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.
class_docstr_tok: ["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","."]
code: def __init__(
      self, activation="tanh", lstm_layers=2, lstm_dims=125, pos_dims=25
  ):
      validate(
          (activation, str),
          (lstm_layers, int, 0, None),
          (lstm_dims, int, 0, 1000),
          (pos_dims, int, 0, 1000),
      )
      self.options = get_options_dict(
          activation, lstm_dims, lstm_layers, pos_dims
      )
      self.params = None
      self.model = None
  
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 1 to create a new BISTModel object from inherited base classes: object with example: obj = BISTModel(activation, lstm_layers, lstm_dims, pos_dims)