Add more algorithms

lib/config_utils/cls_kd_args.py

@@ -0,0 +1,26 @@
+##################################################
+# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019 #
+##################################################
+import os, sys, time, random, argparse
+from .share_args import add_shared_args
+
+def obtain_cls_kd_args():
+  parser = argparse.ArgumentParser(description='Train a classification model on typical image classification datasets.', formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+  parser.add_argument('--resume'      ,     type=str,                   help='Resume path.')
+  parser.add_argument('--init_model'  ,     type=str,                   help='The initialization model path.')
+  parser.add_argument('--model_config',     type=str,                   help='The path to the model configuration')
+  parser.add_argument('--optim_config',     type=str,                   help='The path to the optimizer configuration')
+  parser.add_argument('--procedure'   ,     type=str,                   help='The procedure basic prefix.')
+  parser.add_argument('--KD_checkpoint',    type=str,                   help='The teacher checkpoint in knowledge distillation.')
+  parser.add_argument('--KD_alpha'    ,     type=float,                 help='The alpha parameter in knowledge distillation.')
+  parser.add_argument('--KD_temperature',   type=float,                 help='The temperature parameter in knowledge distillation.')
+  #parser.add_argument('--KD_feature',       type=float,                 help='Knowledge distillation at the feature level.')
+  add_shared_args( parser )
+  # Optimization options
+  parser.add_argument('--batch_size',       type=int,   default=2,      help='Batch size for training.')
+  args = parser.parse_args()
+
+  if args.rand_seed is None or args.rand_seed < 0:
+    args.rand_seed = random.randint(1, 100000)
+  assert args.save_dir is not None, 'save-path argument can not be None'
+  return args