U &ºcÐ!ã@shdZddlZddlmZe e¡Zddddd d d d d ddddddddddddddœZGdd„deƒZdS)z BERT model configuration éNé)ÚPretrainedConfigzQhttps://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-config.jsonzRhttps://s3.amazonaws.com/models.huggingface.co/bert/bert-large-uncased-config.jsonzOhttps://s3.amazonaws.com/models.huggingface.co/bert/bert-base-cased-config.jsonzPhttps://s3.amazonaws.com/models.huggingface.co/bert/bert-large-cased-config.jsonz^https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-multilingual-uncased-config.jsonz\https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-multilingual-cased-config.jsonzQhttps://s3.amazonaws.com/models.huggingface.co/bert/bert-base-chinese-config.jsonzVhttps://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-cased-config.jsonzehttps://s3.amazonaws.com/models.huggingface.co/bert/bert-large-uncased-whole-word-masking-config.jsonzchttps://s3.amazonaws.com/models.huggingface.co/bert/bert-large-cased-whole-word-masking-config.jsonzuhttps://s3.amazonaws.com/models.huggingface.co/bert/bert-large-uncased-whole-word-masking-finetuned-squad-config.jsonzshttps://s3.amazonaws.com/models.huggingface.co/bert/bert-large-cased-whole-word-masking-finetuned-squad-config.jsonz^https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-cased-finetuned-mrpc-config.jsonz\https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-cased-config.jsonz^https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-uncased-config.jsonz\https://s3.amazonaws.com/models.huggingface.co/bert/cl-tohoku/bert-base-japanese/config.jsonzohttps://s3.amazonaws.com/models.huggingface.co/bert/cl-tohoku/bert-base-japanese-whole-word-masking/config.jsonzahttps://s3.amazonaws.com/models.huggingface.co/bert/cl-tohoku/bert-base-japanese-char/config.jsonzthttps://s3.amazonaws.com/models.huggingface.co/bert/cl-tohoku/bert-base-japanese-char-whole-word-masking/config.jsonzchttps://s3.amazonaws.com/models.huggingface.co/bert/TurkuNLP/bert-base-finnish-cased-v1/config.jsonzehttps://s3.amazonaws.com/models.huggingface.co/bert/TurkuNLP/bert-base-finnish-uncased-v1/config.jsonz^https://s3.amazonaws.com/models.huggingface.co/bert/wietsedv/bert-base-dutch-cased/config.json)zbert-base-uncasedzbert-large-uncasedzbert-base-casedzbert-large-casedzbert-base-multilingual-uncasedzbert-base-multilingual-casedzbert-base-chinesezbert-base-german-casedz%bert-large-uncased-whole-word-maskingz#bert-large-cased-whole-word-maskingz5bert-large-uncased-whole-word-masking-finetuned-squadz3bert-large-cased-whole-word-masking-finetuned-squadzbert-base-cased-finetuned-mrpczbert-base-german-dbmdz-casedzbert-base-german-dbmdz-uncasedzbert-base-japanesez%bert-base-japanese-whole-word-maskingzbert-base-japanese-charz*bert-base-japanese-char-whole-word-maskingzbert-base-finnish-cased-v1zbert-base-finnish-uncased-v1zbert-base-dutch-casedc s*eZdZdZeZdZd‡fdd„ Z‡ZS)Ú BertConfiga¼ This is the configuration class to store the configuration of a :class:`~transformers.BertModel`. It is used to instantiate an 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 BERT `bert-base-uncased `__ architecture. Configuration objects inherit from :class:`~transformers.PretrainedConfig` and can be used to control the model outputs. Read the documentation from :class:`~transformers.PretrainedConfig` for more information. Args: vocab_size (:obj:`int`, optional, defaults to 30522): Vocabulary size of the BERT model. Defines the different tokens that can be represented by the `inputs_ids` passed to the forward method of :class:`~transformers.BertModel`. hidden_size (:obj:`int`, optional, defaults to 768): Dimensionality of the encoder layers and the pooler layer. num_hidden_layers (:obj:`int`, optional, defaults to 12): Number of hidden layers in the Transformer encoder. num_attention_heads (:obj:`int`, optional, defaults to 12): Number of attention heads for each attention layer in the Transformer encoder. intermediate_size (:obj:`int`, optional, defaults to 3072): Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. hidden_act (:obj:`str` or :obj:`function`, optional, defaults to "gelu"): The non-linear activation function (function or string) in the encoder and pooler. If string, "gelu", "relu", "swish" and "gelu_new" are supported. hidden_dropout_prob (:obj:`float`, optional, defaults to 0.1): The dropout probabilitiy for all fully connected layers in the embeddings, encoder, and pooler. attention_probs_dropout_prob (:obj:`float`, optional, defaults to 0.1): The dropout ratio for the attention probabilities. max_position_embeddings (:obj:`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 (:obj:`int`, optional, defaults to 2): The vocabulary size of the `token_type_ids` passed into :class:`~transformers.BertModel`. initializer_range (:obj:`float`, optional, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. layer_norm_eps (:obj:`float`, optional, defaults to 1e-12): The epsilon used by the layer normalization layers. Example:: from transformers import BertModel, BertConfig # Initializing a BERT bert-base-uncased style configuration configuration = BertConfig() # Initializing a model from the bert-base-uncased style configuration model = BertModel(configuration) # Accessing the model configuration configuration = model.config Attributes: pretrained_config_archive_map (Dict[str, str]): A dictionary containing all the available pre-trained checkpoints. 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