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