class_docstr: SVM trainer that takes care of training (using k-fold cross validation),
  and evaluating the SVMs
class_docstr_tok: ["SVM","trainer","that","takes","care","of","training","(","using","k-fold","cross","validation",")",",","and","evaluating","the","SVMs"]
code: def _get_svm_model_filename(self, cls_num, cost):
      cls_cost = str(cls_num) + "_cost" + str(float(cost))
      out_file = f"{self.output_dir}/cls{cls_cost}.pickle"
      ap_matrix_out_file = f"{self.output_dir}/AP_cls{cls_cost}.npy"
      return out_file, ap_matrix_out_file
  
imports: import logging
  import pickle
  import threading
  import numpy
  from iopath.common.file_io import g_pathmgr
  from sklearn.model_selection import cross_val_score
  from sklearn.svm import LinearSVC
  from vissl.utils.io import load_file, save_file
  from vissl.utils.svm_utils.evaluate import get_precision_recall
label_desc: Use image node_id 7 for calling the SVMTrainer obj's underlying member method code with example usage: obj._get_svm_model_filename(cls_num, cost) and returns: out_file,  ap_matrix_out_file