codingutf8 2021 tel aviv university allenai 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 splinter model configuration from configurationutils import pretrainedconfig from utils import logging logger logging getloggername splinterpretrainedconfigarchivemap tausplinterbase https huggingface cotausplinterbaseresolvemainconfig json tausplinterbaseqass https huggingface cotausplinterbaseqassresolvemainconfig json tausplinterlarge https huggingface cotausplinterlargeresolvemainconfig json tausplinterlargeqass https huggingface cotausplinterlargeqassresolvemainconfig json see all splinter models at https huggingface comodels filtersplinter class splinterconfigpretrainedconfig r this is the configuration class to store the configuration of a splintermodel it is used to instantiate an splinter 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 splinter tausplinterbasehttps huggingface cotausplinterbase 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 30522 vocabulary size of the splinter model defines the number of different tokens that can be represented by the inputsids passed when calling splintermodel hiddensize int optional defaults to 768 dimension of the encoder layers and the pooler layer 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 dimension of the intermediate i e feedforward layer in the transformer encoder hiddenact str or function optional defaults to gelu the nonlinear activation function function or string in the encoder and pooler if string gelu relu selu and gelunew are supported hiddendropoutprob float optional defaults to 0 1 the dropout probabilitiy 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 splintermodel 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 usecache bool optional defaults to true whether or not the model should return the last keyvalues attentions not used by all models only relevant if config isdecodertrue questiontokenid int optional defaults to 104 the id of the question token example python from transformers import splintermodel splinterconfig initializing a splinter tausplinterbase style configuration configuration splinterconfig initializing a model from the tausplinterbase style configuration model splintermodelconfiguration accessing the model configuration configuration model config modeltype splinter def init self vocabsize30522 hiddensize768 numhiddenlayers12 numattentionheads12 intermediatesize3072 hiddenactgelu hiddendropoutprob0 1 attentionprobsdropoutprob0 1 maxpositionembeddings512 typevocabsize2 initializerrange0 02 layernormeps1e12 usecachetrue padtokenid0 questiontokenid104 kwargs super initpadtokenidpadtokenid kwargs self vocabsize vocabsize self maxpositionembeddings maxpositionembeddings self hiddensize hiddensize self numhiddenlayers numhiddenlayers self numattentionheads numattentionheads self intermediatesize intermediatesize self hiddenact hiddenact self hiddendropoutprob hiddendropoutprob self attentionprobsdropoutprob attentionprobsdropoutprob self initializerrange initializerrange self typevocabsize typevocabsize self layernormeps layernormeps self usecache usecache self questiontokenid questiontokenid coding utf 8 2021 tel aviv university allenai 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 splinter model configuration see all splinter models at https huggingface co models filter splinter this is the configuration class to store the configuration of a splintermodel it is used to instantiate an splinter 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 splinter tau splinter base https huggingface co tau splinter 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 30522 vocabulary size of the splinter model defines the number of different tokens that can be represented by the inputs_ids passed when calling splintermodel hidden_size int optional defaults to 768 dimension of the encoder layers and the pooler layer 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 dimension of the intermediate i e feed forward layer in the transformer encoder hidden_act str or function optional defaults to gelu the non linear activation function function or string in the encoder and pooler if string gelu relu selu and gelu_new are supported hidden_dropout_prob float optional defaults to 0 1 the dropout probabilitiy 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 splintermodel 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_cache bool optional defaults to true whether or not the model should return the last key values attentions not used by all models only relevant if config is_decoder true question_token_id int optional defaults to 104 the id of the question token example python from transformers import splintermodel splinterconfig initializing a splinter tau splinter base style configuration configuration splinterconfig initializing a model from the tau splinter base style configuration model splintermodel configuration accessing the model configuration configuration model config
from ...configuration_utils import PretrainedConfig
from ...utils import logging


logger = logging.get_logger(__name__)

SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP = {
    "tau/splinter-base": "https://huggingface.co/tau/splinter-base/resolve/main/config.json",
    "tau/splinter-base-qass": "https://huggingface.co/tau/splinter-base-qass/resolve/main/config.json",
    "tau/splinter-large": "https://huggingface.co/tau/splinter-large/resolve/main/config.json",
    "tau/splinter-large-qass": "https://huggingface.co/tau/splinter-large-qass/resolve/main/config.json",
    
}


class SplinterConfig(PretrainedConfig):
    r

    model_type = "splinter"

    def __init__(
        self,
        vocab_size=30522,
        hidden_size=768,
        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_cache=True,
        pad_token_id=0,
        question_token_id=104,
        **kwargs,
    ):
        super().__init__(pad_token_id=pad_token_id, **kwargs)

        self.vocab_size = vocab_size
        self.max_position_embeddings = max_position_embeddings
        self.hidden_size = hidden_size
        self.num_hidden_layers = num_hidden_layers
        self.num_attention_heads = num_attention_heads
        self.intermediate_size = intermediate_size
        self.hidden_act = hidden_act
        self.hidden_dropout_prob = hidden_dropout_prob
        self.attention_probs_dropout_prob = attention_probs_dropout_prob
        self.initializer_range = initializer_range
        self.type_vocab_size = type_vocab_size
        self.layer_norm_eps = layer_norm_eps
        self.use_cache = use_cache
        self.question_token_id = question_token_id