class_docstr: BIST parser model class.
  This class handles training, prediction, loading and saving of a BIST parser model.
  After the model is initialized, it accepts a CoNLL formatted dataset as input, and learns to
  output dependencies for new input.
  
  Args:
      activation (str, optional): Activation function to use.
      lstm_layers (int, optional): Number of LSTM layers to use.
      lstm_dims (int, optional): Number of LSTM dimensions to use.
      pos_dims (int, optional): Number of part-of-speech embedding dimensions to use.
  
  Attributes:
      model (MSTParserLSTM): The underlying LSTM model.
      params (tuple): Additional parameters and resources for the model.
      options (dict): User model options.
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docstr: Runs inference with the BIST model on a dataset in CoNLL file format.
  
  Args:
      dataset (str): Path to input CoNLL file.
      evaluate (bool, optional): Write prediction and evaluation files to dataset's folder.
  Returns:
      res (list of list of ConllEntry): The list of input sentences with predicted
      dependencies attached.
docstr_tok: ["Runs","inference","with","the","BIST","model","on","a","dataset","in","CoNLL","file","format",".","Args",":","dataset","(","str",")",":","Path","to","input","CoNLL","file",".","evaluate","(","bool",",","optional",")",":","Write","prediction","and","evaluation","files","to","dataset","'s","folder",".","Returns",":","res","(","list","of","list","of","ConllEntry",")",":","The","list","of","input","sentences","with","predicted","dependencies","attached","."]
code: def predict(self, dataset, evaluate=False):
      """
      Runs inference with the BIST model on a dataset in CoNLL file format.
  
      Args:
          dataset (str): Path to input CoNLL file.
          evaluate (bool, optional): Write prediction and evaluation files to dataset's folder.
      Returns:
          res (list of list of ConllEntry): The list of input sentences with predicted
          dependencies attached.
      """
      dataset = validate_existing_filepath(dataset)
      validate((evaluate, bool))
  
      print("\nRunning predict on " + dataset + "...\n")
      res = list(self.model.predict(conll_path=dataset))
      if evaluate:
          ext = dataset.rindex(".")
          pred_path = dataset[:ext] + "_pred" + dataset[ext:]
          utils.write_conll(pred_path, res)
          utils.run_eval(dataset, pred_path)
      return res
  
file_path: nlp-architect/nlp_architect/models/bist_parser.py
imports: import json
  import os
  from nlp_architect.models.bist import utils
  from nlp_architect.models.bist.utils import get_options_dict
  from nlp_architect.utils.io import validate, validate_existing_filepath
label_desc: Use image node_id 3 for calling the BISTModel obj's underlying member method code with example usage: obj.predict(dataset, evaluate) and returns: res