codingutf8 studio ousia 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 you may obtain a copy of the license at http www apache orglicenseslicense2 0 unless required by applicable law or agreed to in writing software distributed under the license is distributed on an as is basis without warranties or conditions of any kind either express or implied see the license for the specific language governing permissions and limitations under the license luke configuration from configurationutils import pretrainedconfig from utils import logging logger logging getloggername lukepretrainedconfigarchivemap studioousialukebase https huggingface costudioousialukebaseresolvemainconfig json studioousialukelarge https huggingface costudioousialukelargeresolvemainconfig json class lukeconfigpretrainedconfig r this is the configuration class to store the configuration of a lukemodel it is used to instantiate a luke 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 luke studioousialukebasehttps huggingface costudioousialukebase architecture configuration objects inherit from pretrainedconfig and can be used to control the model outputs read the documentation from pretrainedconfig for more information args vocabsize int optional defaults to 50267 vocabulary size of the luke model defines the number of different tokens that can be represented by the inputsids passed when calling lukemodel entityvocabsize int optional defaults to 500000 entity vocabulary size of the luke model defines the number of different entities that can be represented by the entityids passed when calling lukemodel hiddensize int optional defaults to 768 dimensionality of the encoder layers and the pooler layer entityembsize int optional defaults to 256 the number of dimensions of the entity embedding numhiddenlayers int optional defaults to 12 number of hidden layers in the transformer encoder numattentionheads int optional defaults to 12 number of attention heads for each attention layer in the transformer encoder intermediatesize int optional defaults to 3072 dimensionality of the intermediate often named feedforward layer in the transformer encoder hiddenact str or callable optional defaults to gelu the nonlinear activation function function or string in the encoder and pooler if string gelu relu silu and gelunew are supported hiddendropoutprob float optional defaults to 0 1 the dropout probability for all fully connected layers in the embeddings encoder and pooler attentionprobsdropoutprob float optional defaults to 0 1 the dropout ratio for the attention probabilities maxpositionembeddings int optional defaults to 512 the maximum sequence length that this model might ever be used with typically set this to something large just in case e g 512 or 1024 or 2048 typevocabsize int optional defaults to 2 the vocabulary size of the tokentypeids passed when calling lukemodel initializerrange float optional defaults to 0 02 the standard deviation of the truncatednormalinitializer for initializing all weight matrices layernormeps float optional defaults to 1e12 the epsilon used by the layer normalization layers useentityawareattention bool optional defaults to true whether or not the model should use the entityaware selfattention mechanism proposed in luke deep contextualized entity representations with entityaware selfattention yamada et al https arxiv orgabs2010 01057 classifierdropout float optional the dropout ratio for the classification head padtokenid int optional defaults to 1 padding token id bostokenid int optional defaults to 0 beginning of stream token id eostokenid int optional defaults to 2 end of stream token id examples python from transformers import lukeconfig lukemodel initializing a luke configuration configuration lukeconfig initializing a model from the configuration model lukemodelconfiguration accessing the model configuration configuration model config modeltype luke def init self vocabsize50267 entityvocabsize500000 hiddensize768 entityembsize256 numhiddenlayers12 numattentionheads12 intermediatesize3072 hiddenactgelu hiddendropoutprob0 1 attentionprobsdropoutprob0 1 maxpositionembeddings512 typevocabsize2 initializerrange0 02 layernormeps1e12 useentityawareattentiontrue classifierdropoutnone padtokenid1 bostokenid0 eostokenid2 kwargs coding utf 8 studio ousia 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 you may obtain a copy of the license at http www apache org licenses license 2 0 unless required by applicable law or agreed to in writing software distributed under the license is distributed on an as is basis without warranties or conditions of any kind either express or implied see the license for the specific language governing permissions and limitations under the license luke configuration this is the configuration class to store the configuration of a lukemodel it is used to instantiate a luke 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 luke studio ousia luke base https huggingface co studio ousia luke base architecture configuration objects inherit from pretrainedconfig and can be used to control the model outputs read the documentation from pretrainedconfig for more information args vocab_size int optional defaults to 50267 vocabulary size of the luke model defines the number of different tokens that can be represented by the inputs_ids passed when calling lukemodel entity_vocab_size int optional defaults to 500000 entity vocabulary size of the luke model defines the number of different entities that can be represented by the entity_ids passed when calling lukemodel hidden_size int optional defaults to 768 dimensionality of the encoder layers and the pooler layer entity_emb_size int optional defaults to 256 the number of dimensions of the entity embedding num_hidden_layers int optional defaults to 12 number of hidden layers in the transformer encoder num_attention_heads int optional defaults to 12 number of attention heads for each attention layer in the transformer encoder intermediate_size int optional defaults to 3072 dimensionality of the intermediate often named feed forward layer in the transformer encoder hidden_act str or callable optional defaults to gelu the non linear activation function function or string in the encoder and pooler if string gelu relu silu and gelu_new are supported hidden_dropout_prob float optional defaults to 0 1 the dropout probability for all fully connected layers in the embeddings encoder and pooler attention_probs_dropout_prob float optional defaults to 0 1 the dropout ratio for the attention probabilities max_position_embeddings int optional defaults to 512 the maximum sequence length that this model might ever be used with typically set this to something large just in case e g 512 or 1024 or 2048 type_vocab_size int optional defaults to 2 the vocabulary size of the token_type_ids passed when calling lukemodel initializer_range float optional defaults to 0 02 the standard deviation of the truncated_normal_initializer for initializing all weight matrices layer_norm_eps float optional defaults to 1e 12 the epsilon used by the layer normalization layers use_entity_aware_attention bool optional defaults to true whether or not the model should use the entity aware self attention mechanism proposed in luke deep contextualized entity representations with entity aware self attention yamada et al https arxiv org abs 2010 01057 classifier_dropout float optional the dropout ratio for the classification head pad_token_id int optional defaults to 1 padding token id bos_token_id int optional defaults to 0 beginning of stream token id eos_token_id int optional defaults to 2 end of stream token id examples python from transformers import lukeconfig lukemodel initializing a luke configuration configuration lukeconfig initializing a model from the configuration model lukemodel configuration accessing the model configuration configuration model config constructs lukeconfig
from ...configuration_utils import PretrainedConfig
from ...utils import logging


