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Update REA, REINFORCE, RANDOM, and BOHB

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D-X-Y
2020-07-14 11:53:21 +00:00
parent 168b08d9e6
commit 2c861f33c4
8 changed files with 79 additions and 88 deletions
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24
exps/experimental/vis-bench-algos.py
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@@ -5,7 +5,7 @@
###############################################################
# Usage: python exps/experimental/vis-bench-algos.py #
###############################################################
import os, sys, time, torch, argparse
import os, gc, sys, time, torch, argparse
import numpy as np
from typing import List, Text, Dict, Any
from shutil import copyfile
@@ -31,6 +31,7 @@ def fetch_data(root_dir='./output/search', search_space='tss', dataset=None):
alg2name['REA'] = 'R-EA-SS3'
alg2name['REINFORCE'] = 'REINFORCE-0.001'
alg2name['RANDOM'] = 'RANDOM'
alg2name['BOHB'] = 'BOHB'
for alg, name in alg2name.items():
alg2path[alg] = os.path.join(ss_dir, dataset, name, 'results.pth')
assert os.path.isfile(alg2path[alg]), 'invalid path : {:}'.format(alg2path[alg])
@@ -58,14 +59,27 @@ def query_performance(api, data, dataset, ticket):
results.append(interplate)
return sum(results) / len(results)
y_min_s = {('cifar10', 'tss'): 90,
('cifar10', 'sss'): 92,
('cifar100', 'tss'): 65,
('cifar100', 'sss'): 65,
('ImageNet16-120', 'tss'): 36,
('ImageNet16-120', 'sss'): 40}
y_max_s = {('cifar10', 'tss'): 94.5,
('cifar10', 'sss'): 93.3,
('cifar100', 'tss'): 72,
('cifar100', 'sss'): 70,
('ImageNet16-120', 'tss'): 44,
('ImageNet16-120', 'sss'): 46}
def visualize_curve(api, vis_save_dir, search_space, max_time):
vis_save_dir = vis_save_dir.resolve()
vis_save_dir.mkdir(parents=True, exist_ok=True)
dpi, width, height = 250, 5100, 1500
dpi, width, height = 250, 5200, 1400
figsize = width / float(dpi), height / float(dpi)
LabelSize, LegendFontsize = 14, 14
LabelSize, LegendFontsize = 16, 16
def sub_plot_fn(ax, dataset):
alg2data = fetch_data(search_space=search_space, dataset=dataset)
@@ -73,6 +87,8 @@ def visualize_curve(api, vis_save_dir, search_space, max_time):
total_tickets = 150
time_tickets = [float(i) / total_tickets * max_time for i in range(total_tickets)]
colors = ['b', 'g', 'c', 'm', 'y']
ax.set_xlim(0, 200)
ax.set_ylim(y_min_s[(dataset, search_space)], y_max_s[(dataset, search_space)])
for idx, (alg, data) in enumerate(alg2data.items()):
print('plot alg : {:}'.format(alg))
accuracies = []
@@ -107,5 +123,7 @@ if __name__ == '__main__':
api201 = NASBench201API(verbose=False)
visualize_curve(api201, save_dir, 'tss', args.max_time)
del api201
gc.collect()
api301 = NASBench301API(verbose=False)
visualize_curve(api301, save_dir, 'sss', args.max_time)