class_docstr: Constructor for the Polymer class.
  :param dataset_path is the path to the dataset
  :param save_model: whether the model should be saved in a .sav file
class_docstr_tok: ["Constructor","for","the","Polymer","class",".",":","param","dataset_path","is","the","path","to","the","dataset",":","param","save_model",":","whether","the","model","should","be","saved","in","a",".sav","file"]
code: def predict(self, file_path):
      the_model = self.model
      df = pd.read_csv(file_path)
  
      request_info = {
          "df": df,
          "json": self.json_file,
          "y": None,
          "model": "None",
          "analysis": None,
          "custom": self.custom_files,
          "pca": self.runPCA,
      }
  
      request_info = preprocess_module_inference(request_info)
  
      final_df = pd.concat(
          [request_info["df"]["train"], request_info["df"]["test"]],
          axis=0,
      )
  
      model = self.model
      output = model.predict(final_df)
      return output
  
file_path: nylon/nylon/query.py
imports: from pandas.core.algorithms import mode
  from nylon.supplementaries.main import dataset_initializer
  from nylon.supplementaries.handlers import preprocess_module, modeling_module, analysis_module, perform_inference
  import uuid
  import pandas
label_desc: Use image node_id 9 for calling the Polymer obj's underlying member method code with example usage: obj.predict(file_path) and returns: output