codingutf8 2010 dpr s the hugging face 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 dpr model configuration from configurationutils import pretrainedconfig from utils import logging logger logging getloggername dprpretrainedconfigarchivemap facebookdprctxencodersinglenqbase https huggingface cofacebookdprctxencodersinglenqbaseresolvemainconfig json facebookdprquestionencodersinglenqbase https huggingface cofacebookdprquestionencodersinglenqbaseresolvemainconfig json facebookdprreadersinglenqbase https huggingface cofacebookdprreadersinglenqbaseresolvemainconfig json facebookdprctxencodermultisetbase https huggingface cofacebookdprctxencodermultisetbaseresolvemainconfig json facebookdprquestionencodermultisetbase https huggingface cofacebookdprquestionencodermultisetbaseresolvemainconfig json facebookdprreadermultisetbase https huggingface cofacebookdprreadermultisetbaseresolvemainconfig json class dprconfigpretrainedconfig r dprconfig is the configuration class to store the configuration of a dprmodel this is the configuration class to store the configuration of a dprcontextencoder dprquestionencoder or a dprreader it is used to instantiate the components of the dpr model according to the specified arguments defining the model component architectures instantiating a configuration with the defaults will yield a similar configuration to that of the dprcontextencoder facebookdprctxencodersinglenqbasehttps huggingface cofacebookdprctxencodersinglenqbase architecture this class is a subclass of bertconfig please check the superclass for the documentation of all kwargs args vocabsize int optional defaults to 30522 vocabulary size of the dpr model defines the different tokens that can be represented by the inputsids passed to the forward method of bertmodel hiddensize int optional defaults to 768 dimensionality 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 dimensionality 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 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 into bertmodel 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 padtokenid int optional defaults to 0 padding token id positionembeddingtype str optional defaults to absolute type of position embedding choose one of absolute relativekey relativekeyquery for positional embeddings use absolute for more information on relativekey please refer to selfattention with relative position representations shaw et al https arxiv orgabs1803 02155 for more information on relativekeyquery please refer to method 4 in improve transformer models with better relative position embeddings huang et al https arxiv orgabs2009 13658 projectiondim int optional defaults to 0 dimension of the projection for the context and question encoders if it is set to zero default then no projection is done example python from transformers import dprconfig dprcontextencoder initializing a dpr facebookdprctxencodersinglenqbase style configuration configuration dprconfig initializing a model with random weights from the facebookdprctxencodersinglenqbase style configuration model dprcontextencoderconfiguration accessing the model configuration configuration model config modeltype dpr def init self vocabsize30522 hiddensize768 numhiddenlayers12 numattentionheads12 intermediatesize3072 hiddenactgelu hiddendropoutprob0 1 attentionprobsdropoutprob0 1 maxpositionembeddings512 typevocabsize2 initializerrange0 02 layernormeps1e12 padtokenid0 positionembeddingtypeabsolute projectiondim int 0 kwargs super initpadtokenidpadtokenid kwargs self vocabsize vocabsize self hiddensize hiddensize self numhiddenlayers numhiddenlayers self numattentionheads numattentionheads self hiddenact hiddenact self intermediatesize intermediatesize self hiddendropoutprob hiddendropoutprob self attentionprobsdropoutprob attentionprobsdropoutprob self maxpositionembeddings maxpositionembeddings self typevocabsize typevocabsize self initializerrange initializerrange self layernormeps layernormeps self projectiondim projectiondim self positionembeddingtype positionembeddingtype coding utf 8 2010 dpr s the hugging face 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 dpr model configuration dprconfig is the configuration class to store the configuration of a dprmodel this is the configuration class to store the configuration of a dprcontextencoder dprquestionencoder or a dprreader it is used to instantiate the components of the dpr model according to the specified arguments defining the model component architectures instantiating a configuration with the defaults will yield a similar configuration to that of the dprcontextencoder facebook dpr ctx_encoder single nq base https huggingface co facebook dpr ctx_encoder single nq base architecture this class is a subclass of bertconfig please check the superclass for the documentation of all kwargs args vocab_size int optional defaults to 30522 vocabulary size of the dpr model defines the different tokens that can be represented by the inputs_ids passed to the forward method of bertmodel hidden_size int optional defaults to 768 dimensionality 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 dimensionality 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 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 into bertmodel 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 pad_token_id int optional defaults to 0 padding token id position_embedding_type str optional defaults to absolute type of position embedding choose one of absolute relative_key relative_key_query for positional embeddings use absolute for more information on relative_key please refer to self attention with relative position representations shaw et al https arxiv org abs 1803 02155 for more information on relative_key_query please refer to method 4 in improve transformer models with better relative position embeddings huang et al https arxiv org abs 2009 13658 projection_dim int optional defaults to 0 dimension of the projection for the context and question encoders if it is set to zero default then no projection is done example python from transformers import dprconfig dprcontextencoder initializing a dpr facebook dpr ctx_encoder single nq base style configuration configuration dprconfig initializing a model with random weights from the facebook dpr ctx_encoder single nq base style configuration model dprcontextencoder configuration accessing the model configuration configuration model config
from ...configuration_utils import PretrainedConfig
from ...utils import logging


logger = logging.get_logger(__name__)

DPR_PRETRAINED_CONFIG_ARCHIVE_MAP = {
    "facebook/dpr-ctx_encoder-single-nq-base": (
        "https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json"
    ),
    "facebook/dpr-question_encoder-single-nq-base": (
        "https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json"
    ),
    "facebook/dpr-reader-single-nq-base": (
        "https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json"
    ),
    "facebook/dpr-ctx_encoder-multiset-base": (
        "https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json"
    ),
    "facebook/dpr-question_encoder-multiset-base": (
        "https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json"
    ),
    "facebook/dpr-reader-multiset-base": (
        "https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json"
    ),
}


class DPRConfig(PretrainedConfig):
    r

    model_type = "dpr"

    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,
        pad_token_id=0,
        position_embedding_type="absolute",
        projection_dim: int = 0,
        **kwargs,
    ):
        super().__init__(pad_token_id=pad_token_id, **kwargs)

        self.vocab_size = vocab_size
        self.hidden_size = hidden_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.projection_dim = projection_dim
        self.position_embedding_type = position_embedding_type