112 lines
4.2 KiB
Python
112 lines
4.2 KiB
Python
##############################################################################
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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], 2020.08 #
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##############################################################################
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# Usage: python exps/NATS-Bench/test-nats-api.py #
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##############################################################################
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import os, gc, 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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from xautodl.config_utils import dict2config, load_config
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from xautodl.log_utils import time_string
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from xautodl.models import get_cell_based_tiny_net, CellStructure
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from nats_bench import create
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def test_api(api, sss_or_tss=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 sss_or_tss 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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for index in [13, 15, 19, 200]:
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info = api.get_latency(index, "cifar10")
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# Count the number of architectures
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info = api.statistics("cifar100", "12")
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print("{:} statistics results : {:}\n".format(time_string(), 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 sss_or_tss:
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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 : {:}\n\n".format(info))
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if __name__ == "__main__":
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# api201 = create('./output/NATS-Bench-topology/process-FULL', 'topology', fast_mode=True, verbose=True)
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for fast_mode in [True, False]:
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for verbose in [True, False]:
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api_nats_tss = create(None, "tss", fast_mode=fast_mode, verbose=True)
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print(
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"{:} create with fast_mode={:} and verbose={:}".format(
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time_string(), fast_mode, verbose
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)
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)
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test_api(api_nats_tss, False)
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del api_nats_tss
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gc.collect()
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for fast_mode in [True, False]:
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for verbose in [True, False]:
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print(
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"{:} create with fast_mode={:} and verbose={:}".format(
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time_string(), fast_mode, verbose
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)
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)
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api_nats_sss = create(None, "size", fast_mode=fast_mode, verbose=True)
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print("{:} --->>> {:}".format(time_string(), api_nats_sss))
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test_api(api_nats_sss, True)
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del api_nats_sss
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gc.collect()
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