codingutf8 2021 nvidia corporation 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 megatronbert model configuration from configurationutils import pretrainedconfig from utils import logging logger logging getloggername megatronbertpretrainedconfigarchivemap see all megatronbert models at https huggingface comodels filterbert class megatronbertconfigpretrainedconfig r this is the configuration class to store the configuration of a megatronbertmodel it is used to instantiate a megatronbert 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 megatronbert nvidiamegatronbertuncased345mhttps huggingface convidiamegatronbertuncased345m 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 29056 vocabulary size of the megatronbert model defines the number of different tokens that can be represented by the inputsids passed when calling megatronbertmodel hiddensize int optional defaults to 1024 dimensionality of the encoder layers and the pooler layer numhiddenlayers int optional defaults to 24 number of hidden layers in the transformer encoder numattentionheads int optional defaults to 16 number of attention heads for each attention layer in the transformer encoder intermediatesize int optional defaults to 4096 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 megatronbertmodel 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 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 isdecoder bool optional defaults to false whether the model is used as a decoder or not if false the model is used as an encoder 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 examples python from transformers import megatronbertconfig megatronbertmodel initializing a megatronbert bertbaseuncased style configuration configuration megatronbertconfig initializing a model with random weights from the bertbaseuncased style configuration model megatronbertmodelconfiguration accessing the model configuration configuration model config modeltype megatronbert def init self vocabsize29056 hiddensize1024 numhiddenlayers24 numattentionheads16 intermediatesize4096 hiddenactgelu hiddendropoutprob0 1 attentionprobsdropoutprob0 1 maxpositionembeddings512 typevocabsize2 initializerrange0 02 layernormeps1e12 padtokenid0 positionembeddingtypeabsolute usecachetrue 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 positionembeddingtype positionembeddingtype self usecache usecache coding utf 8 2021 nvidia corporation 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 megatron_bert model configuration see all megatron_bert models at https huggingface co models filter bert this is the configuration class to store the configuration of a megatronbertmodel it is used to instantiate a megatron_bert 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 megatron_bert nvidia megatron bert uncased 345m https huggingface co nvidia megatron bert uncased 345m 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 29056 vocabulary size of the megatron_bert model defines the number of different tokens that can be represented by the inputs_ids passed when calling megatronbertmodel hidden_size int optional defaults to 1024 dimensionality of the encoder layers and the pooler layer num_hidden_layers int optional defaults to 24 number of hidden layers in the transformer encoder num_attention_heads int optional defaults to 16 number of attention heads for each attention layer in the transformer encoder intermediate_size int optional defaults to 4096 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 megatronbertmodel 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 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 is_decoder bool optional defaults to false whether the model is used as a decoder or not if false the model is used as an encoder 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 examples python from transformers import megatronbertconfig megatronbertmodel initializing a megatron_bert bert base uncased style configuration configuration megatronbertconfig initializing a model with random weights from the bert base uncased style configuration model megatronbertmodel configuration accessing the model configuration configuration model config
from ...configuration_utils import PretrainedConfig
from ...utils import logging


logger = logging.get_logger(__name__)

MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
    
}


class MegatronBertConfig(PretrainedConfig):
    r

    model_type = "megatron-bert"

    def __init__(
        self,
        vocab_size=29056,
        hidden_size=1024,
        num_hidden_layers=24,
        num_attention_heads=16,
        intermediate_size=4096,
        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",
        use_cache=True,
        **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.position_embedding_type = position_embedding_type
        self.use_cache = use_cache