Clean unnecessary files

others/GDAS/exps-cnn/evaluate.py

@@ -1,53 +0,0 @@
-##################################################
-# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019 #
-##################################################
-# For evaluating the learned model
-import os, sys, time, glob, random, argparse
-import numpy as np
-from copy import deepcopy
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import torchvision.datasets as dset
-import torch.backends.cudnn as cudnn
-import torchvision.transforms as transforms
-from pathlib import Path
-lib_dir = (Path(__file__).parent / '..' / 'lib').resolve()
-if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir))
-from utils import AverageMeter, time_string, convert_secs2time
-from utils import print_log, obtain_accuracy
-from utils import Cutout, count_parameters_in_MB
-from nas import model_types as models
-from train_utils import main_procedure
-from train_utils_imagenet import main_procedure_imagenet
-from scheduler import load_config
-
-
-parser = argparse.ArgumentParser("Evaluate-CNN")
-parser.add_argument('--data_path',         type=str,   help='Path to dataset.')
-parser.add_argument('--checkpoint',        type=str,   help='Choose between Cifar10/100 and ImageNet.')
-args = parser.parse_args()
-
-assert torch.cuda.is_available(), 'torch.cuda is not available'
-
-
-def main():
-
-  assert os.path.isdir( args.data_path ), 'invalid data-path : {:}'.format(args.data_path)
-  assert os.path.isfile( args.checkpoint ), 'invalid checkpoint : {:}'.format(args.checkpoint)
-
-  checkpoint = torch.load( args.checkpoint )
-  xargs      = checkpoint['args']
-  config     = load_config(xargs.model_config)
-  genotype   = models[xargs.arch]
-
-  # clear GPU cache
-  torch.cuda.empty_cache()
-  if xargs.dataset == 'imagenet':
-    main_procedure_imagenet(config, args.data_path, xargs, genotype, xargs.init_channels, xargs.layers, checkpoint['state_dict'], None)
-  else:
-    main_procedure(config, xargs.dataset, args.data_path, xargs, genotype, xargs.init_channels, xargs.layers, checkpoint['state_dict'], None)
-
-
-if __name__ == '__main__':
-  main()