096-extra.pos.embd.only": "https://s3.amazonaws.com/models.huggingface.co/bert/allenai/longformer-large-4096-extra.pos.embd.only/config.json",
}


class LongformerConfig(RobertaConfig):
    r"""
    This is the configuration class to store the configuration of a :class:`~transformers.LongformerModel`.
    It is used to instantiate an Longformer model according to the specified arguments, defining the model
    architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of
    the RoBERTa `roberta-base <https://huggingface.co/roberta-base>`__ architecture with a sequence length 4,096.

    The :class:`~transformers.LongformerConfig` class directly inherits :class:`~transformers.RobertaConfig`.
    It reuses the same defaults. Please check the parent class for more information.

    Args:
        attention_window (:obj:`int` or :obj:`List[int]`, optional, defaults to 512):
            Size of an attention window around each token. If :obj:`int`, use the same size for all layers.
            To specify a different window size for each layer, use a :obj:`List[int]` where
            ``len(attention_window) == num_hidden_layers``.

    Example::

        >>> from transformers import LongformerConfig, LongformerModel

        >>> # Initializing a Longformer configuration
        >>> configuration = LongformerConfig()

        >>> # Initializing a model from the configuration
        >>> model = LongformerModel(configuration)

        >>> # Accessing the model configuration
        >>> configuration = model.config
    """
    model_type = "longformer"

    def __init__(self, attention_window: Union[List[int], int] = 512, sep_token_id: int = 2, **kwargs):
        super().__init__(**kwargs)
        self.attention_window = attention_window
        self.sep_token_id = sep_token_id