Update NATS-Bench (sss version 1.2)
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###############################################################
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# NAS-Bench-201, ICLR 2020 (https://arxiv.org/abs/2001.00326) #
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###############################################################
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# NATS-Bench: Benchmarking NAS algorithms for Architecture Topology and Size
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###############################################################
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# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2020.06 #
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###############################################################
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# Usage: python exps/NAS-Bench-201/test-nas-api.py #
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###############################################################
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import os, sys, time, torch, argparse
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import numpy as np
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from typing import List, Text, Dict, Any
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from shutil import copyfile
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from collections import defaultdict
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from copy import deepcopy
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from pathlib import Path
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import matplotlib
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import seaborn as sns
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matplotlib.use('agg')
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import matplotlib.pyplot as plt
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import matplotlib.ticker as ticker
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lib_dir = (Path(__file__).parent / '..' / '..' / 'lib').resolve()
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if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir))
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from config_utils import dict2config, load_config
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from nats_bench import create
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from log_utils import time_string
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from models import get_cell_based_tiny_net, CellStructure
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def test_api(api, is_301=True):
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print('{:} start testing the api : {:}'.format(time_string(), api))
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api.clear_params(12)
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api.reload(index=12)
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# Query the informations of 1113-th architecture
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info_strs = api.query_info_str_by_arch(1113)
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print(info_strs)
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info = api.query_by_index(113)
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print('{:}\n'.format(info))
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info = api.query_by_index(113, 'cifar100')
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print('{:}\n'.format(info))
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info = api.query_meta_info_by_index(115, '90' if is_301 else '200')
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print('{:}\n'.format(info))
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for dataset in ['cifar10', 'cifar100', 'ImageNet16-120']:
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for xset in ['train', 'test', 'valid']:
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best_index, highest_accuracy = api.find_best(dataset, xset)
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print('')
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params = api.get_net_param(12, 'cifar10', None)
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# Obtain the config and create the network
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config = api.get_net_config(12, 'cifar10')
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print('{:}\n'.format(config))
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network = get_cell_based_tiny_net(config)
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network.load_state_dict(next(iter(params.values())))
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# Obtain the cost information
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info = api.get_cost_info(12, 'cifar10')
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print('{:}\n'.format(info))
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info = api.get_latency(12, 'cifar10')
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print('{:}\n'.format(info))
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# Count the number of architectures
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info = api.statistics('cifar100', '12')
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print('{:}\n'.format(info))
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# Show the information of the 123-th architecture
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api.show(123)
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# Obtain both cost and performance information
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info = api.get_more_info(1234, 'cifar10')
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print('{:}\n'.format(info))
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print('{:} finish testing the api : {:}'.format(time_string(), api))
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if not is_301:
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arch_str = '|nor_conv_3x3~0|+|nor_conv_3x3~0|avg_pool_3x3~1|+|skip_connect~0|nor_conv_3x3~1|skip_connect~2|'
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matrix = api.str2matrix(arch_str)
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print('Compute the adjacency matrix of {:}'.format(arch_str))
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print(matrix)
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info = api.simulate_train_eval(123, 'cifar10')
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print('simulate_train_eval : {:}'.format(info))
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def test_issue_81_82(api):
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results = api.query_by_index(0, 'cifar10-valid', hp='12')
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results = api.query_by_index(0, 'cifar10-valid', hp='200')
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print(list(results.keys()))
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print(results[888].get_eval('valid'))
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print(results[888].get_eval('x-valid'))
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result_dict = api.get_more_info(index=0, dataset='cifar10-valid', iepoch=11, hp='200', is_random=False)
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info = api.query_by_arch('|nor_conv_3x3~0|+|skip_connect~0|nor_conv_3x3~1|+|skip_connect~0|none~1|nor_conv_3x3~2|', '200')
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print(info)
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structure = CellStructure.str2structure('|nor_conv_3x3~0|+|skip_connect~0|nor_conv_3x3~1|+|skip_connect~0|none~1|nor_conv_3x3~2|')
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info = api.query_by_arch(structure, '200')
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print(info)
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if __name__ == '__main__':
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api201 = create(os.path.join(os.environ['TORCH_HOME'], 'NAS-Bench-201-v1_0-e61699.pth'), 'topology', True)
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test_issue_81_82(api201)
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print ('Test {:} done'.format(api201))
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api201 = create(None, 'topology', True) # use the default file path
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test_issue_81_82(api201)
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test_api(api201, False)
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print ('Test {:} done'.format(api201))
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api301 = create(None, 'size', True)
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test_api(api301, True)
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