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#!/usr/bin/python | |
import itertools | |
import subprocess | |
import csv | |
with open('tensorflow_bench_result.csv', 'wb') as csvFile: | |
csvWriter = csv.writer(csvFile, quoting=csv.QUOTE_ALL) | |
#gpus = ['0', '1', '2', '3', '4', '5', '6', '7'] | |
#batch_size = ['32', '64', '128'] | |
#model = ['alexnet', 'resnet50', 'vgg16', 'inception3'] | |
gpus = ['0', '1', '2', '3'] | |
batch_size = ['32'] | |
model = ['alexnet', 'resnet50'] | |
for L in range(2, len(gpus)): | |
for subset in set(itertools.combinations(gpus, L)): | |
chosenGPUs = ','.join(subset) | |
print(chosenGPUs) | |
for i in range(len(batch_size)): | |
chosenBatchSize = batch_size[i] | |
print('\t' + chosenBatchSize) | |
for j in range(len(model)): | |
chosenModel = model[j] | |
print('\t\t' + chosenModel) | |
output = subprocess.check_output(['docker', 'run', '--rm', '-it', '--runtime=nvidia', '-e', 'NVIDIA_VISIBLE_DEVICES=' + chosenGPUs, 'tangzhankun/tensorflow_benchmark:topo', '/notebooks/run_benchmark.sh', str(L), chosenBatchSize, chosenModel]) | |
lines = output.split('\n') | |
FPSline = lines[len(lines)-3]; | |
FPStoken = FPSline.split(':') | |
FPS = FPStoken[1].strip() | |
csvLine = [] | |
csvLine.append(chosenModel) | |
csvLine.append(chosenBatchSize) | |
csvLine.append('-'.join(subset)) | |
csvLine.append(unicode(FPS, "utf-8")) | |
#csvWriter.writerow(['Spam', 'Lovely Spam', 'Wonderful Spam']) | |
csvWriter.writerow(csvLine) | |
csvFile.flush() | |
print('\t\t\t csv line:' + ",".join(csvLine)) | |
#docker run --rm -it --runtime=nvidia -e "NVIDIA_VISIBLE_DEVICES=0,1,2,3" tangzhankun/tensorflow_benchmark:topo /notebooks/run_benchmark.sh 2 32 resnet50 |
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