logger = logging.get_logger(__name__)

LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP = {
    "studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
    "studio-ousia/luke-large": "https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json",
}


class LukeConfig(PretrainedConfig):
    r

    model_type = "luke"

    def __init__(
        self,
        vocab_size=50267,
        entity_vocab_size=500000,
        hidden_size=768,
        entity_emb_size=256,
        num_hidden_layers=12,
        num_attention_heads=12,
        intermediate_size=3072,
        hidden_act="gelu",
        hidden_dropout_prob=0.1,
        attention_probs_dropout_prob=0.1,
        max_position_embeddings=512,
        type_vocab_size=2,
        initializer_range=0.02,
        layer_norm_eps=1e-12,
        use_entity_aware_attention=True,
        classifier_dropout=None,
        pad_token_id=1,
        bos_token_id=0,
        eos_token_id=2,
        **kwargs,
    ):
        
        super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)

        self.vocab_size = vocab_size
        self.entity_vocab_size = entity_vocab_size
        self.hidden_size = hidden_size
        self.entity_emb_size = entity_emb_size
        self.num_hidden_layers = num_hidden_layers
        self.num_attention_heads = num_attention_heads
        self.hidden_act = hidden_act
        self.intermediate_size = intermediate_size
        self.hidden_dropout_prob = hidden_dropout_prob
        self.attention_probs_dropout_prob = attention_probs_dropout_prob
        self.max_position_embeddings = max_position_embeddings
        self.type_vocab_size = type_vocab_size
        self.initializer_range = initializer_range
        self.layer_norm_eps = layer_norm_eps
        self.use_entity_aware_attention = use_entity_aware_attention
        self.classifier_dropout = classifier_dropout