class_docstr: Vowpal Wabbit Class
docstr: Parse input hyper-parameters to build vw train commands
  
  Args:
      params (dict): key = parameter, value = value (use True if parameter is just a flag)
  
  Returns:
      list[str]: vw command line parameters as list of strings
docstr_tok: ["Parse","input","hyper-parameters","to","build","vw","train","commands","Args",":","params","(","dict",")",":","key","=","parameter",",","value","=","value","(","use","True","if","parameter","is","just","a","flag",")","Returns",":","list","[","str","]",":","vw","command","line","parameters","as","list","of","strings"]
code: def parse_train_params(self, params):
      """Parse input hyper-parameters to build vw train commands
  
      Args:
          params (dict): key = parameter, value = value (use True if parameter is just a flag)
  
      Returns:
          list[str]: vw command line parameters as list of strings
      """
  
      # make a copy of the original hyper parameters
      train_params = params.copy()
  
      # remove options that are handled internally, not supported, or test only parameters
      invalid = [
          "data",
          "final_regressor",
          "invert_hash",
          "readable_model",
          "t",
          "testonly",
          "i",
          "initial_regressor",
          "link",
      ]
  
      for option in invalid:
          if option in train_params:
              del train_params[option]
  
      train_params.update(
          {
              "d": self.train_file,
              "f": self.model_file,
              "quiet": params.get("quiet", True),
          }
      )
      return self.to_vw_cmd(params=train_params)
  
file_path: recommenders/recommenders/models/vowpal_wabbit/vw.py
imports: import os
  from subprocess import run
  from tempfile import TemporaryDirectory
  import pandas
  from recommenders.utils.constants import DEFAULT_USER_COL, DEFAULT_ITEM_COL, DEFAULT_RATING_COL, DEFAULT_TIMESTAMP_COL, DEFAULT_PREDICTION_COL
label_desc: Use image node_id 3 for calling the VW obj's underlying member method code with example usage: obj.parse_train_params(params) and returns: self