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# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019.08 #
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# python exps/NAS-Bench-201/test-correlation.py --api_path $HOME/.torch/NAS-Bench-201-v1_0-e61699.pth
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import sys, argparse
import numpy as np
from copy import deepcopy
from tqdm import tqdm
import torch
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 log_utils import time_string
from models import CellStructure
from nas_201_api import NASBench201API as API
def check_unique_arch(meta_file):
api = API(str(meta_file))
arch_strs = deepcopy(api.meta_archs)
xarchs = [CellStructure.str2structure(x) for x in arch_strs]
def get_unique_matrix(archs, consider_zero):
UniquStrs = [arch.to_unique_str(consider_zero) for arch in archs]
print ('{:} create unique-string ({:}/{:}) done'.format(time_string(), len(set(UniquStrs)), len(UniquStrs)))
Unique2Index = dict()
for index, xstr in enumerate(UniquStrs):
if xstr not in Unique2Index: Unique2Index[xstr] = list()
Unique2Index[xstr].append( index )
sm_matrix = torch.eye(len(archs)).bool()
for _, xlist in Unique2Index.items():
for i in xlist:
for j in xlist:
sm_matrix[i,j] = True
unique_ids, unique_num = [-1 for _ in archs], 0
for i in range(len(unique_ids)):
if unique_ids[i] > -1: continue
neighbours = sm_matrix[i].nonzero().view(-1).tolist()
for nghb in neighbours:
assert unique_ids[nghb] == -1, 'impossible'
unique_ids[nghb] = unique_num
unique_num += 1
return sm_matrix, unique_ids, unique_num
print ('There are {:} valid-archs'.format( sum(arch.check_valid() for arch in xarchs) ))
sm_matrix, uniqueIDs, unique_num = get_unique_matrix(xarchs, None)
print ('{:} There are {:} unique architectures (considering nothing).'.format(time_string(), unique_num))
sm_matrix, uniqueIDs, unique_num = get_unique_matrix(xarchs, False)
print ('{:} There are {:} unique architectures (not considering zero).'.format(time_string(), unique_num))
sm_matrix, uniqueIDs, unique_num = get_unique_matrix(xarchs, True)
print ('{:} There are {:} unique architectures (considering zero).'.format(time_string(), unique_num))
def check_cor_for_bandit(meta_file, test_epoch, use_less_or_not, is_rand=True, need_print=False):
if isinstance(meta_file, API):
api = meta_file
else:
api = API(str(meta_file))
cifar10_currs = []
cifar10_valid = []
cifar10_test = []
cifar100_valid = []
cifar100_test = []
imagenet_test = []
imagenet_valid = []
for idx, arch in enumerate(api):
results = api.get_more_info(idx, 'cifar10-valid' , test_epoch-1, use_less_or_not, is_rand)
cifar10_currs.append( results['valid-accuracy'] )
# --->>>>>
results = api.get_more_info(idx, 'cifar10-valid' , None, False, is_rand)
cifar10_valid.append( results['valid-accuracy'] )
results = api.get_more_info(idx, 'cifar10' , None, False, is_rand)
cifar10_test.append( results['test-accuracy'] )
results = api.get_more_info(idx, 'cifar100' , None, False, is_rand)
cifar100_test.append( results['test-accuracy'] )
cifar100_valid.append( results['valid-accuracy'] )
results = api.get_more_info(idx, 'ImageNet16-120', None, False, is_rand)
imagenet_test.append( results['test-accuracy'] )
imagenet_valid.append( results['valid-accuracy'] )
def get_cor(A, B):
return float(np.corrcoef(A, B)[0,1])
cors = []
for basestr, xlist in zip(['C-010-V', 'C-010-T', 'C-100-V', 'C-100-T', 'I16-V', 'I16-T'], [cifar10_valid, cifar10_test, cifar100_valid, cifar100_test, imagenet_valid, imagenet_test]):
correlation = get_cor(cifar10_currs, xlist)
if need_print: print ('With {:3d}/{:}-epochs-training, the correlation between cifar10-valid and {:} is : {:}'.format(test_epoch, '012' if use_less_or_not else '200', basestr, correlation))
cors.append( correlation )
#print ('With {:3d}/200-epochs-training, the correlation between cifar10-valid and {:} is : {:}'.format(test_epoch, basestr, get_cor(cifar10_valid_200, xlist)))
#print('-'*200)
#print('*'*230)
return cors
def check_cor_for_bandit_v2(meta_file, test_epoch, use_less_or_not, is_rand):
corrs = []
for i in tqdm(range(100)):
x = check_cor_for_bandit(meta_file, test_epoch, use_less_or_not, is_rand, False)
corrs.append( x )
#xstrs = ['CIFAR-010', 'C-100-V', 'C-100-T', 'I16-V', 'I16-T']
xstrs = ['C-010-V', 'C-010-T', 'C-100-V', 'C-100-T', 'I16-V', 'I16-T']
correlations = np.array(corrs)
print('------>>>>>>>> {:03d}/{:} >>>>>>>> ------'.format(test_epoch, '012' if use_less_or_not else '200'))
for idx, xstr in enumerate(xstrs):
print ('{:8s} ::: mean={:.4f}, std={:.4f} :: {:.4f}\\pm{:.4f}'.format(xstr, correlations[:,idx].mean(), correlations[:,idx].std(), correlations[:,idx].mean(), correlations[:,idx].std()))
print('')
if __name__ == '__main__':
parser = argparse.ArgumentParser("Analysis of NAS-Bench-201")
parser.add_argument('--save_dir', type=str, default='./output/search-cell-nas-bench-201/visuals', help='The base-name of folder to save checkpoints and log.')
parser.add_argument('--api_path', type=str, default=None, help='The path to the NAS-Bench-201 benchmark file.')
args = parser.parse_args()
vis_save_dir = Path(args.save_dir)
vis_save_dir.mkdir(parents=True, exist_ok=True)
meta_file = Path(args.api_path)
assert meta_file.exists(), 'invalid path for api : {:}'.format(meta_file)
#check_unique_arch(meta_file)
api = API(str(meta_file))
#for iepoch in [11, 25, 50, 100, 150, 175, 200]:
# check_cor_for_bandit(api, 6, iepoch)
# check_cor_for_bandit(api, 12, iepoch)
check_cor_for_bandit_v2(api, 6, True, True)
check_cor_for_bandit_v2(api, 12, True, True)
check_cor_for_bandit_v2(api, 12, False, True)
check_cor_for_bandit_v2(api, 24, False, True)
check_cor_for_bandit_v2(api, 100, False, True)
check_cor_for_bandit_v2(api, 150, False, True)
check_cor_for_bandit_v2(api, 175, False, True)
check_cor_for_bandit_v2(api, 200, False, True)
print('----')