def __init__()

in mico/model/mico.py [0:0]

• 25 lines of code
• 2 McCabe index (conditional complexity)

    def __init__(self, hparams):
        """We initialize all the parameters for 
                the document assignment model P(Z|Y) which is `self.p_z_y`, where Z is the cluster index to which a document Y is assigned.
                the query routing model P(Z|X) which is `self.q_z_x`, where Z is the cluster index to which a query X is routed.
                the model for approximating the distribution of cluster sizes of document assignment E_Y[P(Z|Y)] which is `self.q_z`, 
                (For details, please check https://arxiv.org/pdf/2209.04378.pdf)

        We load the BERT model and its corresponding tokenizer.


        Parameters
        ----------
        hparams : argparse result
            All the hyper-parameters for MICO. This will also be used in training.

        """
        super().__init__()
        self.hparams = hparams
        self.p_z_y = ConditionalDistributionZ(self.hparams.number_clusters,
                                              self.hparams.dim_input,
                                              self.hparams.num_layers_posterior,
                                              self.hparams.dim_hidden)
        self.q_z = MarginalDistributionZ(self.hparams.number_clusters)
        self.q_z_x = ConditionalDistributionZ(self.hparams.number_clusters,
                                              self.hparams.dim_input,
                                              self.hparams.num_layers_posterior,
                                              self.hparams.dim_hidden)

        self.apply(get_init_function(self.hparams.init))

        try:
            tokenizer = BertTokenizerFast.from_pretrained('bert-base-multilingual-cased', local_files_only=True)
            config_bert = BertConfig.from_pretrained("bert-base-multilingual-cased", output_hidden_states=True,
                                                     local_files_only=True)
            model_bert = BertModel.from_pretrained("bert-base-multilingual-cased", config=config_bert,
                                                   local_files_only=True)
        except:
            # Connect to Internet to download the Huggingface tokenizer, config, and model.
            tokenizer = BertTokenizerFast.from_pretrained('bert-base-multilingual-cased')
            config_bert = BertConfig.from_pretrained("bert-base-multilingual-cased", output_hidden_states=True)
            model_bert = BertModel.from_pretrained("bert-base-multilingual-cased", config=config_bert)

        self.model_bert = model_bert
        self.tokenizer = tokenizer